CN117706951A - Intelligent household safety early warning system based on artificial intelligence - Google Patents
Intelligent household safety early warning system based on artificial intelligence Download PDFInfo
- Publication number
- CN117706951A CN117706951A CN202311779738.8A CN202311779738A CN117706951A CN 117706951 A CN117706951 A CN 117706951A CN 202311779738 A CN202311779738 A CN 202311779738A CN 117706951 A CN117706951 A CN 117706951A
- Authority
- CN
- China
- Prior art keywords
- module
- early warning
- warning system
- intelligent household
- artificial intelligence
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 18
- 238000005070 sampling Methods 0.000 claims abstract description 32
- 238000012545 processing Methods 0.000 claims abstract description 28
- 230000004044 response Effects 0.000 claims abstract description 21
- 238000012544 monitoring process Methods 0.000 claims abstract description 14
- 238000004458 analytical method Methods 0.000 claims description 16
- 230000004913 activation Effects 0.000 claims description 12
- 230000006870 function Effects 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000000034 method Methods 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 8
- 230000006698 induction Effects 0.000 claims description 7
- 239000000779 smoke Substances 0.000 claims description 7
- 230000005540 biological transmission Effects 0.000 claims description 4
- 238000004891 communication Methods 0.000 claims description 4
- 238000013528 artificial neural network Methods 0.000 claims description 3
- 238000010411 cooking Methods 0.000 claims description 3
- 230000007613 environmental effect Effects 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 description 6
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000010485 coping Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000030279 gene silencing Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Alarm Systems (AREA)
Abstract
The invention discloses an intelligent home safety early warning system based on artificial intelligence, which comprises a user side, a cloud alarm module and a safety early warning system, wherein the safety early warning system comprises a real-time monitoring module, an indoor environment sampling module, a data processing and analyzing module, an early warning module A, a message response module, a control module, a human body sensing module and a parameter setting input storage module. According to the intelligent household appliance control system, the intelligent household appliance can be automatically controlled to be started under the condition that the indoor environment exceeds a preset value and no response is made, so that the condition that people fall asleep at night and are uncomfortable due to the environment can be effectively reduced, in addition, when no people exceed the set value in a kitchen, the intelligent gas stove can be automatically controlled to be closed, the risk of fire can be effectively reduced, and meanwhile, when the sign of the fire occurs, information is timely transmitted to a fire alarm answering center to be processed, and the loss caused by the fire can be effectively reduced.
Description
Technical Field
The invention relates to the technical field of intelligent household safety early warning systems, in particular to an intelligent household safety early warning system based on artificial intelligence.
Background
The intelligent home is a management system for building high-efficiency residential facilities and family schedule matters by integrating the facilities related to home life by using a comprehensive wiring technology, a network communication technology, a security technology, an automatic control technology and an audio-video technology as a platform; the existing intelligent home lacks a safety early warning function in the use process, particularly, in a kitchen, the situation that a person forgets to turn off fire to cause fire occurs exists, and when the sign of the fire occurs, the person cannot be warned and reminded in time; in addition, when the indoor temperature is higher, personnel can not be warned in time and the electrical equipment is automatically controlled to be closed or opened, and particularly when the personnel fall asleep at night, discomfort caused by the overhigh indoor temperature exists for the personnel, the use requirement can not be met, and the conditions are combined, so that an intelligent household safety early warning system based on artificial intelligence is provided.
Disclosure of Invention
Based on the technical problems in the background technology, the invention provides an intelligent household safety early warning system based on artificial intelligence.
The invention provides an intelligent home safety early warning system based on artificial intelligence, which comprises a user side, a cloud alarm module and a safety early warning system, wherein the safety early warning system comprises a real-time monitoring module, an indoor environment sampling module, a data processing analysis module, an early warning module A, a message response module, a control module, a human body induction module and a parameter setting input storage module;
the user terminal comprises an intelligent household appliance and a mobile phone APP, wherein the intelligent household appliance is connected with the real-time monitoring module and the control module, the mobile phone APP is connected with the message response module and the early warning module A, and the cloud warning module is connected with the early warning module A;
the data processing and analyzing module is connected with the indoor environment sampling module, the real-time monitoring module, the early warning module A, the message response module, the control module, the human body sensing module and the parameter setting input storage module.
Preferably, the intelligent household appliance comprises various electric appliances such as an illuminating lamp, an air conditioner, a warmer, a humidifier, an intelligent gas stove, a curtain and the like.
Preferably, the indoor environment sampling module comprises a temperature sensor, a humidity sensor, a gas sensor and the like, and is used for sampling indoor temperature, humidity, smoke conditions and the like, when the indoor environment sampling module samples, the sampling module in the indoor environment sampling module sends corresponding instructions to the sensors through communication interfaces with the sensors so as to acquire data acquired by the sensors, and the sampling module can send reading instructions to the sensors periodically or on demand so as to acquire latest environmental parameter data.
Preferably, a timing module is built in the human body sensing module and is used for timing the interval time of no person after the intelligent gas stove is started and transmitting the time to the data processing and analyzing module, the standard time when the person leaves is set to be 15-20min by the timing module, and the data processing and analyzing module adopts the formula:the time of the timing module is called and processed, wherein +.>For cooking time and locating a standard time after leaving the person, when +.>At the same time, the normal time is indicated, the monitoring is continued, when +.>And when the time exceeds the standard time, the early warning module A is required to remind personnel and the flameout treatment is controlled by the control module.
Preferably, a signal sending module and a voice broadcasting module are arranged in the early warning module A, the voice broadcasting module directly alarms and reminds personnel in a voice mode, and the information sending module is used for sending early warning notices to the mobile phone APP.
Preferably, the cloud alarm module is connected with an external fire alarm answering center, and the information transmission mode is as follows: the data of the cloud alarm module is processed and forwarded through the cloud server, and early-warning data information is sent to a fire alarm answering center, and the fire alarm answering center provides a system with an alarm information receiving function, and the system can receive alarm data from the cloud server and correspondingly process and distribute the alarm data to corresponding personnel.
Preferably, the parameter input storage module is used for inputting and storing parameter information of the intelligent household electrical appliance and standard parameter information of indoor environment.
Preferably, the data processing and analyzing module is used for storing data, and the data processing and analyzing module analyzes the gas smoke concentration data measured by the gas sensor, and can judge whether the sign of fire exists through analysis, and an algorithm used in the analysis is a neural network identification algorithm, and the application formula comprises: calculation of input layer to hidden layer: z_h=w_hx+b_ha_h=f (z_h); calculation of hidden layer to output layer: z_o=w_oa_h+b_oa_o=f (z_o), wherein w_h and w_o are weight matrices of the hidden layer and the output layer, b_h and b_o are corresponding bias terms, f is an activation function, x is input data, z_h is a weighted sum of the hidden layer, a_h is an activation value of the hidden layer, z_o is a weighted sum of the output layer, a_o is an activation value of the output layer; gradient calculation from output layer to hidden layer: δ_o= (a_o-y) f' (z_o); gradient computation of hidden layer to input layer: delta_h= (w_o≡δ_o) ×f '(z_h), where delta_o is the error of the output layer, y is the actual value, f' is the derivative of the activation function, and T represents the transpose of the matrix; updating weights and biases of the hidden layer to the output layer: Δw_o= - α δ_o a_h Δb_o= - α δ_o; updating weights and biases of input layer to hidden layer: Δw_h= - α x δ_h= - α x δ_h where Δw_o and Δw_h are adjustment amounts of weights, Δb_o and Δb_h are adjustment amounts of offsets, α is a learning rate, and x is input data.
Preferably, the message response module sets the standard time for the personnel not to respond to be 10-15min.
Compared with the prior art, the invention has the beneficial effects that:
1. the indoor environment sampling module, the real-time monitoring module, the data processing and analyzing module, the early warning module A and the message response module are matched, so that when the indoor environment temperature is not in the standard range and people exist indoors, the intelligent household appliance can be automatically and timely warned and reminded, and the intelligent household appliance is automatically controlled to be started when the people do not respond, the condition that the people fall asleep at night due to the environment can be effectively reduced, and the use comfort of the people can be improved;
2. the human body induction module, the early warning module, the message response module, the cloud warning module, the indoor environment sampling module and the data processing analysis module are matched, so that when no one is in a kitchen for exceeding a preset time, the intelligent gas stove is automatically controlled to be closed during working, the risk of fire can be effectively reduced, in addition, when a sign of fire occurs, a person can be automatically and timely warned and reminded, and when no one is detected in a room, information is transmitted to the fire answering center for processing, and the loss caused by the fire can be effectively reduced;
according to the intelligent household appliance control system, the intelligent household appliance can be automatically controlled to be started under the condition that the indoor environment exceeds a preset value and no response is made, so that the condition that people fall asleep at night and are uncomfortable due to the environment can be effectively reduced, in addition, when no people exceed the set value in a kitchen, the intelligent gas stove can be automatically controlled to be closed, the risk of fire can be effectively reduced, and meanwhile, when the sign of the fire occurs, information is timely transmitted to a fire alarm answering center to be processed, and the loss caused by the fire can be effectively reduced.
Drawings
Fig. 1 is a system block diagram of an intelligent home safety early warning system based on artificial intelligence.
Detailed Description
The invention is further illustrated below in connection with specific embodiments.
Examples
Referring to fig. 1, the embodiment provides an intelligent home safety early warning system based on artificial intelligence, which comprises a user side, a cloud alarm module and a safety early warning system, wherein the safety early warning system comprises a real-time monitoring module, an indoor environment sampling module, a data processing and analyzing module, an early warning module a, a message response module, a control module, a human body sensing module and a parameter setting input storage module, wherein a signal sending module and a voice broadcasting module are arranged in the early warning module a, the voice broadcasting module directly alarms and reminds personnel in a voice mode, and the parameter input storage module is used for inputting and storing parameter information of intelligent home appliances and standard parameter information of indoor environments;
the user side includes intelligent household electrical appliances and cell-phone APP, information transmission module is used for sending early warning notice to cell-phone APP, intelligent household electrical appliances include multiple electrical equipment such as light, air conditioner, room heater, humidifier, intelligent gas-cooker and (window) curtain, intelligent household electrical appliances are connected with real-time supervision module and control module, cell-phone APP is connected with message response module and early warning module A, high in the clouds alarm module is connected with early warning module A, wherein high in the clouds alarm module is connected with outside fire alarm answering center, its mode of transmission information is as follows: the data of the cloud alarm module is processed and forwarded through the cloud server, and early-warning data information is sent to a fire alarm answering center, and the fire alarm answering center provides a system with an alarm information receiving function, and the system can receive alarm data from the cloud server and correspondingly process and distribute the alarm data to corresponding personnel;
the system comprises a data processing analysis module, an indoor environment sampling module, a real-time monitoring module, an early warning module A, a message response module, a control module, a human body sensing module and a parameter setting input storage module, wherein the composition of the indoor environment sampling module comprises a temperature sensor, a humidity sensor, a gas sensor and the like, the indoor environment sampling module is used for sampling indoor temperature, humidity, smoke conditions and the like, when the indoor environment sampling module is used for sampling, the sampling module in the indoor environment sampling module sends corresponding instructions to the sensors through communication interfaces with the sensors so as to acquire data acquired by the sensors, the sampling module can periodically or on demand send reading instructions to the sensors so as to acquire the latest environmental parameter data, and the standard time of no response of personnel is set to be 10-15min;
the human body induction module is internally provided with a timing module which is used for timing the interval time of no person after the intelligent gas stove is started and transmitting the time to the data processing and analyzing module, the standard time of the timing module when the person leaves is set to be 15-20min, and the data processing and analyzing module adopts the formula:the time of the timing module is called and processed, wherein +.>For cooking time and locating a standard time after leaving the person, when +.>At the same time, the normal time is indicated, the monitoring is continued, when +.>When the time exceeds the standard time, the early warning module A is required to remind personnel and the flameout treatment is controlled by the control module;
the data processing and analyzing module can be used for storing data, and the data processing and analyzing module analyzes the gas smoke concentration data measured by the gas sensor, and can judge whether the sign of fire exists or not through analysis, and an algorithm used in the analysis is a neural network identification algorithm, and the application formula comprises the following steps: calculation of input layer to hidden layer: z_h=w_hx+b_ha_h=f (z_h); calculation of hidden layer to output layer: z_o=w_oa_h+b_oa_o=f (z_o), wherein w_h and w_o are weight matrices of the hidden layer and the output layer, b_h and b_o are corresponding bias terms, f is an activation function, x is input data, z_h is a weighted sum of the hidden layer, a_h is an activation value of the hidden layer, z_o is a weighted sum of the output layer, a_o is an activation value of the output layer; gradient calculation from output layer to hidden layer: δ_o= (a_o-y) f' (z_o); gradient computation of hidden layer to input layer: delta_h= (w_o≡δ_o) ×f '(z_h), where delta_o is the error of the output layer, y is the actual value, f' is the derivative of the activation function, and T represents the transpose of the matrix; updating weights and biases of the hidden layer to the output layer: Δw_o= - α δ_o a_h Δb_o= - α δ_o; updating weights and biases of input layer to hidden layer: Δw_h= - α x δ_h x Δb_h= - α x δ_h, wherein Δw_o and Δw_h are adjustment amounts of weights, Δb_o and Δb_h are adjustment amounts of offsets, α is a learning rate, and x is input data; according to the intelligent household appliance control system, the intelligent household appliance can be automatically controlled to be started under the condition that the indoor environment exceeds a preset value and no response is made, so that the condition that people fall asleep at night and are uncomfortable due to the environment can be effectively reduced, in addition, when no people exceed the set value in a kitchen, the intelligent gas stove can be automatically controlled to be closed, the risk of fire can be effectively reduced, and meanwhile, when the sign of the fire occurs, information is timely transmitted to a fire alarm answering center to be processed, and the loss caused by the fire can be effectively reduced.
In the embodiment, parameter information of the intelligent household appliance and standard parameter information of an indoor environment are recorded and stored in advance through a parameter setting recording storage module, a real-time monitoring module monitors the service condition of the intelligent household appliance in real time, the monitored information is transmitted to a data processing analysis module for storage, an indoor environment sampling module is used for sampling the indoor environment and analyzing the data recorded by the parameter setting recording storage module through the data analysis module, when the indoor temperature is high or low, a human body sensing module senses that a person is in the room, an early warning module A reminds a person to start an air conditioner or a heater in a voice broadcasting mode, meanwhile, an information transmitting module transmits a message to a mobile phone APP, the person can respond after receiving the message, a silencing response module transmits a signal to the data processing analysis module after receiving the response of the person, and the data processing analysis module transmits the information to a control module which controls the corresponding intelligent household appliance to be started, so that the condition of discomfort caused by the environment when the person falls asleep at night can be effectively reduced, and the use comfort of the person can be improved;
meanwhile, the human body induction module detects the condition of the intelligent gas stove in the kitchen, when the human body induction module induces that the kitchen is not occupied and the gas stove is at the starting time, the timing module in the human body induction module starts timing, and transmits the timing time to the data processing analysis module, and the data processing analysis module adoptsWhen the time for the person to leave exceeds the standard time, the early warning module A early warns the person to prompt the person, the person timely responds and processes the person, if no person responds, the control module directly controls the intelligent gas stove to be closed, and the intelligent gas stove is automatically controlled when the kitchen is emptyThe mode of closing the gas stove can effectively reduce the risk of ignition;
when the gas sampled by the indoor environment sampling module contains smoke, the data processing analysis module analyzes the collected gas and judges whether the gas has a sign of fire or not, if the gas has a weather of fire, the early warning module A warns and reminds personnel, if the personnel responds and processes at home in time, if the human body sensing module detects that the personnel is not at home, and when the response time of the personnel exceeds the standard time, the early warning module A transmits early warning information to the cloud warning module, the cloud warning module transmits the information to the fire answering center, the fire answering center timely carries out coping process, and the loss caused by the fire can be effectively reduced by the mode of timely carrying out alarming process when the fire occurs and no person is at home.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (9)
1. The intelligent home safety early warning system based on the artificial intelligence comprises a user side, a cloud alarm module and a safety early warning system, and is characterized by comprising a real-time monitoring module, an indoor environment sampling module, a data processing analysis module, an early warning module A, a message response module, a control module, a human body induction module and a parameter setting input storage module;
the user terminal comprises an intelligent household appliance and a mobile phone APP, wherein the intelligent household appliance is connected with the real-time monitoring module and the control module, the mobile phone APP is connected with the message response module and the early warning module A, and the cloud warning module is connected with the early warning module A;
the data processing and analyzing module is connected with the indoor environment sampling module, the real-time monitoring module, the early warning module A, the message response module, the control module, the human body sensing module and the parameter setting input storage module.
2. The intelligent household safety early warning system based on artificial intelligence according to claim 1, wherein the intelligent household appliances comprise various electrical appliances such as lighting lamps, air conditioners, heaters, humidifiers, intelligent gas stoves and curtains.
3. The intelligent household safety early warning system based on artificial intelligence according to claim 1, wherein the indoor environment sampling module comprises a temperature sensor, a humidity sensor, a gas sensor and the like, and is used for sampling indoor temperature, humidity, smoke conditions and the like, when the indoor environment sampling module samples, the sampling module in the indoor environment sampling module sends corresponding instructions to the sensors through communication interfaces with the sensors so as to acquire data acquired by the sensors, and the sampling module can send reading instructions to the sensors periodically or on demand so as to acquire latest environmental parameter data.
4. The intelligent household safety early warning system based on artificial intelligence according to claim 1, wherein a timing module is built in the human body sensing module and is used for timing the interval time of no person after the intelligent gas stove is started and transmitting the time to the data processing and analyzing module, the standard time when the person leaves is set to be 15-20min by the timing module, and the data processing and analyzing module adopts the formula:the time of the timing module is called and processed, wherein +.>For cooking time and locating a standard time after leaving the person, when +.>At the same time, the normal time is indicated, the monitoring is continued, when +.>And when the time exceeds the standard time, the early warning module A is required to remind personnel and the flameout treatment is controlled by the control module.
5. The intelligent home safety early warning system based on the artificial intelligence according to claim 1, wherein a signal sending module and a voice broadcasting module are arranged in the early warning module A, the voice broadcasting module is used for directly giving voice alarm to remind personnel, and the information sending module is used for sending early warning notices to the mobile phone APP.
6. The intelligent home safety early warning system based on artificial intelligence of claim 1, wherein the cloud alarm module is connected with an external fire alarm answering center in the following information transmission manner: the data of the cloud alarm module is processed and forwarded through the cloud server, and early-warning data information is sent to a fire alarm answering center, and the fire alarm answering center provides a system with an alarm information receiving function, and the system can receive alarm data from the cloud server and correspondingly process and distribute the alarm data to corresponding personnel.
7. The intelligent household safety early warning system based on artificial intelligence according to claim 1, wherein the parameter input storage module is used for inputting and storing parameter information of intelligent household appliances and standard parameter information of indoor environments.
8. The intelligent household safety pre-warning system based on artificial intelligence of claim 3, wherein the data processing and analyzing module is used for storing data, and the data processing and analyzing module analyzes the gas smoke concentration data measured by the gas sensor, and can judge whether the sign of fire exists or not through analysis, the algorithm used in the analysis is a neural network identification algorithm, and the application formula comprises: calculation of input layer to hidden layer: z_h=w_hx+b_ha_h=f (z_h); calculation of hidden layer to output layer: z_o=w_oa_h+b_oa_o=f (z_o), wherein w_h and w_o are weight matrices of the hidden layer and the output layer, b_h and b_o are corresponding bias terms, f is an activation function, x is input data, z_h is a weighted sum of the hidden layer, a_h is an activation value of the hidden layer, z_o is a weighted sum of the output layer, a_o is an activation value of the output layer; gradient calculation from output layer to hidden layer: δ_o= (a_o-y) f' (z_o); gradient computation of hidden layer to input layer: delta_h= (w_o≡δ_o) ×f '(z_h), where delta_o is the error of the output layer, y is the actual value, f' is the derivative of the activation function, and T represents the transpose of the matrix; updating weights and biases of the hidden layer to the output layer: Δw_o= - α δ_o a_h Δb_o= - α δ_o; updating weights and biases of input layer to hidden layer: Δw_h= - α x δ_h= - α x δ_h where Δw_o and Δw_h are adjustment amounts of weights, Δb_o and Δb_h are adjustment amounts of offsets, α is a learning rate, and x is input data.
9. The intelligent home security pre-warning system based on artificial intelligence of claim 1, wherein the message response module sets the standard time for the personnel not to respond to be 10-15min.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311779738.8A CN117706951A (en) | 2023-12-22 | 2023-12-22 | Intelligent household safety early warning system based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311779738.8A CN117706951A (en) | 2023-12-22 | 2023-12-22 | Intelligent household safety early warning system based on artificial intelligence |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117706951A true CN117706951A (en) | 2024-03-15 |
Family
ID=90153114
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311779738.8A Pending CN117706951A (en) | 2023-12-22 | 2023-12-22 | Intelligent household safety early warning system based on artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117706951A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118038620A (en) * | 2024-04-11 | 2024-05-14 | 深圳天益建设工程有限公司 | Intelligent fire safety monitoring system and method |
-
2023
- 2023-12-22 CN CN202311779738.8A patent/CN117706951A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118038620A (en) * | 2024-04-11 | 2024-05-14 | 深圳天益建设工程有限公司 | Intelligent fire safety monitoring system and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117706951A (en) | Intelligent household safety early warning system based on artificial intelligence | |
| CN1849994B (en) | Domestic sleeping health monitoring system | |
| TWI610596B (en) | Modular multifunctional bio-recognition lighting device | |
| CN108646576A (en) | A kind of intelligent cloud platform of smart home based on big data technology | |
| US4839562A (en) | Electrical devices | |
| CN105045238A (en) | Intelligent home furnishing sleep system | |
| CN204759188U (en) | Intelligence house sleep system | |
| CN114511982B (en) | Smoke alarm method and intelligent smoke alarm | |
| GB2155708A (en) | Electrical devices | |
| CN208000667U (en) | A kind of internet of things intelligent household alarm system | |
| CN110955151A (en) | Automatic scene control sensing system and method for smart home | |
| CN108803546A (en) | A kind of Intelligent home monitoring system | |
| CN207541488U (en) | Classroom electric appliance intelligent switch system | |
| CN209841823U (en) | Intelligent household air detection control system | |
| CN108983623A (en) | A kind of monitoring system of smart home | |
| CN112880161A (en) | Automatic awakening and temperature adjusting air conditioner system and method based on artificial intelligence | |
| CN215770026U (en) | Big data-based environment detection and analysis system | |
| CN205594340U (en) | Remote intelligent house control system | |
| CN212256044U (en) | Intelligent household detection system based on Internet of things | |
| CN109542002A (en) | A kind of networking illumination supervision equipment and management system applied to office building | |
| JP2002042281A (en) | Safety discriminating device and safety deciding device and reporting device | |
| CN212460344U (en) | STM 32-based intelligent bathroom air detection system | |
| CN111092953A (en) | Indoor environment remote monitoring device based on Internet of things | |
| CN211741898U (en) | Household environment monitoring system | |
| CN212843714U (en) | Remote intelligent monitoring system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |