CN111829579B

CN111829579B - Indoor space reconstruction method

Info

Publication number: CN111829579B
Application number: CN202010489251.6A
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: 2022-05-20
Anticipated expiration: 2040-06-02
Also published as: CN111829579A

Abstract

The invention relates to a method for reconstructing an indoor space, which comprises the following steps: receiving location information of a plurality of indoor facilities from the plurality of indoor facilities; obtaining partition information of an indoor space based on the location information of the plurality of indoor facilities; obtaining size information of the partition; and calibrating a plurality of positions of a plurality of sensors in the chamber. According to the indoor space reconstruction method, the size of the indoor partition can be obtained through the position information and grouping of the indoor facilities, and therefore the indoor space is reconstructed.

Description

Indoor space reconstruction method

Technical Field

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

Background

In this century, sensor technology has gained rapid development as one of the important pillars of modern information technology. Various sensors based on semiconductor materials, crystal materials, ceramic materials, organic composite materials, metal materials, polymer materials, superconducting materials, optical fiber materials, and nano materials are developed and started to gradually enter homes. From conventional temperature and humidity sensors to PM2.5 detectors reflecting air quality, they are widely used in homes.

With the gradual acceptance of the smart home concept by people and the popularization of devices with the function of the internet of things, modeling of an indoor space is gradually needed, and the indoor space modeling refers to building of a model of the indoor space. In the prior art, the layout of the indoor space is generally constant. For example, there are several rooms in a house and the size and orientation of each room is rarely adjusted. However, for future smart homes, the layout of the indoor space can be easily changed. And when the room layout is not changed, the data center may store an externally input indoor space model. However, when the layout of a room is frequently changed, it becomes very inconvenient to input an indoor space model from the outside each time. Therefore, there is an urgent need in the art to automatically obtain the layout of the room, or to automatically update the layout of the room when the layout of the room changes, so as to obtain a model of the indoor space to be able to adapt to the future smart home.

Disclosure of Invention

Aiming at the technical problems in the prior art, the application provides a method for reconstructing an indoor space, which comprises the following steps: receiving location information of a plurality of indoor facilities from the plurality of indoor facilities; obtaining partition information of an indoor space based on the location information of the plurality of indoor facilities; obtaining size information of the partition; and calibrating a plurality of positions of a plurality of sensors in the chamber.

The method as described above, wherein the indoor facility is one or more of a movable or non-movable wall, floor, or ceiling.

The method as described above, wherein the indoor facility comprises one or more locations.

The method as described above, wherein the positioning member is configured to be positioned using UWB, infrared, or ultrasonic.

The method as described above, wherein the location of the indoor facility is determined according to the location of the positioning member and the size of the indoor facility.

The method as described above, further comprising: partition information of an indoor space is obtained according to the positions of a plurality of indoor facilities.

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

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

The method as described above, wherein the location attribute information includes one or more of radian, convexity, functional area and indoor facilities around the location.

The method as described above, wherein the sensor in the indoor facility is positionable relative to the locator.

According to another aspect of the present application, there is provided a system for modeling an indoor space, comprising: a plurality of indoor facilities distributed in the indoor space; and a data center in communication with the plurality of indoor facilities; wherein the data center is configured to obtain size information of the zones based on the grouping of the plurality of indoor facilities, based on location information of the plurality of indoor facilities, and calibrate a plurality of locations of a plurality of sensors in a room.

The system as described above, wherein the indoor facility comprises one or more locations.

The system as described above, wherein the positioning member is configured to be positioned using UWB, infrared, or ultrasonic.

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

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

The system as described above, wherein the sensor does not comprise a positioning device.

According to the indoor space reconstruction method, the size of the indoor partition can be obtained through the position information and grouping of the indoor facilities, and therefore the indoor space is reconstructed.

Drawings

Preferred embodiments of the present invention will now be described in further detail with reference to the accompanying drawings, in which:

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

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

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

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

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

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

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

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

FIG. 10 is a flow diagram of a method of modeling an 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 view of an indoor model according to one embodiment of the present application;

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

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

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

FIG. 16 is a schematic diagram of a modeling element-based indoor space modeling process according to an embodiment of the invention;

FIGS. 17A-17D are schematic structural views of an indoor facility according to one embodiment of the present application; and

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

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In the following detailed description, reference is made to the accompanying drawings that form a part hereof and in which is shown by way of illustration specific embodiments of the application. In the drawings, like 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 and 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 provides 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 just integrated sensors. The technical solution of the present application will be described below by taking an integrated sensor as an example, and as understood by those skilled in the art, the position of the integrated sensor may also include a plurality of sensors of different kinds.

In some embodiments of the present invention, the integrated sensor aggregates a plurality of environmental sensors, including but not limited to: one or more of a photosensitive sensor (visual sense), an acoustic sensor (auditory sense), a gas sensor (olfactory sense), a chemical sensor (gustatory sense), a pressure-sensitive sensor (tactile sense), a fluid sensor (tactile sense), a thermal sensor (temperature), a humidity-sensitive sensor (humidity), a magnetic-sensitive sensor (magnetic field), and the like. An environmental sensor user detects one or more parameters of an indoor environment.

In some embodiments of the invention, the integrated sensor aggregates 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 velocity 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 human sensor may be the same sensor, such as a sound sensor. The sound sensor has a function of detecting sound. It is possible to detect both sounds in the environment and sounds made by a person. In some embodiments, the same sensor may have both the function of detecting environmental parameters and human parameters, such as a temperature sensor. The temperature sensor can detect the temperature of indoor air and can also detect the temperature of a human body in a remote distance. However, detecting air temperature and remotely detecting body temperature are two completely different functions.

In some embodiments, the plurality of results detected by the integrated sensor collectively characterize an environmental or human parameter. For example, the results of temperature detection and the results of smoke detection in the integrated sensor together indicate an indoor fire. In some embodiments, the detection results of the plurality of integrated sensors collectively characterize an environmental or human parameter. For example, accurate positioning can be achieved by arranging a plurality of cameras at appropriate positions. As another example, the gravity detection of an integrated sensor at one location in combination with the infrared detection of an integrated sensor at another location may indicate that a person is active at one 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 result of an integrated sensor at one position can locate a person at one position, and the instruction obtained by a gesture motion sensor at another position is combined with an active command which indicates that the person sends.

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

FIG. 1 is a schematic diagram 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 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 to enable assembly of the housing 102, probe 104, and circuit board 106.

As noted in the background of the invention, an important application of the integrated sensor of the present embodiment is to detect indoor human-occupied environments. 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 external surface of the integrated sensor, and thus is in direct contact with the indoor environment. In some embodiments, the probe 104 includes one or more channels in communication 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 at the same time.

In some embodiments, the probe 104 includes a plurality of sensors 11-14. The plurality of sensors 11-14 are a plurality of environment and/or body detectors for detecting a plurality of environmental 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 disposed on the housing 102 or support structure, such as: a conductive coating, a conductive paste, or a conductive layer, etc., rather than electrical leads.

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

Unlike the temperature or humidity detector in the prior art, the integrated sensor of the present embodiment is suitable for installation in indoor facilities such as a wall, a floor, or a ceiling, and thus is integrated with an indoor environment. This has many advantages: on one hand, the appearance design of the integrated sensor can be simplified, and the integrated sensor does not influence the integral beauty of a room; on the other hand, the installation of the integrated sensor is more convenient, and the parts such as the wall, the floor or the ceiling of an indoor room can not be damaged. More importantly, the integrated sensor is arranged in indoor facilities such as a wall, a floor or a ceiling of a room, so that larger space can be provided for integrating a plurality of sensors, the space limitation is not worried about, and the implementation of the integrated sensor is facilitated.

In some embodiments, a bracket is included in the wall, floor, or roof for mounting the integrated sensor. The carrier itself is part of a wall, floor or ceiling and the integrated sensor is mounted on the carrier so as to be located in the wall, floor or ceiling. In some embodiments, the wall, floor, or ceiling is a removable wall, floor, or ceiling that is not rigidly connected to the original wall, floor, or roof of the room. The application number is 201910295819.8, the application date is 2019, 4 and 12, the invention name is an assembly type building and an internal tension wall body, and discloses an internal tension wall which is an example of a movable wall which is not in hard connection with an original wall surface, a floor and a roof. This application is incorporated by reference herein in its entirety. The invention discloses a ceiling and an assembly type building, and the ceiling is an example of a ceiling which is not in hard connection with an original wall surface, a floor and a roof, wherein the application number is 201910858472.3, the application date is 2019, 9 and 11. This application is also incorporated herein by reference in its entirety. Sufficient space is included in both the moveable wall and ceiling as in the above two examples to accommodate the integrated sensors of the present application. Thus, as a preferred embodiment, the integrated sensor of the present application is used with a removable wall, floor, or ceiling that is not hard-wired to the original wall, floor, and roof of the room. In the prior art, there are various ways to implement the installation of the integrated sensor, which are not limited to the way of the bracket, and are not described herein again.

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 a surface or portion thereof of the integrated sensor 100 that is in direct contact with the environment. The sensors 11-14 detect indoor environmental or human parameters through the surface of the probe 104 in direct contact with the environment. In the following 2 specific examples, further designs of integrated sensor probe and housing are shown. Of course, the implementation of the integrated sensor of the present invention is not so limited.

Fig. 2 is a schematic structural diagram 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 portions are similar to the corresponding portions of the embodiment depicted in figure 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 an interior space 207 of the integrated sensor 200. One or more sensors 21-24 are arranged in the channel 205 and the inner 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 a smaller volume and a higher degree of 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. The channel 205 is disposed through the probe face 209. One or more sensors 25-28 are included on the probe face 209. The sensors 25-28 are in direct contact with the indoor environment. These sensors include, but are not limited to: optical 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 probing 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, a probe 304, and circuitry (not shown); wherein the housing and circuit portions are similar to the corresponding portions of the embodiment depicted in figure 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 circuitry may also be implemented in a manner similar 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 channel 305 and the interior space 307, which are in indirect contact with the indoor environment through the channel 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 a smaller volume and a higher degree of 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 disposed through the probe face 309. One or more sensors 36-39 are included on the probe face 309. The sensors 36-39 are in direct contact with the indoor environment. These sensors include, but are not limited to: optical sensors, pyroelectric sensors, infrared sensors, pressure sensors, etc. The probe face 309 provides a surface that is in direct contact with the indoor environment, facilitating accurate detection results.

In some embodiments, there may be a spacer between the integrated sensor and the indoor environment. These spacers include hollowed or vented decorative panels such as wood grain panels, cardboard, stone panels, glazed tiles, etc., or panels coated with materials such as wall paint, wallpaper, wall cloth, wall mud, wall plaster, etc.; hollowed or vented decorations such as decorative pictures, photographs, artworks, textiles, collectibles, floral artworks, etc.; 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 configuration according to one embodiment of the present invention. As shown, 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, processor 402 includes multiple ports each corresponding to a different sensor. For example, the processor 402 includes an 8-channel I/O port, where 2 channels are analog quantities; 2 channels are digital quantities; the 2 channels are switching values. Each channel of the processor 402 corresponds to a sensor of a different type of detection.

In some embodiments, to increase the number of sensors that an integrated sensor can accommodate, and to reduce the limit on the number of sensors that a processor channel can accommodate, communication between the processor and the plurality of sensors is implemented using a fieldbus or a non-fieldbus.

Referring to fig. 4, the

first analog sensors

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

analog sensors

41 and 42 are connected to the digital lines via the analog-to-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 via switching value lines. In some embodiments, the digital and switching value lines may be combined into the same line. Such lines include, but are not limited to: remote digital IO lines, for example: PROFIBUS, MODBUS, etc.; or fieldbus lines, for example: RS485, CAN, CC-LINK, D-Net, ASI, DP bus, etc.; or data bus lines, for example: PCI, PCIe, USB bus, etc. Some high-latency off-site buses (e.g., databuses) may also be used in the present invention, since detection real-time performance for integrated sensors is not critical.

In some embodiments, one or more signal conditioning circuits may be included between the sensors and the circuitry for converting the detection signals from the sensors into standard analog, digital, differential, or switching signals 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 some of the sensors to reduce the workload on processor 402, reduce cost, and improve system efficiency.

In some embodiments, some of the sensors may also be disposed on the circuit board. For these sensors, all the electronics associated therewith may be integrated on the circuit board on which the sensor is integrated. In other embodiments, for the sensors disposed on the circuit board, other electronic devices, including the signal conditioning circuit, the controller and the lines therebetween, are disposed on the circuit board, besides the necessary lines between the sensors and the circuit board, thereby improving the integration of the plurality of sensors.

In this embodiment, the processor 402 may support different sensors through a plurality of different types of interfaces, or may support analog, digital, and switching value lines of the plurality of sensors to communicate with sensors of different types of measurement results, respectively, so as to realize integration of a plurality of types of sensors; 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, integrated sensor 400 digital or switch-value circuitry, respectively, may include plug-and-play interfaces to facilitate adding or changing the functionality of integrated sensor 400 as desired. For example, one or more plug-and-play interfaces, including but not limited to PCIe, PCI, and USB interfaces, are included in the digital or analog lines of integrated sensor 400. For sensors whose output results are digital or switching values, this can be achieved by connecting to these plug-and-play interfaces. For the sensor with the output result of analog quantity, the sensor can be converted into a digital signal through the ADC, and then plug and play can be realized through a plug and play interface in a digital quantity or analog quantity line.

In some embodiments, integrated sensor 400 also includes a display module 404 in communication with 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, which displays the operation status or the detection result. As another example, the display module 404 is a plurality of indicator lights that reflect the operating status of the integrated sensor 400 by color, illumination, flashing, etc.

In some embodiments, integrated sensor 400 also includes memory 406 in communication with processor 402. The memory is used to store data for integrated sensor 400, including but not limited to: the detection results of the integrated sensor, the data (e.g., position, operating state, etc.) of the integrated sensor itself, and the data during the operation of the integrated sensor.

In some embodiments, integrated sensor 400 also 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. The 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. The communication protocol employed by the wired module includes, but is not limited to: remote digital IO lines, for example: PROFIBUS, MODBUS, etc.; or fieldbus lines, for example: RS485, CAN, CC-LINK, D-Net, ASI, DP bus, etc.; or data bus lines, for example: PCI, PCIe, USB bus, etc. Particularly for some embodiments in which the integrated sensor is disposed on a movable wall or ceiling, a wire for wired communication may be preset in the movable wall or ceiling to support the integrated sensor to communicate by wire.

In some embodiments, the 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.

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

Since the integrated sensor is provided in a wall, floor or ceiling, arranging a wired power supply line is an optional option. In some embodiments, the integrated sensor further comprises a wireless charging module 504 connected to the battery 501. The wireless charging of the battery 501 can be realized 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 solar charging module 506 can convert light energy into electric energy to charge the battery 501. In the case of a removable wall, floor or ceiling embodiment, the integrated sensor may also be directly powered by the power supply lines already included in the removable wall, floor or ceiling. In this embodiment, the battery 501, the wireless charging module 504, and the solar charging module 506 are all optional.

As some embodiments of the present invention show, the integrated sensor has the following advantages:

1. small size, light weight and low power consumption. The integrated sensor of the present invention achieves the integration of multiple sensors, is an independent, fully functional electronic system, and can be implemented on a small monolithic integrated circuit board. The volume can be reduced, the weight can be reduced, and the power consumption can be reduced while multiple detection functions are realized.

2. The cost is low. On the one hand, the integrated sensor of the invention is convenient for mass production, thereby enabling the cost to 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 greatly reduced.

3. The reliability is high. The integrated sensor integrates a plurality of electronic devices on one circuit board, connecting points and 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 realizes the integration and mutual communication of a plurality of sensors and the 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 diagram of an indoor human-living environment sensing system according to an embodiment of the invention. As shown, the indoor human-occupiable environment sensing system of the present embodiment includes a plurality of integrated sensors, e.g., integrated sensors a-H, respectively disposed in an indoor environment. In some embodiments, the plurality of integrated sensors are respectively disposed in a wall, a floor, and a ceiling. In particular, walls, floors and ceilings are movable walls, floors and ceilings. Further, the indoor human living environment perception system of the embodiment comprises a family data center. A plurality of integrated sensors communicate wirelessly with a home data center. The home data center can be a server, a special machine, a computer, a notebook computer and other equipment, and can also be mobile equipment such as a mobile phone, a Pad and the like.

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

In some embodiments, a home data center includes one or more processors, a first communication module, and a second communication module. A first wireless module for communicating with the plurality of integrated sensors, receiving one or more probe results from the plurality of integrated sensors; or send control commands to multiple integrated sensors. The first communication module can be a data transceiving end of communication protocols such as 5G, 2.5G, Wi-Fi, Zigbee, Lora, NB-IOT, Z-Ware, Bluetooth and the like. The second communication module is used for communicating with an external network in a wired or wireless manner, including but not limited to the mobile Internet, the Internet, and other networks capable of realizing bidirectional communication.

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

In some embodiments, the home data center can process the detection results from the integrated sensors or the non-integrated sensors, and based on the detection results, adjust one or more parameters of the indoor environment by using technologies such as big data and artificial intelligence, thereby realizing 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 of the first integrated sensor.

At step 730, the detection results from the second sensor of the first integrated sensors and/or the detection results from the third sensor of the second integrated sensors are received at the home data center. The first integrated sensor sends the detection result of the second sensor to a home data center through a 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, in the home data center, the detection results of the first sensor, the second sensor and/or the third sensor are comprehensively analyzed to obtain one or more indoor environmental parameters or human body parameters. As will be understood by those skilled in the art, the present invention does not limit the types, number and detection time of the integrated sensors and the sensors therein, and the comprehensive analysis of the detection results can more accurately obtain the desired indoor environmental parameters or human body parameters in the home data center.

In some embodiments, step 740 further comprises receiving, at the home data center, the detection from a fourth sensor worn by the human body. 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. One or more parameters of the human body can be known more accurately through the detection result of the fourth sensor worn by the human body, so that the desired indoor environment parameters or human body parameters can be obtained more accurately.

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

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

Sensor network

According to one embodiment of the invention, a plurality of integrated sensors form an integrated sensor network. The integrated sensor network and the family data center form a part of an indoor human living environment perception system. In an integrated sensor network, individual integrated sensors can communicate with each other or with a hub of the integrated sensor network. In some embodiments, the home data center may act as a central node of the sensor network. In an integrated sensor network, each integrated sensor is also able to communicate with a home data center. In some embodiments, under the coordination of the sub-center or the home data center of the integrated sensor network, a plurality of integrated sensors can work cooperatively to realize 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 an example of a sensor network. The sensor network includes a plurality of sensors and a data center. Multiple sensors are placed at various locations within the chamber, which may be integrated sensors as described above, or other types of sensors. In the following description, taking an integrated sensor as an example, it will be understood by those skilled in the art that other types of sensors are possible. The data center communicates in a wired or wireless manner with a plurality of sensors that perform detection of 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 sub-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-occupiable environment includes a plurality of rooms, for example: room a, room B, and room C; wherein the rooms a and C are respectively communicated with the room B. 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 room C. In one embodiment, the individual integrated sensors may communicate with each other even if disposed 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) that is capable of communicating with each integrated sensor in each room. In some embodiments, a hub may be included in each room, such as hub a, hub B, and hub C (not shown). The physical structure of the sub-center is similar to a data center and may be a device with computing capabilities. Decentration is not necessary. When the room is large or the number of integrated sensors in the room is large, the arrangement of the sub-centers can reduce the workload of the data center and is beneficial to reacting to the environmental change more quickly. In some embodiments, the integrated sensors work together through a sub-center or a data center without direct communication.

In some embodiments, the integrated sensors in the room may be located in an indoor facility such as a wall, floor, or ceiling, which may or may not be movable. Taking room a as an example, the integrated sensors may be disposed on multiple locations on the walls around room a to form a sensor network for room a, and in some embodiments, the integrated sensors may also be disposed on the ceiling and/or floor of room a (not shown). In some embodiments, smart wearable devices (e.g., smart band, smart watch, smart phone, etc.) in the room may also communicate with the data center.

In some embodiments, after forming a sensor network of one or more rooms, the data center may detect the indoor environment through multiple integrated sensors. Unlike the prior art, multiple integrated sensors in different locations enhance the results of environmental detection in at least two ways. On the one hand, the distribution of the indoor environment can be obtained by detecting from a plurality of positions, thereby improving the accuracy of detection. 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 room. Because a plurality of integrated sensors are arranged at different positions in a room, the integrated sensors can detect the temperature and the humidity of the respective positions. The data center can obtain the distribution of the temperature and the humidity according to the temperature and the humidity of each position, and the temperature and humidity conditions in the room can be reflected more accurately. In another aspect, integrated sensors at multiple locations are 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 cannot be detected by existing sensors.

In some embodiments, the integrated sensors may detect one or more environmental parameters of the indoor environment, and the data center may determine one environmental parameter based on a plurality of detection results and location information of one or more of the plurality of integrated sensors of the sensor network. For example, the data center may determine the temperature distribution within the room based on the temperatures detected within the room 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 body parameters of an indoor active person, and the data center may determine a body parameter jointly according to a plurality of detection results and position information of one or more integrated sensors of the sensor network. For example, the data center may determine a movement route of a person active in a room based on infrared information from a human body detected by a plurality of integrated sensors and locations of the plurality of integrated sensors.

In some embodiments, the data center may collectively determine a command issued by a person for indoor activity based on a plurality of detections of one or more of a plurality of integrated sensors of the sensor network. For example, the data center may determine that the person vocally uttered a command to adjust its ambient temperature based on infrared information from the person detected by one integrated sensor and voice information from the active person detected by another integrated sensor. Infrared information through integrated sensors is useful for determining the person issuing the command and its location. In some embodiments, the data center may adjust the indoor environment according to a plurality of detection results of one or more of the plurality of integrated sensors of the sensor network and/or a command of an indoor active person.

In some embodiments, the integrated sensor, when first communicating with the data center, may send the data center identity information and location information where it is located. In some embodiments, the integrated sensors need to register with the data center before they can join the sensor network of the data center. 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 located in a room A, a room B or a room C, wherein A in the sensor identity information A02 represents the room A, and the number 02 represents the sensor number 2. When the room information is included in the identity information of the integrated sensor, the location information thereof may be 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 mobile integrated sensor, the identity information includes the letter X. Such as X01, number 1 movable sensor.

In some embodiments, when the integrated sensor sends the detection result, the integrated sensor can simultaneously send the identity information and the location information to the data center. In particular a mobile sensor, which updates its location by sending location information. For a non-movable sensor, if the room facility in which it is located is movable, it will also re-register after changing location or transmit updated location information the next time it transmits the detection result.

In some embodiments, the position information of the integrated sensor includes an altitude. That is, the position information of the integrated sensor is three-dimensional position information. In existing indoor positioning, height information is usually not included. The three-dimensional position information is beneficial to establishing a more accurate environment 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 often seems difficult and difficult to locate accurately, which is important for the present invention. In order to solve this problem and reduce the positioning cost, in the present embodiment, the difficulty of positioning is reduced by using horizontal relative position information in units of rooms. The location point of the horizontal relative position is a preset point in the room, or a location integrated sensor on the preset point. Therefore, the three-dimensional space positioning relative to the coordinate origin is changed into the relative positioning of the predetermined point in the room, so that the walls and other auxiliary facilities of the room can be fully utilized, and the relative positioning difficulty is reduced. And the positions of all the integrated sensors relative to the coordinate origin can be easily calculated through the position relation between the preset point and the coordinate origin.

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

walls

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

walls

910 and 930 are connected to the wall 920, respectively. Each wall is connected with a ceiling 940 and a 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 the wall 920 and the wall 930 includes a corner 970 that is relatively convex compared to the wall 920 and the wall 930, and in some embodiments, the corner may have other shapes, such as: fan-shaped, etc. In some embodiments, the wall is not flat throughout. For example: the wall has a certain radian, concave-convex degree and the like.

In some embodiments, a plurality of integrated sensors are included in the room. 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, which is located in the center of the wall 920. Wall 930 includes integrated sensor 931 and integrated sensor 933, integrated sensor 931 being disposed at an interface of wall 930 and ceiling 940, integrated sensor 932 being located at an interface of wall 930 and floor 950, integrated sensor 933 being located at a center of wall 930. The ceiling 940 includes an integrated sensor 941, which is located at the center of the ceiling 940. The floor 950 includes an integrated sensor 951, which is located at the center of the floor 950. The partition 960 includes

integrated sensors

961 and 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 located at the center of the partition 960. Corner 970 includes

integrated sensors

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

In other embodiments, a different number of integrated sensors at different locations may be included on the wall 910, the wall 920, the wall 930, the ceiling 940, the floor 950, or the partition 960. For example: the integrated sensor 911 may also be located on a ceiling, or a wall, a ceiling, a floor, or a partition wall, etc. may be divided into a plurality of rectangles, one integrated sensor may be located at the center of each rectangle, or one integrated sensor may be located at each corner and center of each rectangle, etc.

In some embodiments, the sensor network includes integrated sensors 911-. These integrated sensors are all capable of communicating with a data center. In some embodiments, a smart device 980 may be held or worn by the user. The smart device 980 may also be capable of communicating with a data center.

FIG. 9B is a schematic diagram of an integrated sensor location in accordance with one embodiment of the present invention. As shown, taking the positioning of the integrated sensor 933 as an example, the predetermined point is the center point a of the floor of the room. The integrated sensor 933 does not have a positioning function, but supports input of 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 implemented by a worker setting the integrated sensor 933 with a hand-held laser rangefinder. The worker first measures the distance Z between the integrated sensor 933 and the ground using a laser range finder. At the predetermined point a, the distance X from the predetermined point a to the wall 930 is measured using a laser rangefinder, and the projected point B of the predetermined point a on the wall 930 is determined. Then a light blocking device is placed at the projection point B. Then, the distance Y between the projected point B of the integrated sensor 933 from the predetermined point a is measured on the projected point of the ground using the laser range finder. The measured distances 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. Where X and Y may be positive or negative numbers to indicate a direction with respect 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. This time, 2 predetermined points in the room can be adopted. The horizontal relative position is determined by measuring the distance between the projected point of the integrated sensor on the ground and two predetermined points. In this mode, the position of the integrated sensor can also be accurately calculated. The error is in the order of centimeters or less. Likewise, other integrated sensors within the room 900 may also be located in a similar manner. The method is convenient to operate and low in cost, and does not need more hardware support.

In some embodiments, the integrated sensor may include a locator. The positioning piece can realize accurate positioning by means of UWB, infrared, ultrasonic and the like. The room comprises a positioning device (e.g. a UWB base station or an infrared or ultrasonic emitting device) which is located at a positioning point. The positioning device can communicate with the positioning member in the integrated sensor, so that the positioning of the integrated sensor can be more easily achieved. However, the cost is relatively high. The degree of accuracy of this positioning is related to the technique used. In some cases, indoor centimeter-level positioning can be achieved by positioning elements.

An important application of the sensor network of the present invention is the accurate detection and regulation of indoor environments. According to one embodiment of the invention, an indoor space model can be established based on 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 sensed. After sensing the indoor environment, the data center can control indoor electric appliances and adjust the indoor environment.

Indoor space modeling

By indoor space modeling is meant modeling of an indoor space. In the prior art, the layout of the indoor space is generally constant. For example, there are several rooms in a house and the size and orientation of each room is rarely adjusted. However, for future smart homes, the layout of the indoor space can be easily changed. When the room layout is not changed, the data center may store an externally input indoor space model. However, when the layout of a room is frequently changed, it becomes very inconvenient to externally input an indoor space model each time. Therefore, if the layout of the room can be automatically obtained or updated when the layout of the room changes, so as to obtain the model of the indoor space, the method can be more suitable for the future intelligent house. This automatic method of obtaining and updating a room layout is known as modeling of an indoor space. The sensor network based on the invention can conveniently realize the indoor space modeling. The indoor layout information obtained by indoor space modeling is not necessarily completely accurate, but may already 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 in the figure, the spatial modeling method includes the following steps: at step 1010, location information for a plurality of integrated sensors is received from the plurality of integrated sensors. In the present embodiment, the spatial modeling is based on position information of a plurality of integrated sensors. As previously described, the data center can obtain the location of multiple integrated sensors in a sensor network deployed indoors. Indoor space information reflected by the positions of the integrated sensors is utilized to restore indoor space layout as accurately as possible, and indoor space modeling is achieved. As previously described, the integrated sensor may transmit its location information when it registers in the data center or when it transmits the detection results. If the position of the integrated sensor changes, the integrated sensor needs to register with a data center serving as a main node of the sensor network again; or when the detection result is sent again, the updating of the self position 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; the layout of the non-removable part of the house; location point information of additional placement, etc. For example, the data center may store the original house layout. Although the house layout has changed, the original room layout can still be helpful. And combining the position information of a plurality of integrated sensors to more easily obtain a new house layout and build an indoor space model. In, for example, future houses, houses are provided with only non-removable parts, and the layout of the division of rooms and the like is decided by the user himself. The data center may store the layout of the non-removable portions of the house. Combining the location information of multiple integrated sensors can more easily obtain new house layouts to build an indoor space model. Of course, additional anchor points may be provided in addition to the integrated sensors. The information of these positioning points is also useful for obtaining an indoor space model.

At step 1020, based on the grouping of the plurality of integrated sensors, a partition of the indoor space is obtained. In some embodiments, the data center may group information from multiple integrated sensor receivers, enabling multiple integrated sensors to be grouped such that a partition of the indoor space may be obtained. For example: all integrated sensors in the same room can be grouped together. In the embodiment shown in FIG. 8, the data center groups all integrated sensors into A, B and C groups based on the ID of each integrated sensor. If a movable integrated sensor is included in a room, it can be grouped individually. For groupings of non-movable integrated sensors, each group may correspond to a room. In some embodiments, further, the grouping of integrated sensors may include sub-groups 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 height belong to a ground subgroup; some of the highest height integrated sensors belong to the smallpox subgroup; a different height but horizontally aligned relative position represents a subset of walls. That is, information about the facilities in the room can be obtained for further groupings of integrated sensors within the same grouping. This information is useful for modeling the 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 based on their location characteristics, i.e., automatically obtain room layout information for the premises based on their location characteristics. 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, rectangular or multi-rectangular rooms are most common. There are also some rooms whose shape is irregular. For example, a room consisting of a cuboid and an arc surface. The data center stores these common room shapes, matches the common room shapes with the locations of the multiple integrated sensors, and selects the best matching solution as the room layout.

In some embodiments, the data center may also group integrated sensors based on zone divisions. In some embodiments, the area division may be performed based on a distance optimal solution to a predetermined point. In particular, a plurality of predetermined points are given in the area of a plurality of integrated sensors. The predetermined point setting scheme in which the sum of the distances from the integrated sensors around the predetermined points to the predetermined points is the minimum is the optimal solution. And for this optimal solution, each predetermined point corresponds to a room, thereby identifying the layout of the rooms.

In some embodiments, the zone partitioning may be based on a target recognition algorithm to find different zones to which it may belong from a plurality of integrated sensor locations that appear to be scattered. Target recognition algorithms based on deep learning, including but not limited to R-CNN, YOLO, or SSD. Existing integrated sensor arrangements and room layouts can be used as a data set to train the object recognition algorithm model. The trained target recognition algorithm model can be used for realizing the regional division of a plurality of integrated sensors, so that the layout of a room is recognized.

In some embodiments, the zone division may also be based on detection results of the plurality of integrated sensors. For integrated sensors in the same area, the detection results may be the same or similar. For example, integrated sensors include temperature probes; while the temperatures in the same room may be comparable. In this way, the temperature detection result 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 as to obtain the layout of the room.

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

As will be appreciated by those skilled in the art, the above zone division approaches may be used independently or in combination to arrive at a more accurate room layout. Of course, other area division methods in the prior art can be applied to this, independently or in combination with the above area division methods.

Since the arrangement of integrated sensors is generally sparse, a relatively rough room layout can be obtained. In order to solve the problem that the integrated sensors are sparse and cannot accurately reflect the conditions in the room, in some embodiments, the attribute information of the integrated sensors is added, so that the data center can obtain the local features of the positions of the integrated sensors. 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 upon registering with the data center or sending the detection results. The location attribute information reflects characteristics of the indoor space in the vicinity of the integrated sensor. The location attribute information includes a type field or a type field and a number field. The type field can indicate that the position of the type field is convex, concave, cambered surface, upright post and other characteristics. The number field may represent the distance of the outward or inward bulge, the radius of the arc, the arc of the post, etc. More accurate local features in the room can be obtained through the position attribute information. In some embodiments, the location attribute information may further include a functional region where the integrated sensor is located. For example: if the integrated sensor is located in a specific 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 facilities at or around the location of the integrated sensor. For example: the vicinity of the location of the integrated sensor includes a partition, a window, a door, etc., and the location attribute information indicates the type and rough location of the indoor facility. The information is beneficial to the establishment of the indoor space model.

At step 1030, size information for each of the zones is obtained based on the position information for 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, size information of the respective partitions, for example, the sizes of the respective rooms, may be further obtained. After the dimensions of the room are obtained, a model of the indoor space is also created. Thus, even if the indoor room layout changes, a new room layout can be easily obtained by using a plurality of integrated sensors disposed indoors, thereby realizing automatic updating. In some embodiments, such an automatic update capability is very useful for future premises where the room layout can change at any time according to the user's desires. Furthermore, by utilizing the indoor space modeling, the indoor environment can be more accurately adjusted, so that 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 shapes may be utilized. If the shape of the subarea is not matched, the shape of the subarea is determined by shape matching. After the shapes are matched, the size of the matched shape is determined. This size is the size of the partition. If the location attribute information of the integrated sensor is present, the matching shape and size can be adjusted using the location attribute information of the integrated sensor. In some embodiments, the size of a zone may be determined based on the location of integrated sensors located at the zone edges within the same zone. Likewise, the original layout of the house or the layout of the non-removable parts of the house may also assist in determining the size of the sub-area. After the dimensions of the partitions are determined, a model of the indoor space is also created.

Indoor space environment perception

By indoor space sensing is meant the accurate detection of one or more parameters of the indoor space environment. In the existing indoor environment detection, the detection result of a sensor at a certain point usually represents the environmental parameters of the whole space. However, such detection results are inaccurate, cannot reflect complex environmental changes of the whole space, and are not favorable for realizing more accurate environmental control. In some embodiments of the invention, based on the sensor network, with the help of spatial modeling, more accurate indoor space environment perception can be realized.

Fig. 11 is a method of sensing an indoor space environment according to one embodiment of the present invention. As shown in the figure, the method for sensing the indoor space environment comprises the following steps: 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, a sensor network of an indoor space is capable of detecting environmental parameters from multiple locations of the indoor space to a data center transmitter. In the data center, the environment parameters of multiple positions in the indoor space can be known by collecting the detection results.

At step 1120, indoor space modeling information is obtained using, at least in part, the position information of the plurality of integrated sensors. In some embodiments, the method for modeling an indoor space using an integrated sensor network as described above may be applied thereto for obtaining indoor space information. In some embodiments, other means may be utilized to obtain the indoor space model. The invention is not limited thereto. The location of the plurality of integrated sensors is 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 to an integrated sensor, which may affect later 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 the discrete points in the indoor space. In this step, the environmental parameters of the whole indoor space are established by using the environmental parameters of the discrete points, so as to realize the perception of the environment.

In some embodiments, obtaining 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 to divide molecular space. For example, fixed length, width and height; fixed volume, etc. At step 1132, a plurality of environmental parameters from the plurality of integrated sensors are used to assign a value to an environmental parameter of at least a portion of the subspace. If an integrated sensor is included in or adjacent to a subspace, the data center assigns values to the environmental parameters of the subspace using the measurements of the integrated sensor. Thus, the environmental parameters of the partial subspace are assigned; while the environment parameters of the partial subspace have not been assigned yet.

In step 1133, the data center assigns values to the remaining environment parameters of the subspace that has not been assigned yet, so as to implement environment sensing of the entire indoor space. There are a number of ways to assign values to these subspaces. In some embodiments, values are assigned to the environment parameters of these subspaces by interpolation. For example, two subspaces that have been assigned are separated by one or more subspaces, and then the environment parameters of these separated subspaces can 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, values are assigned to the environmental parameters of some of the subspaces. Taking the temperature field as an example, if a heat source exists in the indoor space, a flow field of heat occurs around the heat source. According to the temperature of the heat source, the air output and the size of the room, the shape of the heat flow field can be estimated approximately, and therefore the flow field distribution of the temperature can be estimated. According to the estimated temperature flow field distribution and the temperature of the subspace which is already assigned, the temperature of some subspaces can be assigned so that the temperature flow field distribution of the whole room is consistent with the estimated temperature flow field distribution. This enables assignment of environmental parameters to a molecular space. Based on the estimated temperature flow field, other subspaces can be assigned by using an interpolation method or a further field analysis method, so that the temperature field of the whole indoor space is obtained. For another example, for the electromagnetic signal intensity, the distribution of the electromagnetic signal intensity field can be roughly predicted according to the position of the signal source and the attenuation law of the electromagnetic signal in space. And combining the detection results of a plurality of indoor integrated sensors on the electromagnetic signal intensity, the evaluation on the electromagnetic signal intensity of the indoor partial subspace can be realized. 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 environmental parameters of at least a portion of the subspace based on location attribute information of the plurality of integrated sensors. As previously described, the integrated sensor may include location attribute information indicative of spatial characteristics of the integrated sensor or a location proximate thereto. 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. As another example, if the integrated sensor is located near a water supply in a toilet, the moisture assignments in the surrounding sub-space may be increased accordingly.

Those skilled in the art will appreciate that the above approaches may be used independently or in combination to more accurately assign values to the environment parameters of the respective subspaces. Of course, there are other ways to assign values to environment parameters of subspaces that have not yet been assigned. These means can be used independently or in combination with the above methods to sense the environment of the indoor space more accurately.

In step 1140, the data center may estimate the change in the environmental parameters of each subspace and update the environmental parameters of each subspace according to the estimated change. These subspaces include both subspaces with or adjacent to integrated sensors and subspaces that are not in direct contact with any integrated sensors.

In some embodiments, the data center predicts changes in environmental parameters for each subspace in the indoor space based on changes in the indoor space facility status. For example, if a door or window in a room is opened to allow gas exchange with the outside, the data center may predict that the temperature and humidity in the room will change. According to the outdoor temperature and humidity and the opening time of the door and the window, the data center can estimate the change of the temperature and the humidity of the indoor space. 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 estimates changes in environmental parameters of other sub-spaces in the indoor space based on changes in the state of the indoor space facility and subsequent changes in the environmental parameters from the plurality of integrated sensors. Although the updating is delayed slightly in speed, the accuracy of environment change perception can be guaranteed.

In some embodiments, the data center predicts changes in environmental parameters for each subspace in the indoor space in response to outdoor environmental change conditions. If the outdoor environment changes significantly, such as a large drop in temperature, then even without opening the door or window, a corresponding change in indoor temperature is expected. The data center can predict changes in 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.

Those skilled in the art will appreciate that the above approaches may be used independently or in combination to more accurately update the environment parameter assignments for the respective subspaces. Of course, there are other ways to update the environment parameter assignments for each subspace. These methods can be used independently or in combination with the above methods, thereby sensing the environmental change of the indoor space more precisely.

The sensor network of the present application will be further described below with reference to a specific room as an example, modeling an indoor space, recognizing a command issued by a user, and sensing an environment of the indoor space.

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

walls

1210, 1220, and 1230, a ceiling 1240, a floor 1250, and wall corners 1260, which are arranged in a similar manner to the embodiment of fig. 9 and therefore not described in further 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. Each integrated sensor is located in the center of each wall, ceiling or floor partition rectangle to form 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 the data center modeling the room space of the 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 the

walls

1220, 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 sensor-integrated grouping information 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 by the preset grouping information of the integrated sensors, so that the partition information of the indoor space may be obtained. For example: the indoor facilities are 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 sensors. For example: the location attribute information for the

integrated sensors

1222, 1223, 1231, and 1234 all appear to be located protruding outward, and the data center may derive that the room 1200 includes a corner 1260, which is located between the wall 1220 and the wall 1230.

In some embodiments, the room includes corners of a wall or the wall is a curved surface, etc., and the location attribute information may include a radian of a location where the integrated sensor is located, etc. In some embodiments, the location attribute information may further include a functional region 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 the indoor partition as a special function zone. In some embodiments, the location attribute information may also include indoor facilities around the location of the integrated sensor. 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 obtaining the spatial model of the room 1200, the data center may further sense the spatial environment in the room 1200 by using the sensor network. The data center divides the space of the room 1200 into a plurality of sub-spaces to facilitate estimating the environment of the other sub-spaces of the room based on the plurality of integrated sensors detecting environmental parameters of the different sub-spaces. As shown, the space of the room 1000 is divided equally into 27 subspaces, room01-room 27. As will be appreciated by those skilled in the art, the above division is merely exemplary, and the space of the room 1200 may also be divided into other numbers of subspaces.

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

The data center assigns values to the environmental parameters of at least a portion of the sub-spaces using the environmental parameters detected by the integrated sensors. For example: the subspace in direct contact with the integrated sensor may be assigned a value depending 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 integrated sensor detection results of contact therewith.

In some embodiments, environmental parameters in other subspaces not in contact with the integrated sensor may be interpolated to determine environmental parameters in their space. Taking the temperature field as an example, if the temperature detected by the integrated sensor in the eleventh subspace rom 11 is 10.0 ℃, and the temperature detected by the integrated sensor in the seventeenth subspace rom 17 is 11.0 ℃, the temperature in the fourteenth subspace rom 14 can be considered to be 10.5 ℃. Alternatively, taking the humidity field as an example, if the humidity detected by the integrated sensor in the fifth subspace rom 5 is 50%, and the humidity detected by the integrated sensor in the twenty-third subspace rom 23 is 48%, the humidity in the fourteenth subspace rom 14 can be considered to be 49%.

In some embodiments, the data center may predict the field distribution of the indoor space from a subspace at least partially determining the environmental parameter, and may determine the environmental parameter for a subspace for which other environmental parameters are not determined from the flow field distribution of the indoor space.

In some implementations, the location attributes of the indoor space or the indoor space facilities or their status may have an impact on the flow field of the indoor space. For example: a screen, a corner, or the like may have an influence on the temperature field of the indoor space, or the state of indoor equipment such as a door, a window, or the like may also have an influence on 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 environmental parameters for the environment of the affected subspace based on the location attribute information. The factors affecting the indoor environment will be described in detail below.

Fig. 13A and 13B are schematic diagrams illustrating changes in indoor environment according to an embodiment of the present application. Fig. 13A and 13B show the flow field distribution and the influence of the indoor environment change.

As shown, the room 1300 includes

walls

1310, 1320, and 1330, a ceiling 1340, and a floor 1350. The layout is the same as the above embodiment, and therefore, the description thereof is omitted. Wherein room 1300 further comprises

integrated sensors

1301 and 1308 arranged in the corners of room 1300. For example: the corner where the wall 1310 intersects the wall 1320 and the ceiling 1340, or the corner where the wall 1320 intersects the wall 1330 and the floor 1350. The room 1300 may also include

integrated sensors

1311, 1321, 1331, 1341 and 1351, which are centrally located on the walls, ceiling and floor, respectively. The

integrated sensors

1301, 1311, 1321, 1331, 1341 and 1351 together form a sensor network of the room 1300, and can detect the room 1300 and upload the detection result to the data center, so that a space model can be established for the room 1300 and environmental parameters in the space can be determined, which can refer to the embodiments in fig. 9, fig. 10 and fig. 11 and will not be described herein again.

In some embodiments, the data center may determine environmental parameters of the indoor space or a portion of the subspace based on the location attribute information of the integrated sensors. In some embodiments, the walls, ceilings, or floors of the room 1300 include special shapes that may affect the environment of the partial sub-spaces within the room 1300. In some embodiments, the room 1300 includes a particular area that may affect environmental parameters of the partial molecular space. For example: where a bathroom is included in the room 1300, the humidity in some of the sub-spaces may be high; or the room 1300 includes a kitchen, the electromagnetic intensity in a portion of the subspace may be higher. In some embodiments, the room 1300 includes indoor facilities that may affect the environment in the molecular space. For example: windows and doors may affect the temperature in the molecular space.

In some embodiments, the wall 1310 may include a door 1313 and the wall 1330 may include a window 1332, wherein the door 1313 and the window 1332 may have an effect on the environment within the room 1300. Wherein the data center can predict the environmental parameters of the room 1300 or each sub-space according to the state change of the door 1313 and/or the window 1332. For example: the door 1313 and window 1332 are moved from a closed position to an open position, and the data center may be turned down or up by a certain amount (e.g., 2 c, 3 c, 5 c, etc.) for the temperature in the door or window contacting sub-space or the sub-space between the two.

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

In some embodiments, the data center may also estimate the environmental parameter or the change of the environmental parameter of the indoor space or each sub-space according to the outdoor environment or the outdoor environment change state. In some embodiments, the outdoor environment may have an effect on the indoor environment (e.g., temperature, humidity, etc.) during different seasons. For example: the outdoor temperature is relatively high in summer and relatively low in winter, and the temperature in a room is greatly influenced; or the rainwater is more in summer and is drier in winter, so that the humidity in the room is greatly influenced. In some embodiments, there is also an effect on the indoor environment at different times of the day outdoors. For example: the temperature is lower in the morning and evening, and the temperature is higher in the noon, so that the indoor temperature is greatly influenced. In some embodiments, the outdoor environment is subject to large changes, which can have an impact on the indoor environment. For example: sudden precipitation can have a large effect on the humidity in the room. In some embodiments, the data center may also receive a weather forecast 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.

Conditioning of indoor environment

The regulation of the indoor environment means that the indoor environment is regulated by starting indoor electric appliances. The regulation of the indoor environment includes passive regulation and active regulation. Passive regulation is the usual way: when the indoor environment changes or receives an instruction of a user, the indoor electric appliance is started to regulate the indoor environment. Active regulation is a unique regulation mode: according to the possible change trend of the indoor environment or the condition of users, the indoor environment is actively changed, so that the human living environment is more friendly and the people can live more comfortably.

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

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

At step 1430, the environmental conditioning devices are activated to condition the indoor environment to achieve the desired indoor environment. In the indoor space, one or more climate control devices are arranged. Different environmental conditioning means may be used for different environmental parameters. These environmental conditioning devices include, but are not limited to: air-conditioning, fan, electric heater, humidifier, signal amplifier etc. different kinds and quantity of electrical apparatus or facilities. By activating these appliances or facilities, adjustments to the indoor environmental parameters can be achieved. In some embodiments, the number and distribution of the environmental conditioning devices within a room are arranged so that the data center can learn their effect on the variation of the environmental parameters of the various subspaces to achieve accurate conditioning of the environment. Taking temperature as an example, the room comprises a plurality of air-conditioning or air-conditioning outlets and heaters distributed on various walls, so that the temperature of each subspace can be accurately adjusted.

For passive regulation, the method of the invention allows for more precise environmental regulation than in the prior art. For example, the comfortable temperature of the indoor environment is 21 ± 2 ℃. To ensure occupant comfort, the temperature of all occupant-related sub-spaces is set at 21 ± 2 ℃, and the data center maintains the temperature of these sub-spaces. Through the perception of the indoor space environment, the data center found that the temperature of the sub-space near the doors and windows in the indoor space was at 23 ℃ while the temperature of the sub-space of the bed located farther from the doors and windows in the indoor space reached 25 ℃. The data center activates the air conditioner or air conditioner outlet near the bed, reduces the temperature of the subspace of the bed, and controls the temperature around the bed within a comfortable range for the human body. As can be seen from such an example, through spatial environment sensing, 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 multiple active persons indoors through, for example, an integrated sensor, and can respectively adjust the environmental parameters of the sub-spaces where the multiple persons are located according to the commands, so that the multiple persons in indoor activities can all enjoy comfortable indoor environment. For example, indoors includes both men and women: a and B, wherein A prefers a little lower temperature; while B prefers a little higher temperature. When both A and B people are in the same room, A and B may issue different commands, the command for A is that the temperature is reduced to 16 ℃; and B is commanded to a temperature increase to 25 ℃. In the prior art, such commands cannot be executed. In the case of the present invention, if there is a certain separation between a and B, in different subspaces; the data center may then meet such a demand by fine tuning the temperature of each of the a and B subspaces. The data center can reduce the temperature of the subspace A through an air conditioner; and raising the temperature of the subspace where the B is located by the heater. Thus, both A and B can enjoy comfortable environments, and the comfort of the whole indoor living environment is improved.

One feature of the indoor environment adjustment of the present invention is active adjustment, that is, the environment can be actively adjusted without changing the environment or receiving a command from a user, thereby further improving the comfort of living. This is further illustrated below by a few examples.

In some embodiments, the data center may estimate changes in environmental parameters of each subspace in the indoor space based on changes in the state of the indoor facility, and actively adjust the indoor environment based on the estimated changes in the environmental parameters of each subspace. For example, if a door or window in a room is changed from a closed state to an open state, the temperature in the room may not be changed immediately. After detecting the state change of the door or window of the indoor facility, the data center can estimate that the indoor temperature will rise or fall according to the outdoor temperature, the wind speed and the like. Further, the data center may activate the climate control device to adjust the temperature of each sub-space to maintain the indoor environment within a comfortable range. In other words, the temperature in the room does not change while the door or window is opened for ventilation.

In some embodiments, the indoor facility where the change of state occurs may be an environmental conditioning device. After the environment adjusting device is started, the data center can estimate the environmental parameters of each indoor subspace. For example: taking fig. 13 as an example, the initial temperature of each sub-space in the room is 20 ℃, the air conditioner at the wall 1310 is turned on to cool, the data center estimates the temperature of the sub-space near the wall 1310 according to the power and wind direction of the air conditioner may be 15 ℃, the temperature of the sub-space near the wall 1330 may be 18 ℃, and the temperature of the sub-space therebetween may be 16 ℃. Further, the data center may activate 1310 the heating devices of the sub-spaces by itself, and increase 1310 the temperature of the sub-spaces, thereby maintaining the temperature of each sub-space in a comfortable environment.

If one or more persons exist indoors, the data center can actively adjust the environmental parameters of the subspaces around the persons according to the presence or absence of the persons, the identities, activities and the like of the persons and enable the human-living environment to be more humanized.

In some embodiments, multiple integrated sensors within room 1300 may detect one or more persons active within the room. The data center can know that someone is now in the room, and know the number and location of people. The data center can actively adjust the illumination of each subspace which can be seen by people, so that the people can comfortably and clearly see the indoor conditions.

In some embodiments, multiple integrated sensors in room 1300 may detect one or more body parameters of an indoor activity, and the data center may adjust the environment of the subspace surrounding the indoor active person based on the detection. Taking temperature as an example, if the data center finds that the body temperature of one of a plurality of people who move indoors is increased (no matter the people move or eat hot food and the like), the data center can turn on an air conditioner to reduce the temperature of a subspace where the people with high body temperature are located, so that the people feel comfortable; while keeping the temperature of the subspace around the other person unchanged.

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

walls

1310 and 1320, and the data center can adjust the environment of its surrounding subspace according to user a's habits, adjusting the temperature to the range of user a's habits.

In some embodiments, the integrated sensor identifies activities of the indoor active person, and the data center may actively adjust the environmental parameters of the subspace near the indoor active person according to the identification result. For example, when it is recognized that someone is sleeping in the room (e.g., lying down in bed is inactive for more than a predetermined time), the temperature of the subspace around it is appropriately raised. For another example, when it is recognized that someone is doing indoor exercise (e.g., running, exercising, etc.), the oxygen content of the subspace around the person is appropriately increased.

The invention has another characteristic that the energy conservation and environmental protection can be realized on the premise of not reducing the comfort level of the human living environment through the accurate adjustment of the indoor environment, thereby being more in line with the future development direction of home furnishing.

In some embodiments, the data center turns the environmental parameter adjustment device on or off in response to detection of one or more persons in the indoor activity. For example, when the data center identifies one or more people in the room, it activates the signal amplifiers in its surrounding subspace so that the one or more people can enjoy the wireless signal. If there is no person in the room or no person in the subspace for the surroundings, the data center turns off the signal amplifier to save energy. Likewise, this may also be the case for temperature. When the data center recognizes that the indoor people are in a sleeping state, the data center can turn off the air conditioner or the heater and other environment temperature adjusting devices for the rest subspaces except for the subspace around the people for properly increasing the temperature to ensure the comfort level of the human living environment, thereby saving energy. The invention can realize fine adjustment of indoor environment, thereby saving energy to the maximum extent and realizing green home furnishing.

In some embodiments, even when adjusting the indoor environment, the data center estimates, based on the desired indoor environment, a number of environmental conditioning devices and their corresponding powers that need to be activated to adjust the environment of each of the sub-spaces within the room prior to activating the environmental conditioning devices.

In some embodiments, the data center may activate the environmental conditioning devices in a manner that estimates the least total energy consumed by the plurality of environmental conditioning devices that need to be activated to condition the indoor environment, to facilitate energy savings. For example: when the location of user a needs to be cooled, the user a may use the cooling device of wall 1310, the cooling device of wall 1320, or both. Through the energy consumption comparison, the data center selects to control the cooling devices of wall 1310 to cool down the subspace around the data center, and does not start the cooling devices 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.

Comfort is also a consideration in some embodiments. The data center can also estimate that the indoor environment needs to be adjusted, and the environment adjusting devices are started in a mode that the adjusting speed of the environment adjusting devices is the fastest, so that the user experience is increased. For example: when the location of the user B needs to be warmed, the heating devices near the wall 1330 and the floor 1350 are controlled to heat the subspace around the user B at the same time, so as to quickly raise the temperature of the location of the user B to the required temperature range.

In the above part of this document, the solution of the invention is illustrated by way of a number of embodiments by integrating sensors, sensor networks, indoor space modeling, indoor space environment sensing and indoor space environment conditioning. It will be appreciated by those skilled in the art that there are many possible variations to the technical solution of the invention, which variations still fall within the scope of the invention.

The technical solution of the present invention is further explained below by two variations of the technical solution of the present 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. Multiple sensors can be positioned relative to multiple modeling elements, at lower cost, and with greater flexibility.

FIG. 15 is a schematic diagram of a structure of an indoor space modeling component according to one embodiment of the present application. As shown, the modeling component 1500 of the indoor space includes a processor 1510, a positioning component 1520, and a communication module 1530; the processor 1510 is electrically connected to the positioning element 1520 and the communication module 1530. The positioning element 1520 is used to determine the position of the modeling element, and in some embodiments, the positioning element may perform indoor spatial positioning by UWB, Wi-Fi, RFID, infrared, or ultrasound, among others. In some embodiments, the communications module 1530 is used to communicate with a home data center or a data center of a room hub.

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

In some embodiments, the modeling component may also include an input display 1560 coupled to the processor that may be used to input information to 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 a modeling element-based indoor space modeling process according to an embodiment of the invention. As shown, at step 1610, the data center obtains location information for each modeling component from a plurality of modeling components. As mentioned before, the positioning element of the modelling element enables indoor space positioning. The data center receives the spatial positioning information of its positioning element from the modeling element and can obtain the position of the modeling element.

To facilitate positioning, in some embodiments, the position information of the modeling element includes height and/or horizontal relative position information. In some embodiments, the horizontal relative position may be a relative position with respect to a location point within the room. For spatial localization, determining height is sometimes difficult. Spatial localization can be simplified and the results more accurate by arranging the modeling elements at a fixed height or heights and obtaining horizontal relative position information using only the localization elements. In some embodiments, the positioning manner used by the integrated sensor in the foregoing embodiments with respect to the positioning point in the room is also applicable here, and is not described here again.

At step 1620, the data center may obtain partition information for the indoor space from the grouping of the plurality of modeling elements. In some embodiments, the data center may receive grouping information for a plurality of modeling elements from the modeling element. The grouping of the modeling elements can be realized by utilizing the grouping information, and then the partition of the indoor space is obtained. Similar to the integrated sensor embodiment, in some embodiments, the plurality of modeling elements may be grouped by shape matching. For example: a plurality of modeling elements that are grouped into a rectangular shape are grouped. In some embodiments, the grouping of modeling elements may be implemented by a clustering algorithm.

At 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 multiple modeling elements so that characteristic information for indoor space partitions may be derived. In some embodiments, the location attribute information includes, but is not limited to: the radian of the position of the modeling element, the convexity and concavity of the position of the modeling element, the functional area to which the position of the modeling element belongs, and indoor facilities around the position of the modeling element.

At step 1640, multiple locations of multiple sensors within the room are calibrated in the indoor space model. For spatial context sensing and spatial context control, it is necessary to know the position of the sensor in the spatial model, which does not include the positioning element.

In some embodiments, the plurality of sensors also include a positioning element, such as by UWB, Wi-Fi, RFID, infrared, or ultrasonic, for example, to enable indoor space positioning. In this step, the position calibration of the sensor can be realized according to the positions received from the plurality of sensors.

In some embodiments, the plurality of sensors do not include positioning elements to reduce costs. 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 to place a sensor 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 the sensor at the midpoint between modeling elements # 1 and # 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 according to the name of the sensor, so that the position of the sensor can be calibrated on the space model.

In some more complex examples, the plurality of sensors includes RFID tags. The plurality of modeling elements also includes RFID tags. The RFID label 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. By calibrating the return times and signal strengths of the RFIDs of the plurality of modeling elements, the position of the plurality of sensors relative to the modeling elements can be known. The technology has the action distance of several meters to dozens of meters, and can meet the requirement of indoor positioning. The information of centimeter-level positioning accuracy can be obtained within a few milliseconds through the RFID scanner, the transmission range is large, and the cost is low. Such a method is also applicable to infrared, Wi-Fi, ultrasonic, and the like.

Therefore, the positions of the sensors are calibrated on the indoor space model, the combination of the sensor network and the space model is realized, the subsequent 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 human-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 special, enabling indoor localization by its own localization element without the help of other sensors. While another type of sensor, although also having a positioning element, does not perform positioning itself and must rely on other sensors to perform positioning.

Spatial modeling with 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 detection 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.

FIGS. 17A-17D are schematic structural views of an indoor facility 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 kick; the indoor facility shown in fig. 17C is a floor; and the indoor facility shown in fig. 17D is a ceiling. As shown, these facilities include a processor 1710, a pointing element 1720, and a communication module 1730; the processor 1710 is electrically connected to the positioning element 1720 and the communication module 1730. Positioning element 1720 is used to determine the position of the modeling element, and in some embodiments, the positioning element may 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 hub.

Fig. 18 is a schematic view illustrating a process of modeling an indoor space based on an indoor facility according to an embodiment of the present invention. As shown, the data center obtains location information for each of the indoor facilities from the plurality of indoor facilities at step 1810. As previously mentioned, one or more positioning elements of a plurality of indoor facilities enable indoor space positioning. The data center receives the spatial location information of its location element from the indoor facility and can obtain the location of the indoor facility.

To facilitate location, in some embodiments, the location information of the indoor facility includes height and/or horizontal relative location information. In some embodiments, the horizontal relative position may be a relative position with respect to a location point within the room. For spatial localization, determining height is sometimes difficult. Spatial localization can be simplified and the results more accurate by arranging the indoor facility at a fixed height or heights and obtaining horizontal relative position information using only the localization elements. Since the number of positioning elements used in indoor facilities is small, there is a high demand for positioning accuracy. In some embodiments, the positioning element is a high-precision positioning technology such as UWB, infrared, ultrasonic, and the like, providing a positioning precision on the order of centimeters or more.

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 divide 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 kick. The respective indoor facilities are thus used to divide the respective areas. Other indoor settings, such as floors, ceilings, etc., are also divided into individual rooms.

At step 1830, the data center obtains dimensional information for the indoor space zone to form an indoor space model. In some embodiments, the data center receives location attribute information from a plurality of indoor facilities so that characteristic information of indoor space partitions can be derived. In some embodiments, the location attribute information includes, but is not limited to: the radian of the position of the indoor facility, the convexity and concavity of the position of the indoor facility, the functional area to which the indoor facility belongs, and the indoor facilities around the position of the indoor facility.

At step 1840, a plurality of locations of a plurality of sensors within a room are calibrated in an indoor space model. For spatial context sensing and spatial context control, it is necessary to know the position of the sensor in the spatial model, which does not include the positioning element.

In some embodiments, the plurality of sensors do not include positioning elements to reduce costs. The plurality of sensors are installed in the indoor facility, and the positions of the sensors relative to the positioning elements of the indoor facility are fixed, so that the position calibration in the space model can be directly realized. For example, the designation of each sensor indicates its position relative to a positioning element of the indoor facility. For example, sensor a12 represents sensor number 12 in the interior installation wall a. The data center stores a table of the specific locations of the various sensors in the various indoor facilities. The data center can see by looking up the table that sensor number 12 is the sensor located 45 deg. above and to the right of the locating element in wall a, 40 cm. Thus, the data center may calibrate the location of the A12 sensor in the indoor space model. For another example, B67 denotes the No. 67 sensor in the indoor installation floor B. The data center can understand by looking up the table, that is, the location of sensor number 67 is at the (150, -300) cm coordinates with the location element of floor B as the origin. Thus, the data center may calibrate the location of the B67 sensor in the indoor space model. In this way, 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 may also become a sensor, becoming part of the sensor network.

The above embodiments are provided only for illustrating the present invention and not for limiting the present invention, and those skilled in the art can make various changes and modifications without departing from the scope of the present invention, and therefore, all equivalent technical solutions should also fall within the scope of the present disclosure.

Claims

1. A method of indoor space reconstruction, comprising:

receiving location information of a plurality of indoor facilities from the plurality of indoor facilities;

obtaining partition information of an indoor space based on the location information of the plurality of indoor facilities;

obtaining size information of the partition; and

calibrating a plurality of positions of a plurality of sensors in a room;

wherein the indoor facility includes one or more locators, wherein a location of the indoor facility is determined according to a location of the locator and a size of the indoor facility.

2. The method of claim 1, wherein the indoor facility is one or more of a movable or non-movable wall, floor, or ceiling.

3. The method of claim 1, wherein the positioning member is configured to be positioned utilizing UWB, infrared, or ultrasonic means.

4. The method of claim 1, further comprising receiving location attribute information from the plurality of indoor facilities.

5. The method of claim 4, further comprising obtaining characteristic information of the partition of indoor space based at least in part on location attribute information of the plurality of indoor facilities.

6. The method of claim 4, wherein the location attribute information comprises one or more of an arc degree, a convexity, a functional region, and an indoor facility around the location.

7. The method of claim 4, wherein the sensor in the indoor facility is positionable relative to the locator.

8. A system for modeling an indoor space, comprising:

a plurality of indoor facilities distributed in the indoor space; and

a data center in communication with the plurality of indoor facilities;

wherein the data center is configured to obtain size information for a partition based on a grouping of the plurality of indoor facilities based on location information for the plurality of indoor facilities, and to calibrate a plurality of locations for a plurality of sensors indoors;

wherein the indoor facility comprises one or more positioning parts, and the data center determines the position of the indoor facility according to the position of the positioning part and the size of the indoor facility.

9. The system of claim 8, wherein the locator is configured to be located utilizing UWB, infrared, or ultrasonic means.

10. The system of claim 8, wherein the data center is configured to receive location attribute information from the plurality of indoor facilities.

11. The system of claim 10, wherein the data center is configured to obtain characteristic information for the partition of indoor space based at least in part on location attribute information for the plurality of indoor facilities.

12. The system of claim 8, wherein the sensor does not include a positioning device.