CN111854753B

CN111854753B - Modeling method for indoor space

Info

Publication number: CN111854753B
Application number: CN202010489717.2A
Authority: CN
Inventors: 栾世壹
Original assignee: Shenzhen Panoramic Space Industry Co ltd
Current assignee: Shenzhen Panoramic Space Industry Co ltd
Priority date: 2020-06-02
Filing date: 2020-06-02
Publication date: 2023-05-23
Anticipated expiration: 2040-06-02
Also published as: CN111854753A

Abstract

The invention relates to a modeling method of indoor space, comprising the following steps: receiving location information of a plurality of integrated sensors from the plurality of integrated sensors; based on the grouping of the plurality of integrated sensors, obtaining partition information of the indoor space; and obtaining size information of the partition based on the position information of the plurality of integrated sensors. According to the modeling method of the indoor space, the indoor space model can be built through the detection result of one or more of the plurality of sensors of the sensor network. And the indoor environment is further perceived through the built indoor space model. After sensing the indoor environment, the indoor electric appliances can be controlled to adjust the indoor environment.

Description

Modeling method for indoor space

Technical Field

The invention relates to the technical field of sensors, in particular to a modeling method of indoor space.

Background

Sensor technology has gained rapid development in this century as one of the important support posts for modern information technology. Various sensor layers based on semiconductor materials, crystalline materials, ceramic materials, organic composite materials, metal materials, polymer materials, superconducting materials, optical fiber materials, and nanomaterials are endless, and are beginning to gradually enter the home.

Indoor space modeling is to build a model of indoor space. In the prior art, the layout of the indoor space is generally unchanged. For example, there are several rooms in a house and the size and orientation of each room are rarely adjusted. However, for future intelligent houses, the layout of the indoor space can be easily changed. The data center may store an externally input indoor space model when the room layout is not changed. However, when the room layout is frequently changed, it becomes very inconvenient to input the indoor space model from the outside every time. Therefore, there is an urgent need in the art for a specific spatial modeling manner that can automatically collect indoor space information according to a change of indoor space structure or layout so as to be able to adapt to a future smart home. .

Disclosure of Invention

Aiming at the technical problems in the prior art, the application provides a modeling method for indoor space, which comprises the following steps: receiving location information of a plurality of integrated sensors from the plurality of integrated sensors; based on the grouping of the plurality of integrated sensors, obtaining partition information of the indoor space; and obtaining size information of the partition based on the position information of the plurality of integrated sensors.

The method as described above, wherein the integrated sensor is configured to detect one or more environmental parameters of the indoor environment and/or one or more human parameters of a person moving indoors.

A method as above wherein an environmental or body parameter is determined in common from a plurality of detection results from one or more of the plurality of integrated sensors.

A method as above wherein the integrated sensor is configured to detect commands issued by a person moving indoors.

A method as above wherein the location information comprises altitude.

A method as above wherein the location information comprises horizontal relative location information.

The method as described above, further comprising: grouping information of the plurality of integrated sensors is received from the plurality of integrated sensors.

The method as described above, further comprising: grouping the plurality of integrated sensors, and obtaining partition information of the indoor space based on grouping information obtained after grouping.

A method as described above, wherein the grouping of the plurality of integrated sensors is based at least in part on shape matching.

A method as above, wherein the grouping of the plurality of integrated sensors is based at least in part on region partitioning.

The method as described above, wherein the area division is based on detection results of the plurality of integrated sensors.

The method as described above, further comprising receiving location attribute information from the plurality of integrated sensors.

The method as described above, further comprising obtaining characteristic information of the partition of the indoor space based at least in part on the location attribute information of the plurality of integrated sensors.

A method as above wherein the location attribute information comprises an arc of where the location is located.

The method as described above, wherein the location attribute information includes a convexity and concavity of the location.

The method as described above, wherein the location attribute information includes a function area to which the location belongs.

A method as above wherein the location attribute information comprises indoor facilities around the location.

According to another aspect of the present application, a system for modeling indoor space is presented, comprising: a plurality of integrated sensors distributed in the indoor space; and a data center in communication with the plurality of integrated sensors; wherein the data center is configured to obtain partition information of an indoor space based on the grouping of the plurality of integrated sensors; and obtaining size information of the partition based on the position information of the plurality of integrated sensors.

A system as above wherein the location information comprises altitude.

A system as above wherein the location information comprises horizontal relative location information.

The system as described above, wherein the data center is configured to receive grouping information of the plurality of integrated sensors from the plurality of integrated sensors.

The system as described above, wherein the data center is configured to group the plurality of integrated sensors, and obtain partition information of the indoor space based on grouping information obtained after grouping.

The system as described above, wherein the data center is configured to receive location attribute information from the plurality of integrated sensors.

The system as described above, wherein the data center is configured to obtain characteristic information of the partition of the indoor space based at least in part on location attribute information of the plurality of integrated sensors.

According to the modeling method of the indoor space, the indoor space model can be built through the detection result of one or more of the plurality of sensors of the sensor network. And the indoor environment is further perceived through the built indoor space model. After sensing the indoor environment, the indoor electric appliances can be controlled to adjust the indoor environment.

Drawings

Preferred embodiments of the present invention will be described in further detail below with reference to the attached drawing figures, wherein:

FIG. 1 is a schematic diagram of an integrated sensor according to one embodiment of the invention;

FIG. 2 is a schematic diagram of an integrated sensor according to another embodiment of the invention;

FIG. 3 is a schematic view of an integrated sensor housing according to yet another embodiment of the invention;

FIG. 4 is a schematic diagram of an integrated sensor circuit configuration according to one embodiment of the invention;

FIG. 5 is a schematic diagram of an integrated sensor power architecture according to one embodiment of the invention;

FIG. 6 is a schematic diagram of an indoor human-occupied environment awareness system according to one embodiment of the invention;

FIG. 7 is a flow chart of an integrated sensor detection method according to one embodiment of the invention;

FIG. 8 is a schematic diagram of a sensor network architecture according to one embodiment of the invention;

FIG. 9A is a schematic diagram of an in-room architecture of a sensor network according to one embodiment of the present application;

FIG. 9B is a schematic diagram of integrated sensor positioning according to one embodiment of the invention;

FIG. 10 is a flow chart of a method of modeling indoor space according to one embodiment of the invention;

FIG. 11 is a method of sensing an indoor space environment according to one embodiment of the present invention;

FIG. 12 is a schematic illustration of an indoor model according to one embodiment of the present application;

FIGS. 13A and 13B are schematic diagrams illustrating changes in indoor environment according to one embodiment of the present application;

FIG. 14 is a flow chart of a method of adjusting an indoor environment according to one embodiment of the invention;

FIG. 15 is a schematic view of the structure of an indoor space modeling element according to one embodiment of the present application;

FIG. 16 is a schematic diagram of an indoor space modeling flow based on modeling elements in accordance with an embodiment of the invention;

17A-17D are schematic structural views of indoor facilities according to one embodiment of the present application; and

fig. 18 is a schematic diagram of an indoor space modeling flow based on an indoor facility according to an embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

In the following detailed description, reference is made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration specific embodiments in which the application may be practiced. In the drawings, like reference numerals describe substantially similar components throughout the different views. Various specific embodiments of the present application are described in sufficient detail below to enable those skilled in the art to practice the teachings of the present application. It is to be understood that other embodiments may be utilized or structural, logical, or electrical changes may be made to the embodiments of the present application.

The invention provides an integrated sensor for an indoor human living environment, and a sensor network based on the integrated sensor. In some embodiments, the sensor network may also be a plurality of different sensors, not limited to only integrated sensors. The present application will be described below by taking an integrated sensor as an example, and as those skilled in the art will understand, the location of the integrated sensor may also include a plurality of different kinds of sensors.

In some embodiments of the present invention, the integrated sensor groups a plurality of environmental sensors, including but not limited to: one or more of a photosensor (vision), a sound sensor (hearing), a gas sensor (smell), a chemical sensor (taste), a pressure sensor (touch), a fluid sensor (touch), a heat sensor (temperature), a humidity sensor (humidity), a magnetic sensor (magnetic field), and the like. The environmental sensor user detects one or more parameters of the indoor environment.

In some embodiments of the present invention, the integrated sensor integrates a plurality of body sensors, including but not limited to: one or more of a sound sensor, an infrared sensor, an ultrasonic sensor, a laser sensor, a gravity sensor, a motion sensor, a gesture sensor, a temperature sensor, a current sensor, a voltage sensor, a magnetic field sensor, a displacement sensor, a speed sensor, an acceleration sensor, and the like. The body sensors are used to detect one or more parameters of a person moving indoors.

In some embodiments, the environmental sensor and the body sensor may be the same sensor, such as a sound sensor. The sound sensor has a function of detecting sound. The sound in the environment can be detected, and the sound emitted by a person can be detected. In some embodiments, the same sensor may have both the function of detecting environmental parameters and parameters of a person, such as a temperature sensor. The temperature sensor can detect the temperature of indoor air and also detect the temperature of human body in a long distance. However, detecting the air temperature and detecting the human body temperature remotely are two completely different functions.

In some embodiments, the plurality of results of the integrated sensor detection collectively characterize an environmental or human parameter. For example, the results of temperature detection and smoke detection in the integrated sensor together account for an indoor fire. In some embodiments, the detection results of the plurality of integrated sensors collectively characterize an environmental or human parameter. For example, a plurality of cameras set up in suitable position just can realize accurate location. For another example, the combination of the gravitational detection result of the integrated sensor at one location and the infrared detection result of the integrated sensor at another location indicates that a person is active at a location in the room.

In some embodiments, the environmental or human parameters include commands issued by objects or people in the environment. For example, the microwave detection results of an integrated sensor at a certain location may be used to locate a person at a certain location, in combination with instructions obtained by a gesture motion sensor at another location, in combination with an active command indicating the person.

Therefore, one or more integrated sensors can detect and provide a plurality of environmental or human body parameters of the indoor living environment, can replace the existing various types of sensors, provide data services of basic environments and human bodies for a data center of the smart home, such as a computer or a server, are simple, convenient and easy to install and maintain, and enable the smart home to be realized more conveniently.

Fig. 1 is a schematic diagram of the structure of an integrated sensor according to one embodiment of the present invention. As shown, the integrated sensor 100 includes a housing 102, a probe 104, and a circuit board 106. In some embodiments, the probe 104 and the circuit board 106 are mounted on the housing 102. In some embodiments, one or more support structures are included in the housing 102. The probe 104 and the electrical circuitry 106 are mounted to the housing 102 by one or more support structures. Alternatively, the housing 102, probe 104, and circuit board 106 are all mounted to one or more support structures, thereby enabling assembly of the housing 102, probe 104, and circuit board 106.

As described in the background of the invention, an important application of the integrated sensor of the present embodiment is for detecting indoor living environment. In some embodiments, at least a portion of the probe 104 is in direct contact with the indoor environment. For example, the probe 104 is part of the outer surface of the integrated sensor so as to be in direct contact with the indoor environment. In some embodiments, the probe 104 includes one or more channels that communicate with the indoor environment, thereby indirectly contacting the indoor environment. Of course, the probe 104 may be in direct and indirect contact with the indoor environment simultaneously.

In some embodiments, the probe 104 includes a plurality of sensors 11-14. The plurality of sensors 11-14 are a plurality of environment detectors and/or body detectors for detecting a plurality of environment parameters and/or body parameters. The plurality of sensors 11-14 are electrically connected to the circuit 106.

As shown, the plurality of sensors 11-14 are electrically connected to the circuit 106 board by a plurality of wires. In some embodiments, these lines are fixed lines provided on the housing 102 or support structure, such as: conductive coatings, conductive pastes, or conductive layers, etc., rather than electrical leads.

In some embodiments, the circuit board 106 includes a monolithic printed circuit board and electronic components on multiple boards, such as a processor and a communication module. The circuit board 106 receives the detection results from the sensors 11-14 through electronic components on a plurality of boards, processes the detection results from the sensors 11-14, and then forwards the detection results to the home data center.

Unlike the temperature or humidity sensor of the prior art, the integrated sensor of the present embodiment is adapted to be installed in a room facility such as a wall, floor or ceiling of a room, thereby integrating with the indoor environment. This approach has many benefits: on one hand, the design of the integrated sensor can be simplified, and the integrated sensor does not need to worry about influencing the overall beauty of a room; on the other hand, the integrated sensor can be installed more conveniently, and parts such as indoor room walls, floors or ceilings are not damaged. More importantly, the integrated sensor can be installed in room facilities such as indoor walls, floors or ceilings to provide larger space for integrating a plurality of sensors, so that the space is not limited, and the implementation of the integrated sensor is facilitated.

In some embodiments, a bracket for mounting the integrated sensor is included in a wall, floor, or roof. The bracket itself is part of a wall, floor or ceiling, and the integrated sensor is mounted on the bracket so as to be placed in the wall, floor or ceiling. In some embodiments, the wall, floor, or ceiling is a movable wall, floor, or ceiling that is not hard-wired to the original wall, floor, and roof of the room. The application number is 201910295819.8, the application date is 2019, 4 and 12, the invention name is an assembled building and an internal tension wall, and an internal tension wall is disclosed, which is an example of a movable wall which is not hard-connected with the original wall surface, floor and roof. The entirety of this application is incorporated by reference herein. The application number is 201910858472.3, the application date is 2019, 9, 11, the invention name is a ceiling and assembled building, and a ceiling is disclosed, which is an example of a ceiling which is not hard-connected with the original wall, floor and roof. The entirety of this application is also incorporated by reference herein. Sufficient space is included in both the movable wall and ceiling of the above two examples to accommodate the integrated sensor of the present application. Thus, as a preferred embodiment, the integrated sensor of the present application is used with a movable wall, floor or ceiling that is not hard-wired to the original wall, floor and roof of the room. In the prior art, various ways can be used to mount the integrated sensor, and the method is not limited to the bracket, and is not described herein.

In embodiments where the integrated sensor is placed on a wall, floor, or ceiling, the manner in which the integrated sensor is in contact with the indoor environment can be accomplished in a variety of ways. In the embodiment shown in fig. 1, the probe 104 becomes the surface or portion thereof of the integrated sensor 100 that is in direct contact with the environment. The sensors 11-14 detect indoor environmental parameters or body parameters through the surface of the probe 104 in direct contact with the environment. In the following 2 specific embodiments, further designs of integrated sensor probe and housing are shown. Of course, the implementation of the integrated sensor of the present invention is not limited thereto.

Fig. 2 is a schematic structural view of an integrated sensor according to another embodiment of the present invention. The integrated sensor 200 shown in fig. 2 includes: a housing, a probe 204, and a circuit board (not shown); wherein the housing and circuit board parts are similar to the corresponding parts of the embodiment described in fig. 1. Likewise, the integrated sensor of the embodiment shown in FIG. 2 may also include a support structure. Further, the wiring between the sensor and the circuit board may also be implemented in a similar manner to the embodiment described in fig. 1. And will not be described in detail herein.

As shown in fig. 2, the probe 204 of the integrated sensor 200 includes a channel 205 that communicates with the interior space 207 of the integrated sensor 200. One or more sensors 21-24 are disposed in the channel 205 and the interior space 207. The sensors 21-24 are indirectly in contact with the indoor environment through the channel 205. Such sensors include, but are not limited to, acoustic sensors, temperature sensors, humidity sensors, magnetic sensors, gas sensors, electromagnetic signal sensors, and the like. The channel 205 and the interior space 207 provide sufficient space to accommodate multiple sensors, thereby enabling the integrated sensors of the present application to have smaller volumes and higher integration.

In some embodiments, the probe 204 of the integrated sensor 200 includes a probe surface 209 that is in direct contact with the indoor environment. A channel 205 is provided through the probe surface 209. One or more transducers 25-28 are included on the probe surface 209. The sensors 25-28 are in direct contact with the indoor environment. These sensors include, but are not limited to: light sensors, pyroelectric sensors, infrared sensors, pressure sensors, etc. The probe surface 209 provides a surface that is in direct contact with the indoor environment, facilitating accurate detection results.

FIG. 3 is a schematic view of an integrated sensor housing according to yet another embodiment of the invention. The integrated sensor shown in fig. 3 includes: a housing, probe 304, and circuitry (not shown); wherein the housing and circuit parts are similar to the corresponding parts of the embodiment described in fig. 1. Likewise, the integrated sensor of the embodiment shown in fig. 3 may also include a support structure. Further, the wiring between the sensor and the circuit may also be implemented in a similar manner to the embodiment described in fig. 1. And will not be described in detail herein.

As shown in fig. 3, the probe 304 of the integrated sensor 300 includes a plurality of channels 305, wherein each channel 305 communicates with one of the interior spaces 307 of the integrated sensor 300. One or more sensors 31-35 are disposed in the passageway 305 and the interior space 307, which are in indirect contact with the indoor environment through the passageway 305. Such sensors include, but are not limited to, acoustic sensors, temperature sensors, humidity sensors, magnetic sensors, gas sensors, electromagnetic signal sensors, and the like. The channel 305 and the interior space 307 provide sufficient space to accommodate multiple sensors, thereby enabling the integrated sensors of the present application to have smaller volumes and higher integration.

In some embodiments, the probe 304 of the integrated sensor 300 includes a probe surface 309 that is in direct contact with the indoor environment. A plurality of channels 305 are provided through the probe surface 309. One or more transducers 36-39 are included on probe surface 309. The sensors 36-39 are in direct contact with the indoor environment. These sensors include, but are not limited to: light sensors, pyroelectric sensors, infrared sensors, pressure sensors, etc. The probe surface 309 provides a surface that is in direct contact with the indoor environment, facilitating accurate detection results.

In some embodiments, a spacer may be present between the integrated sensor and the indoor environment. Such spacers include hollowed-out or vented decorative panels, such as wood grain panels, cardboard, stone panels, glazed tiles, etc., or panels coated with wall paint, wallpaper, wall cloth, wall mud, wall stickers, etc.; hollowed-out or ventilated ornaments, such as decorative pictures, photographs, artwork, textiles, collectibles, flower art works and the like; or furniture or household appliances, etc. The presence of these spacers does not affect the direct or indirect contact between the integrated sensor and the indoor environment.

Fig. 4 is a schematic diagram of an integrated sensor circuit structure according to one embodiment of the invention. As shown, the integrated sensor 400 includes a probe 401 and a circuit board. The probe 401 includes one or more analog quantity sensors, one or more digital quantity sensors, and one or more switching quantity sensors. The circuit board includes a processor 402. In some embodiments, the processor 402 includes a plurality of ports each corresponding to a different sensor. For example, the processor 402 includes an 8-channel I/O port, with 2 channels being analog; 2 channels are digital quantities; the 2 channels are switching values. Each channel of the processor 402 corresponds to a different type of sensor of the detection result.

In some embodiments, to increase the number of integrated sensors that can accommodate the sensors, reducing the processor channel limit on the number of sensors, a fieldbus or non-fieldbus is employed to enable communication between the processor and the plurality of sensors.

Referring to fig. 4,

first analog sensors

41 and 42 of a probe 401 are electrically connected to a processor 402 through analog lines. The detection results of the

analog quantity sensors

41 and 42 are connected to a digital quantity line through an analog-digital signal converter ADC, and are electrically connected to the processor 402. The first

digital quantity sensors

43 and 44 of the probe 401 are electrically connected to the processor 402 by digital quantity lines. The first

switching value sensors

43 and 44 of the probe 401 are electrically connected to the processor 402 through switching value lines. In some embodiments, the digital and switching circuitry may be combined into the same circuitry. Such lines include, but are not limited to: remote digital IO lines, such as: PROFIBUS, MODBUS, etc.; or a fieldbus line, for example: RS485, CAN, CC-LINK, D-Net, ASI, DP bus, etc.; or a data bus line, for example: PCI, PCIe, USB bus, etc. Because of the low real-time requirements for detection of integrated sensors, some high latency off-site buses (e.g., data buses) may also be used in the present invention.

In some embodiments, one or more signal conditioning circuits may be included between the sensor and the line for converting the detection signal from the sensor into a standard analog, digital, differential, or switching signal for subsequent signal processing.

In some embodiments, one or more controllers may be included in the analog, digital, or switching circuitry for signal processing and control of portions of the sensors to reduce the effort of the processor 402, reduce costs, and increase the efficiency of the system.

In some embodiments, some sensors may also be provided on the circuit board. For these sensors, all of the electronics associated therewith may be integrated on the circuit board of the integrated sensor. In other embodiments, for sensors disposed outside the circuit board, other electronics, including signal conditioning circuitry, controllers, and wiring therebetween, are disposed on the circuit board in addition to the necessary wiring between the sensors and the circuit board, thereby improving the integration of multiple sensors.

In this embodiment, the processor 402 may support different sensors through a plurality of interfaces of different types, or may communicate with sensors of different types of measurement results through analog, digital and switching value lines supporting the plurality of sensors, so as to implement integration of a plurality of sensors of different types; and the number of sensors is not limited by the number of ports of the processor 402.

In some embodiments, to facilitate adding or replacing sensors, the integrated sensor 400 digital quantity or switching quantity circuitry may include a plug and play interface, respectively, to facilitate adding or changing the functionality of the integrated sensor 400 as desired. For example, one or more plug and play interfaces are included in the digital or analog lines of integrated sensor 400, including but not limited to PCIe, PCI, and USB interfaces. For sensors that output digital quantities or switching quantities, this can be achieved by connecting to these plug-and-play interfaces. For a sensor with an output result of analog quantity, the sensor can be converted into a digital signal through an ADC, and then plug and play is realized through a plug and play interface in a digital quantity or analog quantity line.

In some embodiments, the integrated sensor 400 further includes a display module 404 in communication with the processor 402. The display module 404 is used to display the status of the integrated sensor. For example, the display module 404 may be a liquid crystal display, display operating status or detection result. For another example, the display module 404 is a plurality of indicator lights that reflect the operating state of the integrated sensor 400 by a state of color, lighting, blinking, etc.

In some embodiments, integrated sensor 400 also includes memory 406 in communication with processor 402. The memory is used to store data of the integrated sensor 400, including but not limited to: the detection result of the integrated sensor, the data (such as position, working state, etc.) of the integrated sensor itself, and the data during the working process of the integrated sensor.

In some embodiments, integrated sensor 400 further includes a communication module 408. The communication module 408 is used to communicate with the outside (e.g., other integrated sensors or a home data center). In some embodiments, the communication module 408 may be a wireless module. Communication protocols employed by the wireless module include, but are not limited to: 5G, 2.5G, wi-Fi, zigbee, lora, NB-IOT, Z-Ware, bluetooth, etc.

In some embodiments, the communication module 408 may be a wired module. The wired module is used for external (e.g., other integrated sensors or home data center) communication. Communication protocols employed by the wired module include, but are not limited to: remote digital IO lines, such as: PROFIBUS, MODBUS, etc.; or a fieldbus line, for example: RS485, CAN, CC-LINK, D-Net, ASI, DP bus, etc.; or a data bus line, for example: PCI, PCIe, USB bus, etc. In particular, for some embodiments in which the integrated sensor is disposed on a movable wall or ceiling, wiring for wired communication may be preset in the movable wall or ceiling to support the integrated sensor to communicate by wired means.

In some embodiments, the respective integrated sensors may communicate with each other using respective communication modules 408 to form a communication network, such as a mobile ad hoc (ad hoc) network, or the like.

Fig. 5 is a schematic diagram of an integrated sensor power architecture according to one embodiment of the invention. As shown, the integrated sensor further includes a battery 501 and a power management module 502. Under the control of the power management module 502, the battery 501 supplies power to various sensors, such as sensor 1 and sensor 2. Similarly, the power management module 502 also controls the battery 501 to power the processor 402 as well as to power the wireless module and memory.

Since the integrated sensor is provided in a wall, floor or ceiling, wired power wiring is an option. In some embodiments, the integrated sensor further comprises a wireless charging module 504 connected to the battery 501. Wireless charging of the battery 501 can be achieved by the wireless charging module 504. In some embodiments, the integrated sensor further comprises a solar charging module 506 connected to the battery 501. The battery 501 can be charged by converting light energy into electrical energy through the solar charging module 506. In the embodiment of the movable wall, floor or ceiling, power supply lines have been included in the movable wall, floor or ceiling, and thus the integrated sensor can also be directly powered by the power supply lines therein. In this embodiment, the battery 501, wireless charging module 504, and solar charging module 506 are all optional.

As shown by some embodiments of the invention, an integrated sensor has the following advantages:

1. the volume is small, the weight is light, and the power consumption is small. The integrated sensor of the invention realizes the integration of a plurality of sensors, is an independent electronic system with perfect functions, and can be realized on a small monolithic integrated circuit board. The volume and the weight can be reduced, and the power consumption can be reduced while the detection functions are realized.

2. The cost is low. On one hand, the integrated sensor is convenient for mass production, so that the cost can be greatly reduced. On the other hand, a plurality of sensors can be arranged and managed in a centralized way, and the installation and management cost of the sensors is also greatly reduced.

3. The reliability is high. The integrated sensor integrates a plurality of electronic devices on the same circuit board, so that the connection points and the welding points are greatly reduced, and the high reliability of the devices is ensured by factory inspection. Therefore, compared with a plurality of discrete sensors, the circuit reliability is greatly improved, and the maintenance cost is reduced.

4. And the expandability is good. The integrated sensor provided by the invention realizes integration and mutual communication of a plurality of sensors and communication with an external data center, is convenient to realize different functions on the basis, and has excellent expandability.

Fig. 6 is a schematic structural view of an indoor human living environment sensing system according to an embodiment of the present invention. As shown, the indoor human living environment sensing system of the present embodiment includes a plurality of integrated sensors, such as integrated sensors a-H, which are respectively disposed in indoor environments. In some embodiments, the plurality of integrated sensors are disposed in a wall, floor, and ceiling, respectively. In particular, walls, floors and ceilings are movable walls, floors and ceilings. Further, the indoor human living environment sensing system of the embodiment includes a home data center. The plurality of integrated sensors communicate wirelessly with the home data center. The home data center can be a server, a special machine, a computer, a notebook computer and other devices, and can also be a mobile device such as a mobile phone and a Pad.

The home data center serves as a center for storing, processing and mining detection results (data) of each integrated sensor, and is also a command center for controlling indoor human living environment by using the data. On the other hand, a home data center is also a gateway of a home network. The home data center includes a gateway. The detection results (data) of all integrated sensors cannot be transmitted outside without going through the home data center. Thus, home data centers are also centers for data protection.

In some embodiments, a home data center includes one or more processors, a first communication module, and a second communication module. The first wireless module is used for communicating with a plurality of integrated sensors, and receiving one or more detection results from the plurality of integrated sensors; or to send control commands to a plurality of integrated sensors. The first communication module may be a data transceiver of a communication protocol such as 5G, 2.5G, wi-Fi, zigbee, lora, NB-IOT, Z-Ware, bluetooth, etc. The second communication module is used for communicating with external networks in a wired or wireless manner, including but not limited to the mobile Internet, the Internet, and other networks capable of two-way communication.

In some embodiments, the home data center can communicate with sensors worn by the human body in a wired or wireless manner to obtain detection results from non-integrated sensors. In some embodiments, the home data center communicates with home appliances in the home in a wired or wireless manner, thereby obtaining detection results from non-integrated sensors.

In some embodiments, the home data center can perform processing of detection results from the integrated sensor or the non-integrated sensor, and based thereon, adjust one or more parameters of the indoor environment using big data and artificial intelligence techniques, to achieve active indoor environment adjustment.

FIG. 7 is a flow chart of an integrated sensor detection method according to one embodiment of the invention. As shown, the integrated sensor detection method includes: at step 710, a detection result from a first sensor of the first integrated sensors is received at the home data center. The first integrated sensor transmits the detection result of the first sensor to the home data center through the wireless module.

In step 730, the detection results from the second sensor in the first integrated sensor and/or the detection results from the third sensor in the second integrated sensor are received at the home data center. The first integrated sensor sends the detection result of the second sensor to the home data center through the wireless module of the first integrated sensor; or the second integrated sensor sends the detection result of the third sensor to the home data center through the wireless module of the second integrated sensor; alternatively, the detection result of the second sensor of the first integrated sensor and the detection result of the third sensor of the second integrated sensor are both transmitted to the home data center.

In step 750, the detection results of the first sensor, the second sensor, and/or the third sensor are comprehensively analyzed in the home data center to obtain one or more indoor environment parameters or human body parameters. As will be appreciated by those skilled in the art, the present invention is not limited to the type, number and detection time of the integrated sensors and the sensors therein, and the detection results are comprehensively analyzed, so that the home data center can obtain the desired indoor environment parameters or human body parameters more accurately.

In some embodiments, at step 740, further comprising receiving, at the home data center, a detection result from a fourth sensor worn by the person. In an embodiment, the home data center comprehensively analyzes the detection results of the first sensor, the second sensor, the third sensor and/or the fourth sensor, and then obtains one or more indoor environment parameters or human body parameters. By using the detection result of the fourth sensor worn by the human body, one or more parameters of the human body can be more accurately known, so that the desired indoor environment parameters or human body parameters can be more accurately obtained.

In some embodiments, at step 770, the home data center further comprises controlling one or more appliances in the indoor environment according to the one or more indoor environment parameters or the human body parameters from step 750, adjusting the one or more indoor environment parameters. The indoor environment is adjusted to the user's appropriate or desired conditions by adjusting one or more indoor environment parameters. The method of the embodiment realizes the active indoor human living environment change by utilizing the detection result of the integrated sensor, thereby becoming the direct application of the active artificial intelligence aspect.

Although the application takes an indoor living environment as an example, the technical scheme of the integrated sensor is described; however, it will be appreciated by those skilled in the art that the application of the integrated sensor of the present invention is not limited to indoor but may be applied to other independent spaces including, but not limited to, static outdoor spaces, mobile spaces (e.g., in-car), etc.

Sensor network

According to one embodiment of the invention, the plurality of integrated sensors forms an integrated sensor network. The integrated sensor network and the home data center form a part of an indoor human living environment sensing system. In an integrated sensor network, the individual integrated sensors can communicate with each other or with a separate center of the integrated sensor network. In some embodiments, the home data center may act as a central node of the sensor network. In the integrated sensor network, each integrated sensor is also capable of communicating with a home data center. In some embodiments, multiple integrated sensors may work cooperatively under coordination of a sub-center of the integrated sensor network or a home data center to achieve better indoor human living environment control.

In another aspect, the invention also provides a sensor network. An integrated sensor network as described above may be one example of a sensor network. The sensor network includes a plurality of sensors and a data center. The plurality of sensors are placed at a plurality of locations in the room, which may be integrated sensors as described above, or may be other types of sensors. In the following description, which exemplifies an integrated sensor, a person skilled in the art will understand that other types of sensors are possible. The data center communicates with a plurality of sensors in a wired or wireless manner that detects an indoor environment based at least in part on a plurality of location information of the plurality of sensors. The data center may be a home data center or a split center.

Fig. 8 is a schematic diagram of a sensor network structure according to an embodiment of the present invention. As shown in fig. 8, the indoor human living environment includes a plurality of rooms, for example: room a, room B, and room C; wherein room a and room C are in communication with room B, respectively. A plurality of integrated sensors A01-A05 are arranged in the room A; a plurality of integrated sensors B01-B04 are arranged in the room B; and, a plurality of integrated sensors C01-C05 are disposed within the room C. In one embodiment, the individual integrated sensors may communicate with each other even if arranged in different rooms. For example, integrated sensor A01 may communicate directly with integrated sensor C05. In some embodiments, the sensor network shown in fig. 8 may include a data center (not shown) capable of communicating with each integrated sensor in each room. In some embodiments, sub-centers may be included in each room, such as sub-center a, sub-center B, and sub-center C (not shown). The physical structure of the sub-center is similar to that of the data center and may be a device with computing power. A split center is not necessary. When the room is larger or the number of integrated sensors in the room is larger, the arrangement of the sub-centers can reduce the workload of the data center, and is also beneficial to reacting to environmental changes more quickly. In some embodiments, the individual integrated sensors are cooperatively operated by a separate center or data center without direct communication.

In some embodiments, the integrated sensors in the room may be located in a movable or non-movable wall, floor, or ceiling, etc. indoor facility. Taking room a as an example, the integrated sensor may be disposed at a plurality of locations on the walls around room a, forming a sensor network for room a, and in some embodiments, the integrated sensor may also be disposed on the ceiling and/or floor (not shown) of room a. In some embodiments, smart wearable devices (e.g., smart bracelets, smart watches, smartphones, etc.) within the room may also communicate with the data center.

In some embodiments, after composing a network of sensors for one or more rooms, the data center may detect the environment within the room through a plurality of integrated sensors. Unlike the prior art, a plurality of differently located integrated sensors promote environmental detection results in at least two ways. On the one hand, the indoor environment distribution can be obtained by detecting from a plurality of positions, so that the detection accuracy is improved. For example, in the prior art, there may be only one temperature and humidity sensor in one room, the temperature and humidity distribution in the room may be uneven, and the temperature and humidity sensor may only detect the temperature and humidity around the temperature and humidity sensor. Because a plurality of integrated sensors are arranged at different positions in the room, the integrated sensors can detect the temperature and the humidity of the respective positions. The data center can obtain the temperature and humidity distribution according to the temperature and humidity of each position, and the temperature and humidity conditions in the room can be reflected more accurately. In another aspect, the integrated sensor at multiple locations is capable of detecting multiple types of environmental parameters. The different types of environmental parameters obtained at different locations enable the data center to detect environmental parameters that are not detectable by existing sensors.

In some embodiments, the integrated sensor may detect one or more environmental parameters of the indoor environment, and the data center may determine one environmental parameter together according to a plurality of detection results of one or more of the plurality of integrated sensors of the sensor network and the location information thereof. For example, the data center may determine a temperature distribution within the room based on temperatures within the room detected from the plurality of integrated sensors and the locations of the plurality of integrated sensors.

In some embodiments, the integrated sensor may also detect one or more human parameters of the indoor active person, and the data center may determine one human parameter together according to a plurality of detection results of one or more of the plurality of integrated sensors of the sensor network and the position information thereof. For example, the data center may determine a moving route of a person moving in a room based on infrared information from a human body detected by a plurality of integrated sensors and positions of the plurality of integrated sensors.

In some embodiments, the data center may collectively determine a command issued by a person moving in the room based on a plurality of detection results of one or more of a plurality of integrated sensors of the sensor network. For example, the data center may determine that a person is sounding a command to adjust his or her surrounding temperature based on infrared information from the person detected by one integrated sensor and voice information from an active person detected by another integrated sensor. Infrared information through the integrated sensor is useful for determining the person issuing the command and its location. In some embodiments, the data center may adjust the indoor environment based on a plurality of detection results of one or more of a plurality of integrated sensors of the sensor network and/or commands of indoor active persons.

In some embodiments, the integrated sensor may send identity information and location information to the data center when it first communicates with the data center. In some embodiments, the integrated sensor needs to be registered with the data center to be able to join the data center's sensor network. At registration, the integrated sensor sends its identity information, e.g., ID; and its location information. In some embodiments, the identity information of the integrated sensor includes the room in which it is located. For example: the integrated sensor is positioned in room A, room B or room C, wherein A in the sensor identity information A02 represents room A, and the number 02 represents the number 2 sensor. When the room information is included in the identity information of the integrated sensor, the location information thereof may be the location information in the room. In some embodiments, the identity information of the integrated sensor may also include integrated sensor location status information. For example: the integrated sensor is a movable or non-movable sensor. For a removable integrated sensor, the identity information includes the letter X. For example X01, number 1.

In some embodiments, when the integrated sensor sends the detection result, the identity information and the location information of the integrated sensor can be sent to the data center at the same time. In particular a movable sensor, which updates its position by sending position information. For an immovable sensor, if the room facility in which it is located is movable, after changing the location, it will also re-register or send updated location information at the same time when the detection result is sent next time.

In some embodiments, the location information of the integrated sensor includes altitude. That is, the position information of the integrated sensor is three-dimensional position information. In the existing indoor positioning, the height information is not included. The three-dimensional position information facilitates the creation of a more accurate environmental model. Further, in some embodiments, the location information includes horizontal relative location information. The height information and the horizontal relative position information together define the position of the integrated sensor. The horizontal relative position information is based on the relative position with a positioning point, wherein the positioning point is the position of a positioning sensor or a preset point of a room where the sensor is located. Indoor positioning generally seems to be difficult, difficult to position accurately, which is important for the present invention. To solve this problem and reduce the positioning cost, in the present embodiment, the difficulty of positioning is reduced by using the horizontal relative position information in units of rooms. The locating point of the horizontal relative position is a preset point in the room or a locating integrated sensor on the preset point. Thus, the three-dimensional space positioning relative to the origin of coordinates becomes the relative positioning of the preset point in the room, thereby fully utilizing auxiliary facilities such as walls of the room and reducing the relative positioning difficulty. By the positional relationship between the predetermined point and the origin of coordinates, the positions of all the integrated sensors with respect to the origin of coordinates can be easily calculated.

Fig. 9A is a schematic diagram of an in-room architecture of a sensor network according to one embodiment of the present application. As shown, room 900 includes

walls

910, 920, and 930 (only 3 shown), ceiling 940, and floor 950; wherein

walls

910 and 930 are each connected to wall 920. Each wall is connected with the ceiling 940 and the floor 950 to form an indoor space. In some embodiments, the room 900 may further include a partition 960, which may be connected to the wall 910 and disposed between the ceiling 940 and the floor 950, may be used to partition an indoor space, and may partition the indoor space into a plurality of spaces. In some embodiments, partition 960 is a movable partition.

In some embodiments, the junction of wall 920 and wall 930 includes a corner 970 that is relatively convex compared to wall 920 and wall 930, and in some embodiments, the corner may have other shapes, such as: fan-shaped, etc. In some embodiments, the wall as a whole is not flat. For example: the wall has a certain radian, concave-convex, etc.

In some embodiments, the room includes a plurality of integrated sensors therein. The wall 910 may include integrated sensors 911-913 thereon, wherein the integrated sensor 911 is located at the interface of the wall 910 and the ceiling 940, the integrated sensor 912 is located at the interface of the wall 910 and the floor 950, and the integrated sensor 913 is located at the interface of the wall 910, the floor 950, and the partition 960. The wall 920 may include an integrated sensor 921 that is located in the center of the wall 920. The wall 930 includes integrated sensors 931-933, the integrated sensor 931 being disposed at the junction of the wall 930 and the ceiling 940, the integrated sensor 932 being located at the junction of the wall 930 and the floor 950, the integrated sensor 933 being located at the center of the wall 930. The ceiling 940 includes an integrated sensor 941 that is located at the center of the ceiling 940. The floor 950 includes an integrated sensor 951 that is located at the center of the floor 950. The partition 960 includes integrated sensors 961-963, wherein the integrated sensor 961 is located at the interface of the partition 960 and the ceiling 940, the integrated sensor 962 is located between the partition 960 and the floor 950, and the integrated sensor 963 is disposed at the center of the partition 960. The corner 970 includes

integrated sensors

971 and 972, wherein the integrated sensor 971 is located at the junction of the corner 970 and the ceiling 940 and the integrated sensor 972 is located at the junction of the corner 970 and the floor 950.

In other embodiments, a different number of integrated sensors in different locations may be included on wall 910, wall 920, wall 930, ceiling 940, floor 950, or partition 960. For example: the integrated sensor 911 may be located on the ceiling, or divide a wall, ceiling, floor, partition, or the like into a plurality of rectangles, each rectangle having one integrated sensor disposed at its center, or each rectangle having one integrated sensor disposed at its corners and center, or the like.

In some embodiments, the sensor network includes integrated sensors 911-913, integrated sensors 921, integrated sensors 931-933, integrated sensor 941, integrated sensor 951, integrated sensors 961-963,

integrated sensors

971 and 972 within the room 900. These integrated sensors can all communicate with a data center. In some embodiments, a smart device 980 may be held or worn by a user. The smart device 980 is also capable of communicating with a data center.

FIG. 9B is a schematic diagram of integrated sensor positioning according to one embodiment of the invention. As shown, the predetermined point is the center point a of the floor of the room, taking the positioning of the integrated sensor 933 as an example. The integrated sensor 933 does not have a positioning function, but supports inputting the height and the horizontal relative position to the predetermined point a in an input manner. One typical operation is that the height and horizontal relative position is performed by a worker provided with an integrated sensor 933 using a hand-held laser rangefinder. The worker first measures the distance Z between the integrated sensor 933 and the ground using a laser rangefinder. At predetermined point a, the distance X from predetermined point a to wall 930 is measured using a laser rangefinder and the projected point B of predetermined point a on wall 930 is determined. Then, a light blocking device is placed at the projection point B. Then, the distance Y between the point and the projected point B of the predetermined point a is measured on the projected point of the integrated sensor 933 on the ground using a laser range finder. The measured distance X, Y and Z are input to the integrated sensor 933, where X and Y are the horizontal relative distances of the integrated sensor 933 with respect to the predetermined point a. Wherein X and Y may be positive or negative numbers to indicate the direction relative to the predetermined point a. In other words, the predetermined point is similar to one origin of coordinates in the room. The data center stores the location of the predetermined point a. The data center can calculate the position of the integrated sensor 933 using the positions of X, Y and Z from the integrated sensor 933 and the predetermined point a. In some cases, the shape of the room is irregular. It is now possible to use 2 predetermined points arranged in the room. The distance between the projection point of the integrated sensor on the ground and two preset points is measured as the horizontal relative position. In this mode, the position of the integrated sensor can also be calculated accurately. The error is in the order of centimeters or less. Likewise, other integrated sensors within the room 900 may be positioned in a similar manner. The mode is convenient to operate and low in cost, and does not need more hardware support.

In some embodiments, the integrated sensor may include a positioning member. The positioning piece can realize accurate positioning by using UWB, infrared rays, ultrasonic waves and the like. The room includes a locating device (e.g., a UWB base station or an infrared or ultrasonic transmitting device) located at a location point. The positioning device can communicate with a positioning member in the integrated sensor, so that positioning of the integrated sensor can be achieved more easily. However, the cost is relatively high. The degree of accuracy of this positioning is dependent on the technique used. In some cases, positioning on the order of centimeters within the chamber can be achieved by the positioning member.

An important application of the sensor network of the invention is the accurate detection and adjustment of indoor environments. According to one embodiment of the invention, an indoor space model can be built according to a plurality of detection results of one or more of a plurality of integrated sensors of a sensor network. Based on the indoor space model, the indoor environment can be further perceived. After sensing the indoor environment, the data center can control indoor electrical appliances and adjust the indoor environment.

Indoor space modeling

Indoor space modeling is to build a model of indoor space. In the prior art, the layout of the indoor space is generally unchanged. For example, there are several rooms in a house and the size and orientation of each room are rarely adjusted. However, for future intelligent houses, the layout of the indoor space can be easily changed. The data center may store an externally input indoor space model when the room layout is not changed. However, when the room layout is frequently changed, it becomes very inconvenient to input the indoor space model from the outside every time. Therefore, if the layout of the room can be automatically obtained or updated when the layout of the room changes, the model of the indoor space can be obtained, and the system can be more suitable for future intelligent houses. This automatic method of obtaining and updating the layout of the room becomes a modeling of the indoor space. The sensor network based on the invention can conveniently realize the indoor space modeling. Indoor layout information obtained through indoor space modeling is not necessarily completely accurate, but can also meet the requirements of use.

Fig. 10 is a flowchart of an indoor space modeling method according to an embodiment of the present invention. As shown, the spatial modeling method includes the steps of: in step 1010, location information for a plurality of integrated sensors is received from the plurality of integrated sensors. In this embodiment, the spatial modeling is based on positional information of a plurality of integrated sensors. As previously described, the data center is able to obtain the locations of a plurality of integrated sensors in the sensor network arranged indoors. Indoor space layout is restored as accurately as possible by utilizing indoor space information reflected by the positions of the integrated sensors, so that indoor space modeling is realized. As described above, the location information of the integrated sensor may be transmitted when the integrated sensor is registered in the data center or when the detection result is transmitted. If the position of the integrated sensor changes, the integrated sensor needs to be registered with a data center serving as a sensor network main node again; or when the detection result is sent again, the self-position updating is completed at the same time.

In some embodiments, the data center may also utilize other information to assist in spatial modeling. Such information includes, but is not limited to, the original house layout; layout of non-removable portions of the house; anchor point information of additional arrangement, etc. For example, the data center may store the original house layout. Although the house layout is changed, the original room layout can still be helpful. New house layouts can be more easily obtained in combination with the position information of the plurality of integrated sensors, and an indoor space model can be built. In future houses, for example, houses are provided with only non-removable portions, and the layout of the division of rooms and the like is determined by the user himself. The data center may store a layout of the non-removable portion of the house. New house layouts can be more easily obtained in combination with the position information of the plurality of integrated sensors, thereby creating an indoor space model. Of course, additional anchor points may be provided in addition to the integrated sensor. The information of the positioning points is also beneficial to obtaining an indoor space model.

At step 1020, a partition of the indoor space is obtained based on the grouping of the plurality of integrated sensors. In some embodiments, the data center may group information from multiple integrated sensor receivers, enabling multiple integrated sensors to be grouped so that a partition of the indoor space may be obtained. For example: all integrated sensors in the same room may be grouped together. As in the embodiment shown in fig. 8, the data center groups all integrated sensors into A, B and C groups according to the IDs of the individual integrated sensors. If a mobile integrated sensor is included in the room, it may be individually grouped. For groupings of non-mobile integrated sensors, each group may correspond to a room. In some embodiments, further, the groupings of integrated sensors may include subgroups that may represent local facilities of a room (e.g., walls, ceilings, floors, etc.), and so forth. Some of the integrated sensors with the lowest heights belong to the ground subgroup; some of the highest integrated sensors belong to the ceiling subgroup; the different heights but horizontal relative positions are in a straight line representing a subset of walls. That is, information about facilities in the room can be obtained for further groupings of integrated sensors within the same grouping. This information is useful for modeling indoor space.

In some embodiments, if room information is not available from the identity information of the integrated sensors, the data center may automatically group the integrated sensors according to the location characteristics of the integrated sensors, i.e., automatically obtain room layout information of the house according to the location characteristics of the integrated sensors. For example, the data center may implement groupings of integrated sensors based on shape matching. Typically, the shape of the room is regular. For example, a room made up of a rectangular parallelepiped or a plurality of rectangular cubes is most common. There are also rooms in which the shape is irregular. Such as a room consisting of a rectangular parallelepiped and a cambered surface. The data center stores these common room shapes, matches the locations of the plurality of integrated sensors with the common room shapes, and selects the best matching scheme as the room layout.

In some embodiments, the data center grouping of integrated sensors may also be based on zone partitioning. In some embodiments, the region division may be based on a distance-optimal scheme to a predetermined point. Specifically, a plurality of predetermined points are given in the area of a plurality of integrated sensors. The predetermined point setting scheme with the smallest distance accumulation result from the integrated sensor around the predetermined points to the predetermined points is the optimal solution. For this optimal solution, each predetermined point corresponds to a room, thereby identifying the layout of the room.

In some embodiments, the region division may be based on an object recognition algorithm to find different regions to which it may belong from a seemingly scattered plurality of integrated sensor locations. Deep learning-based object recognition algorithms, including, but not limited to, R-CNN, YOLO, or SSD. Existing integrated sensor arrangements and room layouts may be used as data set training target recognition algorithm models. The area division of the plurality of integrated sensors can be achieved using a trained object recognition algorithm model, thereby recognizing the layout of the room.

In some embodiments, the region division may also be based on detection results of the plurality of integrated sensors. The results of the detection may be the same or similar for integrated sensors in the same area. For example, the integrated sensor includes a temperature detector therein; while the temperatures in the same room may be quite different. Thus, the temperature detection results of the integrated sensor can also be used to perform or assist in zone division, for example: the integrated sensors with the same or similar detection results can be divided into a group, so that the layout of the room is obtained.

Likewise, the original house layout or the layout of the non-removable portions of the house may also assist in determining groupings of integrated sensors to obtain a new room layout.

As will be appreciated by those skilled in the art, the above zone divisions may be used independently or in combination to yield a more accurate room layout. Of course, other area dividing methods in the prior art, either alone or in combination with the above area dividing methods, may be applied thereto.

Since the arrangement of the integrated sensors is generally sparse, a relatively coarse room layout situation can be obtained. To address the problem of sparse integrated sensors that cannot accurately reflect conditions in a room, in some embodiments, attribute information of the integrated sensors is added to enable a data center to obtain local features of where the integrated sensors are located. The integrated sensor includes location attribute information, which may be part of the identity ID or a separate field. The data center obtains location attribute information of the integrated sensor when registering to the data center or transmitting a detection result. The location attribute information reflects characteristics of the indoor space near the integrated sensor. The location attribute information includes a type field or a type field and a number field. The type field may indicate that the location is convex, concave, curved, vertical, etc. The number field may represent the distance of the male or female, the radius of the arc, the arc of the column, etc. More accurate local characteristics in the room can be obtained through the position attribute information. In some embodiments, the location attribute information may also include a functional area as described by where the integrated sensor is located. For example: if the integrated sensor is located in a particular place such as a bathroom, a kitchen, etc., the location attribute information of the integrated sensor indicates the type of the functional area. In some embodiments, the location attribute information may also include the indoor facility where or around which the integrated sensor is located. For example: the vicinity of the location where the integrated sensor is located includes partitions, windows, doors, etc., and the location attribute information indicates the type and rough location of the indoor facility. All the information is beneficial to the establishment of the indoor space model.

In step 1030, size information of each partition is obtained based on the position information of the plurality of integrated sensors. After the partition information of the indoor space, that is, the layout of the rooms in the room is obtained, the size information of each partition, for example, the size of each room, may be further obtained. After the dimensions of the room are obtained, a model of the indoor space is built. Thus, even if the indoor room layout is changed, a new room layout can be easily obtained by using a plurality of integrated sensors arranged indoors, thereby realizing automatic updating. In some embodiments, such automatic updating capability is very useful for future houses where the room layout may change over time according to the desires of the user. Further, by using the indoor space modeling, the indoor environment can be adjusted more accurately, so that a more comfortable living experience is realized.

In some embodiments, the partitions are first shape matched. If the partitions have been shape matched, the previously adapted shape may be utilized. If the partition has not been subjected to shape matching, the shape of the partition is determined by shape matching. After the shapes are matched, the size of the matched shape is determined. The size is the size of the partition. If there is location attribute information for the integrated sensor, the location attribute information for the integrated sensor can be used to adjust the shape and size of the match. In some embodiments, the size of a zone may be determined based on the location of integrated sensors located at the edges of the zone within the same zone. Likewise, the original house layout or layout of the house non-removable portions may also assist in sizing the partitions. After the size of the partition is determined, a model of the indoor space is built.

Indoor space environment perception

By indoor space perception is meant precisely detecting one or more parameters of the indoor space environment. The existing indoor environment detection often uses the detection result of a sensor at a certain point to represent the environmental parameter of the whole space. However, such detection results are inaccurate and cannot reflect complex environmental changes throughout the space, and are also disadvantageous for achieving more accurate environmental control. In some embodiments of the present invention, based on the sensor network, with the help of spatial modeling, more accurate indoor space environment sensing can be achieved.

Fig. 11 is a method of sensing an indoor space environment according to an embodiment of the present invention. As shown, the method of sensing an indoor space environment includes the steps of: at step 1110, a plurality of environmental parameters of a location of a plurality of integrated sensors are received from the plurality of integrated sensors. As previously described, the sensor network of the indoor space is capable of detecting environmental parameters from multiple locations of the indoor space to the data center transmitter. The data center gathers the detection results, so that the environment parameters of a plurality of positions in the indoor space can be known.

At step 1120, indoor space modeling information is obtained at least in part using the location information of the plurality of integrated sensors. In some embodiments, the method for modeling indoor space using an integrated sensor network as described above may be applied thereto to obtain indoor space information. In some embodiments, other ways of obtaining the indoor space model may also be utilized. The invention is not limited herein. The locations of the plurality of integrated sensors are utilized, at least in part, to modify or validate the indoor space model to obtain indoor space information. For example, if an existing indoor space model cannot be matched with an integrated sensor, which may affect subsequent environmental assignments, the indoor space model may be modified based on the location of the integrated sensor.

At step 1130, indoor environment distribution information is obtained based at least in part on the plurality of environmental parameters of the plurality of integrated sensors and the indoor space modeling information. The indoor space information reflects the indoor space condition, and the detection results of the integrated sensors reflect the environmental parameters of a plurality of discrete points in the indoor space. In the step, the environment parameters of the whole indoor space are established by utilizing the environment parameters of the discrete points, so that the perception of the environment is realized.

In some embodiments, obtaining the indoor environment information may include the steps of: in step 1131, the indoor space is divided into a plurality of subspaces based on the indoor space information. There are many ways of dividing the subspace. For example, a fixed length, width, and height; fixed volume, etc. In step 1132, the environmental parameters of at least a portion of the subspace are assigned values using the plurality of environmental parameters from the plurality of integrated sensors. If an integrated sensor is included in or adjacent to a subspace, the data center uses the integrated sensor measurements to assign a value to the subspace's environmental parameters. Thus, the environmental parameters of a portion of the subspace are assigned; while the environmental parameters of part of the subspace have not yet been assigned.

In step 1133, the data center assigns values to the remaining environmental parameters of the subspace that have not been assigned, thereby implementing the environmental awareness of the entire indoor space. There are a number of ways to assign values to these subspaces. In some embodiments, the environmental parameters of these subspaces are assigned by interpolation. For example, two subspaces that have been assigned are separated by one or more subspaces, and then the environmental parameters of these separated subspaces may be assigned by interpolation.

In some embodiments, the field distribution of the environmental parameters of the indoor space may be estimated based on the environmental parameters of the plurality of subspaces that have been assigned; then, based on the field distribution of the indoor space, the environmental parameters of some subspaces are assigned values. Taking the temperature field as an example, if there is a heat source in the indoor space, a flow field of heat may occur around the heat source. The shape of the heat flow field can be estimated approximately according to the temperature of the heat source, the air output and the size of the room, so that the flow field distribution of the temperature can be estimated. Based on the estimated temperature flow field distribution and the temperatures of the subspaces that have been assigned, the temperatures of some subspaces may be assigned such that the temperature flow field distribution of the entire room coincides with the estimated temperature flow field distribution. This enables assignment of environmental parameters to parts of the subspace. Based on the estimated temperature flow field, other subspaces can be assigned by an interpolation method or a further field analysis method, so that the temperature field of the whole indoor space is obtained. For another example, regarding the electromagnetic signal intensity, the distribution of the electromagnetic signal intensity field can be approximately predicted according to the position of the signal source and the attenuation law of the electromagnetic signal in space. And the assignment of the electromagnetic signal intensity to the indoor partial subspace can be realized by combining the detection results of the electromagnetic signal intensity by a plurality of indoor integrated sensors. Based on the estimated electromagnetic signal intensity field, other subspaces can be assigned by using an interpolation method, so that the electromagnetic intensity distribution of the whole indoor space is obtained.

In some embodiments, the data center may also assign values to the environmental parameters of at least a portion of the subspace based on the location attribute information of the plurality of integrated sensors. As previously described, the integrated sensor may include location attribute information that is indicative of a spatial characteristic of the integrated sensor or a location in its vicinity. For example, if the location of the integrated sensor is concave, its environmental parameters may be relatively stable, and all subspaces of the concave region may be assigned the same value. For another example, if the integrated sensor is located near the water source of the bathroom, then the humidity assignment in the subspace around it will increase accordingly.

It will be appreciated by those skilled in the art that the above approaches may be used independently or in combination to more accurately assign values to the environmental parameters of the respective subspaces. Of course, there are other ways to assign values to environmental parameters for subspaces that have not yet been assigned. These approaches may be used independently or in combination with the above approaches to more accurately perceive the environment of the indoor space.

In step 1140, the data center may predict changes in the environmental parameters of each subspace and update the environmental parameters of each subspace based on the predicted changes. These subspaces include both subspaces with or adjacent to integrated sensors, and subspaces that do not directly contact any integrated sensors.

In some embodiments, the data center predicts changes in environmental parameters of each subspace in the indoor space based on changes in the indoor space facility status. For example, a door or window in a room is open to allow air exchange with the outside world, and the data center may anticipate changes in temperature and humidity in the room. According to the outdoor temperature and humidity and the opening time of the doors and windows, the data center can estimate the change of the indoor space temperature and humidity. According to the estimated result, the data center can reassign the temperature and humidity of a plurality of subspaces in the indoor space.

In some embodiments, the data center predicts changes in environmental parameters of other sub-spaces in the indoor space based on changes in environmental parameters from the plurality of integrated sensors after changes in the status of the indoor space facility. Such updating, although somewhat delayed in speed, can ensure the accuracy of the perception of the environmental change.

In some embodiments, the data center predicts environmental parameter changes for each subspace in the indoor space in response to outdoor environmental change states. If the outdoor environment is changed considerably, for example the temperature is lowered considerably, it is expected that the indoor temperature will be changed accordingly even if the door or window is not opened. The data center can estimate the change of the indoor space temperature and humidity. According to the estimated result, the data center can reassign the temperature and humidity of a plurality of subspaces in the indoor space.

It will be appreciated by those skilled in the art that the above approaches may be used independently or in combination to more accurately update the environmental parameter assignments for the respective subspaces. Of course, there are other ways to update the environment parameter assignments for the respective subspaces. These approaches may be used independently or in combination with the above methods to more accurately sense environmental changes in the indoor space.

The sensor network of the present application, indoor space modeling, recognizing commands issued by users and sensing the environment of indoor space will be further described below by taking a specific room as an example.

Fig. 12 is a schematic view of an indoor model according to one embodiment of the present application. As shown, room 1200 includes

walls

1210, 1220 and 1230, ceiling 1240, floor 1250, and corners 1260, the layout of which is similar to the embodiment of fig. 9 and will not be described in detail.

In some embodiments, wall 1210 includes integrated sensors 1211-1215, wall 1220 includes integrated sensors 1221-1225, wall 1230 includes integrated sensors 1231-1235, ceiling 1240 includes integrated sensors 1241-1245, and floor 1250 includes integrated sensors 1251-1255. Wherein each integrated sensor is located at the center of each wall, ceiling or floor separation rectangle, forms a sensor network of the room 1200, and each integrated sensor can detect one or more environmental parameters and/or one or more human parameters in the room, and can upload the detection results to the data center.

The identity IDs of all integrated sensors 1211-1255 have the same identity a, representing room a. Thus, the room 1200 may be the result of a data center modeling the room space of a house. Of course, the house may also include room B and room C as shown in fig. 8. The data center obtains the position information of each integrated sensor and obtains the size information of the room.

In some embodiments, the data center may regroup the integrated sensors within room a. For example: integrated sensors 1211-1215 on wall 1210 are a subset; all integrated sensors on wall 1220, wall 1230, ceiling 1240 and floor 1250 are each a subset. Thus, the related information of the facilities in the room can be further obtained. In some embodiments, the data center may receive grouping information of integrated sensors from the integrated sensors. In some embodiments, the grouping information of the integrated sensors may be preset when the integrated sensors are installed (for example, the integrated sensors belong to the wall 1210 or the room a, etc.), and the integrated sensors may be grouped according to the preset grouping information of the integrated sensors, so that the partition information of the indoor space may be obtained. For example: the indoor space is divided into a plurality of rooms or one room is divided into different indoor facilities such as walls, ceilings, floors and the like.

In some embodiments, the data center may also obtain location attribute information for the integrated sensor. For example: the location attribute information of the

integrated sensors

1222, 1223, 1231, and 1234 all show that their locations are protruding outward, and the data center may derive that the room 1200 includes a corner 1260 between

walls

1220 and 1230.

In some embodiments, the room includes corners or walls that are curved, etc., and the location attribute information may include the curvature, etc., of the location where the integrated sensor is located. In some embodiments, the location attribute information may also include a functional area as described by where the integrated sensor is located. For example: the integrated sensor is positioned in special places such as a toilet, a kitchen and the like. The data center may determine that the indoor partition is a special function area. In some embodiments, the location attribute information may also include indoor facilities around the location where the integrated sensor is located. For example: the proximity of the integrated sensors includes partitions, windows, doors, etc. and the data center can determine the location of these facilities indoors.

Further, after the data center obtains the spatial model of the room 1200, the sensor network may further be utilized to sense the spatial environment in the room 1200. The data center divides the space of the room 1200 into a plurality of subspaces to facilitate estimating the environment of other subspaces of the room based on the plurality of integrated sensors detecting the environmental parameters of the different subspaces. As shown, the space of the room 1000 is equally divided into 27 subspaces room01-room27. As will be appreciated by those skilled in the art, the above division is merely exemplary, and the space of the room 1200 may be divided into other numbers of subspaces.

The data center receives the environmental parameters of the positions of the integrated sensors from the integrated sensors, and can obtain indoor environmental information according to the indoor space information obtained by the position information of the integrated sensors. In some embodiments, the indoor space information derived from the location information of the integrated sensor includes at least a size of the indoor space.

The data center assigns a value to an environmental parameter of at least a portion of the subspace using the environmental parameter detected by the integrated sensor. For example: the subspace in direct contact with the integrated sensor may be assigned a value based on the detection result of the integrated sensor. As shown, a subspace near a wall, ceiling or floor may be assigned a value based on the integrated sensor detection result in contact therewith.

In some embodiments, environmental parameters within other subspaces that are not in contact with the integrated sensor may determine environmental parameters within their space from interpolation. Taking the temperature field as an example, when the integrated sensor in the eleventh subspace room11 detects a temperature of 10.0 ℃ and the integrated sensor in the seventeenth subspace room17 detects a temperature of 11.0 ℃, the temperature in the fourteenth subspace room14 can be considered to be 10.5 ℃. Alternatively, taking the humidity field as an example, the humidity detected by the integrated sensor in the fifth subspace room5 is 50% and the humidity detected by the integrated sensor in the thirteenth subspace room23 is 48%, the humidity in the fourteenth subspace room14 is considered to be 49%.

In some embodiments, the data center may estimate a field distribution of the indoor space from the subspace that at least partially determines the environmental parameter, and may determine the environmental parameter for subspaces where other environmental parameters are not determined from the field distribution of the indoor space.

In some implementations, the location properties of the indoor space or the indoor space facilities or the status thereof may have an effect on the flow field of the indoor space. For example: the screen, corner, etc. may affect the temperature field of the indoor space, or the state of indoor facilities such as doors and windows may also affect the temperature field of the indoor space. In some embodiments, the data center receives location attribute information for the locations of the integrated sensors from the plurality of integrated sensors and determines its environmental parameters for the environment of the affected subspace based on the location attribute information. Factors affecting the indoor environment will be described in detail below.

Fig. 13A and 13B are schematic diagrams of indoor environment change according to an embodiment of the present application. From fig. 13A and 13B, it is possible to understand both the distribution of the flow field and the influence of the change in the indoor environment.

As shown, the room 1300 includes

walls

1310, 1320, 1330, a ceiling 1340, and a floor 1350. The layout is the same as that of the above embodiment, and thus will not be described again here. The room 1300 also includes integrated sensors 1301-1308, which are disposed at various corners of the room 1300. For example: the corner where wall 1310 intersects wall 1320 and ceiling 1340, or the corner where wall 1320 intersects wall 1330 and floor 1350. The room 1300 may also include

integrated sensors

1311, 1321, 1331, 1341, and 1351 disposed at the center of the wall, ceiling, and floor, respectively. The integrated sensors 1301-1308, 1311, 1321, 1331, 1341 and 1351 together form a sensor network of the room 1300, and may detect the room 1300 and upload the detection result to the data center, so that a space model may be built for the room 1300 and environmental parameters in the space may be determined, which will not be described herein with reference to the embodiments of fig. 9, 10 and 11.

In some embodiments, the data center may determine environmental parameters of the indoor space or the partial subspace based on the location attribute information of the integrated sensor. In some embodiments, the walls, ceiling or floor of the room 1300 include special shapes that may have an impact on the environment of a portion of the subspace within the room 1300. In some embodiments, the room 1300 includes special areas that may have an impact on environmental parameters of a portion of the subspace. For example: room 1300 includes a bathroom, then the humidity in some of the subspaces may be higher; or the room 1300 includes a kitchen therein, the electromagnetic intensity in a portion of the subspace may be high. In some embodiments, the room 1300 includes some indoor facilities that may have an impact on the environment within a portion of the subspace. For example: doors and windows and the like may have an effect on the temperature in part of the subspace.

In some embodiments, wall 1310 may include door 1313 and wall 1330 may include window 1332, wherein door 1313 and window 1332 may have an impact on the environment within room 1300. Wherein the data center may estimate environmental parameters of the space or various subspaces of the room 1300 based on changes in the state of the door 1313 and/or window 1332. For example: the door 1313 and window 1332 change from a closed state to an open state and the data center may adjust down or up a certain amount (e.g., 2 c, 3 c, 5 c, etc.) to the temperature in the subspace where the door or window is in contact or in between.

In some embodiments, the data center may also estimate environmental parameters of other subspaces of the indoor space based on a plurality of environmental parameter changes of a plurality of integrated sensors after the door 1313 and/or window 1332 state changes. For example: the integrated sensor detects a subspace temperature of 25 c near window 1332 and 20 c near door 1313, and predicts a temperature of 22.5 c for the other subspaces between window 1332 and door 1313.

In some embodiments, the data center may also estimate the environmental parameters or changes in environmental parameters of the indoor space or each subspace through the outdoor environment or the outdoor environment change state. In some embodiments, the outdoor is in different seasons, which can have an effect on the indoor environment (e.g., temperature, humidity, etc.). For example: the outdoor temperature is relatively hot in summer and relatively cold in winter, so that the temperature in the room can be greatly influenced; or more rainwater in summer and drier in winter, and can greatly influence the humidity in the room. In some embodiments, there is also an impact on the indoor environment for different periods of the day outdoors. For example: the temperature in the morning and evening is lower, and the temperature in the noon is higher, can produce great influence to indoor temperature. In some embodiments, the outdoor environment changes significantly, which may have an impact on the indoor environment. For example: sudden precipitation can have a large impact on indoor humidity. In some embodiments, the data center may also accept weather forecasts local to the room 1300, from which the outdoor environment may be determined. In some embodiments, the exterior of the room 1300 may also include integrated sensors for detecting the environment outside the room.

Indoor ringRegulation of the environment

The adjustment of the indoor environment means that the indoor environment is adjusted by starting the indoor electric appliance. The regulation of the indoor environment includes passive regulation and active regulation. Passive regulation is a common way: when the indoor environment changes or the instruction of a user is received, the indoor electric appliance is started to adjust the indoor environment. Active regulation is a specific regulation mode: according to the possible change trend of the indoor environment or the condition of a user, the indoor environment is actively changed, so that the living environment is more friendly and the living is more comfortable.

Fig. 14 is a flowchart of a method of adjusting an indoor environment according to an embodiment of the present invention. As shown in the figure, the method for adjusting indoor environment of the present embodiment includes the following steps: at step 1410, a plurality of environmental parameters of a location of a plurality of integrated sensors are received from the plurality of integrated sensors. As previously described, the sensor network of the indoor space is capable of detecting environmental parameters from multiple locations of the indoor space to the data center transmitter. The data center gathers the detection results, so that the environment parameters of a plurality of positions in the indoor space can be known.

At step 1420, indoor environment information is obtained based at least in part on the plurality of environmental parameters of the plurality of integrated sensors and the indoor space information. As described above, the sensor network can realize the perception of indoor space environment, thereby obtaining more accurate indoor environment information. It will be appreciated by those skilled in the art that the present invention is not limited to the previously described method of spatial environment awareness. Other ways of obtaining accurate spatial environment information may also be applied.

In step 1430, an environmental conditioning device is activated to condition the indoor environment to obtain the desired indoor environment. In the indoor space, one or more environmental conditioning devices are arranged. Different environmental conditioning means may be used for different environmental parameters. Such environmental conditioning devices include, but are not limited to: air conditioning, fans, electric heaters, humidifiers, signal amplifiers, and the like. By activating these appliances or facilities, an adjustment of the indoor environmental parameters can be achieved. In some embodiments, the number and distribution of environmental conditioning devices within the room are arranged so that the data center is aware of its effects on the changes in environmental parameters of the respective subspaces, thereby enabling accurate conditioning of the environment. Taking temperature as an example, the indoor space comprises a plurality of air conditioners or air conditioner air outlets and heaters distributed on each wall, so that accurate adjustment of the temperature of each subspace can be realized.

For passive regulation, the method of the invention allows for a more accurate environmental regulation than in the prior art. For example, the comfort temperature of the indoor environment is 21±2℃. To ensure comfort of living, the temperature of all the occupant-related subspaces is set at 21±2 ℃, and the data center maintains the temperature of these subspaces. Through the perception of the indoor space environment, the data center finds that the temperature of the subspace near the doors and windows in the indoor space is 23 ℃, while the temperature of the subspace of the bed located farther from the doors and windows in the indoor space reaches 25 ℃. The data center starts an air conditioner or an air outlet of the air conditioner near the bed, reduces the temperature of the subspace of the bed, and controls the temperature around the bed within the range of human comfort. From such an example, it can be seen that by spatial environment perception, finer environmental parameters of the spatial environment can be obtained, and thus finer environmental parameter adjustment can be achieved.

For another example, the data center receives commands of a plurality of people moving indoors through the integrated sensor, and the environmental parameters of the subspaces where the plurality of people are located can be respectively adjusted according to the commands, so that the plurality of people moving indoors can enjoy a comfortable indoor environment. For example, indoors includes two people, men and women: a and B, wherein a prefers a somewhat lower temperature; whereas B prefers a slightly higher temperature. When both A and B are in the same room, A and B may issue different commands, A being a temperature decrease to 16 ℃; and B is commanded to increase the temperature to 25 ℃. In the prior art, such commands are not executable. In the case of the present invention, if there is a certain space between a and B, in different subspaces; the data center may then meet such a need by fine-tuning the temperature of each of the a and B subspaces. The data center can reduce the temperature of the subspace where A is located through an air conditioner; and the temperature of the subspace where B is located is raised by the heater. Thus, both A and B can enjoy respective comfortable environments, thereby improving the comfort of the whole indoor living environment.

The indoor environment regulation of the invention is characterized by active regulation, namely the environment can be actively regulated without changing the environment or receiving the command of a user, and the living comfort is further improved. This is further illustrated by the following examples.

In some embodiments, the data center may predict environmental parameter changes of each subspace in the indoor space according to state changes of the indoor facility, and actively adjust the indoor environment according to the predicted environmental parameter changes of each subspace. For example, if a door or window in a room transitions from a closed state to an open state, the temperature in the room may not change immediately. After the data center detects the state change of the door or window of the indoor facility, the indoor temperature can be estimated to rise or fall according to the outdoor temperature, the wind speed and the like. Further, the data center may activate the environmental conditioning device to adjust the temperature of each subspace to maintain the indoor environment within the comfort range. In other words, the temperature in the room is not changed while the door or window is ventilated.

In some embodiments, the indoor facility where the state change occurs may be an environmental conditioning device. After the environment adjusting device is started, the data center can estimate the environment parameters of each indoor subspace. For example: taking fig. 13 as an example, the initial temperature of each indoor subspace is 20 ℃, the air conditioner at the wall 1310 is turned on for cooling, the temperature of the subspace close to the wall 1310 estimated by the data center according to the power and the wind direction of the air conditioner can be 15 ℃, the temperature of the subspace close to the wall 1330 can be 18 ℃, and the temperature of the subspace between the two can be 16 ℃. Further, the data center may self-activate 1310 the heating device of the subspace to raise 1310 the temperature of the subspace, thereby maintaining the temperature of each subspace in a comfortable environment.

If one or more persons exist in the room, the data center can actively adjust the environmental parameters of subspaces around the persons according to whether the persons exist, the identities and activities of the persons and the like, so that the living environment is more humanized.

In some embodiments, multiple integrated sensors within the room 1300 may detect one or more persons moving indoors. The data center can know that people are now active in the room and know the number and positions of people. The data center can actively adjust the illumination of each subspace visible by a person, so that the human eyes can comfortably see the indoor conditions.

In some embodiments, multiple integrated sensors within the room 1300 may detect one or more human body parameters of indoor activity, and the data center may adjust the environment of surrounding subspaces of indoor activity based on the detection results. Taking temperature as an example, if the data center finds that one of a plurality of people moving indoors has a raised body temperature (whether due to sports or eating hot food, etc.), the data center can turn on the air conditioner to reduce the temperature of the subspace where the person having the raised body temperature is located, so that the person feels comfortable; while keeping the temperature of the subspace around the other people unchanged.

The data center can identify the identity of the person and actively adjust the environment of the subspace around the indoor movable person according to the identity. For example: the integrated sensor detects that the a-user is located near

walls

1310 and 1320, and the data center can adjust the environment of the subspace around the a-user according to the habit of the a-user, so as to adjust the temperature to the habit range of the a-user.

In some embodiments, the integrated sensor identifies the activity of the indoor active person, and the data center can actively adjust the environmental parameters of the subspace near the indoor active person according to the identification result. For example, when it is identified that someone in the room sleeps (e.g., lies in the bed inactive for more than a predetermined time), the temperature of its surrounding subspaces is appropriately raised. For another example, when an indoor person is identified to be in motion (e.g., running, exercising, etc.), the oxygen content of the surrounding subspace is appropriately adjusted.

The invention has the other characteristic that the energy conservation and environmental protection can be realized on the premise of not reducing the comfort level of the living environment by accurately adjusting the indoor environment, thereby being more in line with the future development direction of the home.

In some embodiments, the data center turns on or off the environmental parameter adjustment device in response to detection of one or more persons of the indoor activity. For example, when the data center recognizes that there are one or more persons in the room, then the signal amplifiers of its surrounding subspaces are activated so that the one or more persons can enjoy the wireless signal. If no person is in the room or for a subspace of surrounding persons, the data center turns off the signal amplifier to save energy. The same is true for temperature. The data center recognizes that the indoor person is in a sleep state, and except for the subspace around the person, the temperature is properly increased to ensure the comfort of the living environment, and for the rest subspace, the data center can close the air conditioner or the environment temperature adjusting device such as the heater, thereby saving energy. The invention can realize fine adjustment of indoor environment, thereby saving energy to the maximum extent and realizing green home.

In some embodiments, even when the indoor environment is conditioned, the data center estimates a plurality of environmental conditioning devices, and their corresponding power, that are required to be activated to condition the environment of each subspace in the room, based on the desired indoor environment, prior to activating the environmental conditioning devices.

In some embodiments, the data center may activate the environmental conditioning device in a manner that evaluates the total minimum consumption of multiple environmental conditioning devices that need to be activated to condition the indoor environment to facilitate energy conservation. For example: when the user a is located at a location where cooling is desired, either the refrigeration of wall 1310, the refrigeration of wall 1320, or both may be utilized. Through the energy consumption comparison, the data center chooses to control the cooling device of wall 1310 to cool the subspace around it without activating the cooling device of wall 1320. In this way, the temperature of the location where user a is located can be reduced to the desired temperature range with minimal energy consumption.

In some embodiments, comfort is also a concern. The data center can also estimate the mode that a plurality of environment adjusting devices are required to be started to adjust the indoor environment, and the environment adjusting devices are started in the fastest adjusting speed mode, so that the user experience is improved. For example: when the user B is located at a position where it needs to be warmed, the heating means near the wall 1330 and the floor 1350 are controlled to heat the subspace around them at the same time, so as to raise the temperature of the position where B is located to a desired temperature range at the highest speed.

In the above section of the present disclosure, the technical solution of the present disclosure is illustrated by integrating sensors, sensor networks, indoor space modeling, indoor space environment sensing, and indoor space environment adjustment in a manner of a plurality of embodiments. Those skilled in the art will appreciate that there are numerous possible variations to the solution of the invention that remain within the scope of the invention.

The technical scheme of the invention is further described below through two variants of the technical scheme of the invention.

Spatial modeling using modeling elements instead of integrated sensors

In this embodiment, the indoor space modeling element has a positioning function, and may not include a sensor, and does not have a detection function. The plurality of sensors may be positioned relative to the plurality of modeling elements at a lower cost and more flexible.

Fig. 15 is a schematic structural view of an indoor space modeling element according to an embodiment of the present application. As shown, the modeling element 1500 of the indoor space includes a processor 1510, a positioning element 1520, and a communication module 1530; wherein the processor 1510 is electrically connected to the positioning element 1520 and the communication module 1530. Positioning element 1520 is used to determine the position of the modeling element, and in some embodiments, the positioning element may implement indoor space positioning by UWB, wi-Fi, RFID, infrared, or ultrasonic, among others. In some embodiments, the communication module 1530 is used to communicate with a home data center or a data center that is a room-centric.

In some embodiments, modeling element 1500 can also include a memory 1540, which is electrically coupled to processor 1510 and can be used to store data for modeling element 1500. In some embodiments, memory 1540 may be integrated with the processor on the same chip.

In some embodiments, the modeling element may also include an input display 1560 that is coupled to the processor and may be used to input information into the processor and display related information. For example: identity information and/or location information of the modeling element may be input to the processor. In some embodiments, the input display device may be a touch display screen.

FIG. 16 is a schematic diagram of an indoor space modeling flow based on modeling elements according to an embodiment of the invention. As shown, at step 1610, the data center obtains positional information for each modeling element from a plurality of modeling elements. As previously described, the positioning element of the modeling element enables indoor space positioning. The data center receives spatial positioning information of its positioning elements from the modeling elements to obtain the positions of the modeling elements.

To facilitate positioning, in some embodiments, the positional information of the modeling element includes altitude and/or horizontal relative positional information. In some embodiments, the horizontal relative position may be a relative position with respect to a locating point within the room. For spatial positioning, determining the height is sometimes difficult. By arranging the modeling elements at a fixed height or heights and using only positioning elements to obtain horizontal relative position information, spatial positioning can be simplified and the results more accurate. In some embodiments, the positioning manner of the integrated sensor relative to the positioning point in the room in the foregoing embodiments is also applicable, and will not be described herein.

In step 1620, the data center may obtain partition information of the indoor space according to the grouping of the plurality of modeling elements. In some embodiments, the data center may receive grouping information of a plurality of modeling elements from the modeling elements. The grouping information can be utilized to realize grouping of modeling elements, so that the partition of the indoor space is obtained. Similar to the integrated sensor embodiment, in some embodiments, multiple groupings of modeling elements may be matched by shape. For example: a plurality of modeling elements that make up a rectangular shape are grouped. In some embodiments, grouping of modeling elements may be accomplished by a clustering algorithm.

In step 1630, the data center obtains size information of the indoor space partition from the position information of the plurality of modeling elements obtained from the plurality of modeling elements, forming an indoor space model. In some embodiments, the data center may also receive location attribute information from a plurality of modeling elements, such that characteristic information of the indoor space partition may be derived. In some embodiments, the location attribute information includes, but is not limited to: radian of the modeling element, convexity and concavity of the modeling element, functional area of the modeling element, and indoor facilities around the modeling element.

In step 1640, a plurality of locations of a plurality of sensors within the room are identified in the indoor space model. For spatial environment awareness and spatial environment control, it is necessary to know the position of the sensor in the spatial model, which does not include a positioning element.

In some embodiments, the plurality of sensors also include a positioning element, such as by UWB, wi-Fi, RFID, infrared, or ultrasonic means, to effect indoor space positioning. In this step, the calibration of the sensor position can be achieved based on the positions received from the plurality of sensors.

In some embodiments, the plurality of sensors does not include a positioning element to reduce cost. The plurality of sensors uses their position relative to the modeling element to achieve position calibration in the spatial model. In some embodiments, the relative positions of the sensor and the modeling element are fixed. For example, a simple rule is that one sensor is placed at the midpoint between two modeling elements, and the naming of each sensor indicates that it is between those two modeling elements. For example, sensor A12 represents a sensor at the midpoint between modeling elements No. 1 and No. 2 in room A. B67 represents the sensor at the midpoint between modeling elements No. 6 and No. 7 in room B. In this way, the data center can know the position of the sensor relative to the modeling element based on the name of the sensor, and can therefore map its position to a spatial model.

In some more complex examples, the plurality of sensors includes RFID tags. The plurality of modeling elements also includes RFID tags. The RFID tag has low cost and is beneficial to large-scale use and popularization. A plurality of RFID scanners are disposed indoors. By scanning the sensor, the time and signal strength of the return of the RFID tag at different locations can be obtained. Calibration with the return times and signal strengths of the RFID's of the multiple modeling elements allows knowledge of the locations of the multiple sensors relative to the modeling elements. The technical action distance is several meters to tens of meters, and the indoor positioning requirement can be met. The information with centimeter-level positioning accuracy can be obtained in a few milliseconds through the RFID scanner, and the transmission range is large and the cost is low. The same applies to infrared, wi-Fi, ultrasonic, and the like.

Therefore, the combination of the sensor network and the space model is realized by calibrating the positions of the plurality of sensors on the indoor space model, so that the follow-up indoor environment sensing and indoor environment control can be realized, the indoor environment can be detected more finely, the indoor environment is changed, and the better living environment is provided.

In some embodiments, the modeling element may also have a probing function. In this way, the modeling element may also become a sensor. However, this type of sensor of the modeling element will be quite special, enabling indoor positioning by its own positioning element without the help of other sensors. While another type of sensor, while also having a positioning element, is not capable of positioning itself, and must rely on other sensors to achieve positioning.

Space modeling using indoor facilities

In this embodiment, an indoor facility such as a wall, a skirting, a floor, or a ceiling has a positioning function, and also includes a plurality of sensors having a detecting function; therefore, the sensor network and the space modeling can be directly realized, the method is suitable for industrial production, and the cost is lower.

17A-17D are schematic structural views of indoor facilities according to one embodiment of the present application; wherein the indoor facility shown in fig. 17A is a movable wall; the indoor facility shown in fig. 17B is a skirting; the indoor facility shown in fig. 17C is a floor; and the indoor facility shown in fig. 17D is a ceiling. As shown, a processor 1710, a positioning element 1720, and a communication module 1730 are included in each of these facilities; wherein the processor 1710 is electrically connected to the positioning element 1720 and the communication module 1730. The positioning element 1720 is used to determine the position of the modeling element, and in some embodiments, the positioning element may be configured to perform indoor space positioning via UWB, wi-Fi, RFID, infrared, or ultrasound, among others. In some embodiments, the communication module 1730 is used to communicate with a home data center or a data center of a room-dividing center.

Fig. 18 is a schematic diagram of an indoor space modeling flow based on an indoor facility according to an embodiment of the present invention. As shown, the data center obtains location information of each indoor facility from a plurality of indoor facilities in step 1810. As previously described, one or more positioning elements of a plurality of indoor facilities enable indoor space positioning. The data center receives spatial location information of its location elements from the indoor facility to obtain the location of the indoor facility.

To facilitate positioning, in some embodiments, the location information of the indoor facility includes altitude and/or horizontal relative location information. In some embodiments, the horizontal relative position may be a relative position with respect to a locating point within the room. For spatial positioning, determining the height is sometimes difficult. By arranging the indoor installation at a fixed height or heights and obtaining horizontal relative position information only with the positioning elements, spatial positioning can be simplified and the results also more accurate. The number of positioning elements used in indoor facilities is small, so that high requirements on positioning accuracy are met. In some embodiments, the positioning element is a high precision positioning technique such as UWB, infrared, ultrasonic, etc., providing positioning accuracy on the order of centimeters or greater.

In step 1820, the data center may obtain partition information of the indoor space based on the location information of the plurality of indoor facilities obtained from the plurality of indoor facilities. In some embodiments, some indoor facilities are used to partition an indoor space, and the indoor space may be divided into a plurality of areas directly according to the size and location of the indoor facility, such as the length or location of a wall or a skirting. The respective indoor facilities are thus used to divide the respective areas. Other indoor settings, such as floors, ceilings, etc., are divided into separate rooms.

In step 1830, the data center obtains size information of the indoor space partition, forming an indoor space model. In some embodiments, the data center receives location attribute information from a plurality of indoor facilities, such that characteristic information of the indoor space partition may be derived. In some embodiments, the location attribute information includes, but is not limited to: radian of the position of the indoor facility, convexity and concavity of the position of the indoor facility, functional area of the position of the indoor facility, and indoor facilities around the position of the indoor facility.

In step 1840, a plurality of locations of a plurality of sensors within the room are identified in the indoor space model. For spatial environment awareness and spatial environment control, it is necessary to know the position of the sensor in the spatial model, which does not include a positioning element.

In some embodiments, the plurality of sensors does not include a positioning element to reduce cost. The plurality of sensors are installed in the indoor installation with their positions fixed relative to the positioning elements of the indoor installation, and thus, the position calibration in the spatial model can be directly achieved. For example, the naming of each sensor indicates its position relative to the positioning element of the indoor installation. For example, sensor a12 represents sensor No. 12 in the indoor facility wall a. The data center stores a table of specific locations of the individual sensors in the individual indoor facilities. The data center can know through the lookup table that the sensor No. 12 is the sensor with the distance of 40cm at 45 degrees above the right of the positioning element in the wall A. Thus, the data center can calibrate the position of the A12 sensor in the indoor space model. For another example, B67 represents a 67 th sensor in the indoor floor B. The data center can know the position of the 67 th sensor through table look-up, and the position of the 67 th sensor is at the position with the locating element of the floor B as the origin and the coordinates of 150-300 cm. Thus, the data center can calibrate the position of the B67 sensor in the indoor space model. Thus, the data center can know the position of the sensor relative to the indoor facility positioning element according to the name of the sensor, so that the position of the sensor can be calibrated on the space model. In the embodiment, the sensor does not need to add any additional positioning element, and has low cost and good expansibility. In some embodiments, the positioning element of the indoor facility may also have a detection function. In this way, the positioning element can also become a sensor, as part of the sensor network.

The above embodiments are provided for illustrating the present invention and not for limiting the present invention, and various changes and modifications may be made by one skilled in the relevant art without departing from the scope of the present invention, therefore, all equivalent technical solutions shall fall within the scope of the present disclosure.

Claims

1. A modeling method of an indoor space, comprising:

receiving location information of a plurality of integrated sensors from the plurality of integrated sensors;

based on the grouping of the plurality of integrated sensors, obtaining partition information of the indoor space; and

obtaining size information of the partition based on the position information of the plurality of integrated sensors;

wherein the sensor-integrated probe includes a channel in communication with an interior space of the integrated sensor, one or more sensors disposed in the channel and the interior space; the probe comprises a probe surface which is in direct contact with the room, one or more sensors are arranged on the probe surface, and the sensors positioned on the probe surface are in direct contact with the room environment;

Wherein the integrated sensor is configured to detect one or more environmental parameters of the indoor environment and/or one or more human parameters of a person moving indoors.

2. The method of claim 1, wherein an environmental or body parameter is determined in common from a plurality of detection results from one or more of a plurality of integrated sensors.

3. The method of claim 1, wherein the integrated sensor is configured to detect commands issued by people moving indoors.

4. The method of claim 1, wherein the location information comprises altitude.

5. The method of claim 1, wherein the location information comprises horizontal relative location information.

6. The method of claim 1, further comprising: grouping information of the plurality of integrated sensors is received from the plurality of integrated sensors.

7. The method of claim 1, further comprising: grouping the plurality of integrated sensors, and obtaining partition information of the indoor space based on grouping information obtained after grouping.

8. The method of claim 7, wherein the grouping of the plurality of integrated sensors is based at least in part on shape matching.

9. The method of claim 7, wherein the grouping of the plurality of integrated sensors is based at least in part on region partitioning.

10. The method of claim 7, wherein the zoning is based on detection results of the plurality of integrated sensors.

11. The method of claim 1, further comprising receiving location attribute information from the plurality of integrated sensors.

12. The method of claim 11, further comprising obtaining characteristic information of the partition of indoor space based at least in part on location attribute information of the plurality of integrated sensors.

13. The method of claim 11, wherein the location attribute information includes radians of the location.

14. The method of claim 11, wherein the location attribute information includes a convexity and concavity of the location.

15. The method of claim 11, wherein the location attribute information includes a function area to which the location belongs.

16. The method of claim 11, wherein the location attribute information includes indoor facilities around the location.

17. A system for indoor space modeling, comprising:

a plurality of integrated sensors distributed in the indoor space; and

A data center in communication with the plurality of integrated sensors;

wherein the data center is configured to obtain partition information of an indoor space based on the grouping of the plurality of integrated sensors; obtaining size information of the subareas based on the position information of the plurality of integrated sensors;

18. The system of claim 17, wherein the location information comprises altitude.

19. The system of claim 17, wherein the location information comprises horizontal relative location information.

20. The system of claim 17, wherein the data center is configured to receive grouping information of the plurality of integrated sensors from the plurality of integrated sensors.

21. The system of claim 17, wherein the data center is configured to group the plurality of integrated sensors, and obtain partition information of an indoor space based on grouping information obtained after grouping.

22. The system of claim 17, wherein the data center is configured to receive location attribute information from the plurality of integrated sensors.

23. The system of claim 22, wherein the data center is configured to obtain characteristic information of the partition of indoor space based at least in part on location attribute information of the plurality of integrated sensors.