In-vehicle anti-suffocation device based on Internet of Things and working method thereof

Abstract

The invention discloses an in-vehicle anti-suffocation device based on the Internet of Things and a working method of the in-vehicle anti-suffocation device. The in-vehicle anti-suffocation device comprises a main control assembly, an environment sensing module, an emergency communication module and a danger judgment algorithm. The environment sensing module monitors in-vehicle environment data and personnel retention conditions in real time; and the main control assembly dynamically analyzes data through a danger judgment algorithm, and judges the danger level in combination with a dynamic threshold adjustment and false alarm prevention module. And the emergency communication module realizes real-time communication and remote warning with a mobile application program and a webpage end of a vehicle owner through a 4G-LTE terminal and voice synthesis equipment, triggers corresponding emergency measures step by step when environment data reaches different levels of danger threshold values, and automatically alarms to related departments under the highest danger level. Through multi-sensor fusion, an intelligent algorithm and the Internet of Things communication technology, the suffocation risk caused by retention of people in the vehicle is effectively prevented, the characteristics of high-precision monitoring and low false alarm are achieved, and the automation level of vehicle safety protection is improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of smart car safety, and specifically to an in-vehicle anti-suffocation safety solution that combines the Internet of Things with a dynamic programming algorithm, radio frequency communication, and data visualization. Specifically, the present invention relates to an in-vehicle anti-suffocation device based on the Internet of Things and a working method thereof. Background Art

[0002] Every year, countless deaths worldwide occur due to suffocation caused by people left behind in closed vehicles. In the summer, temperatures inside closed vehicles exposed to direct sunlight can rise dramatically, leading to a rapid increase in carbon dioxide concentrations, creating a dangerous or even fatal environment. However, despite the rapid development of technology, there remains a lack of effective solutions to detect and automatically alert drivers when someone is left behind, leading to frequent tragedies. Therefore, efforts should be made to address this safety hazard.

[0003] Nowadays, although relevant anti-suffocation systems are constantly being proposed, many of them use ultrasonic or infrared means. Both technologies are easily blocked by other objects in the car, which will cause the anti-suffocation system to be frequently activated by mistake, wasting a lot of resources.

[0004] The control system of the existing patent CN106143378A uses an ultrasonic probe and a camera for detection. The system is relatively complex and redundant, and the alarm device uses a flashing car light group and an external speaker. Although the system has an auxiliary anti-theft function, its automatic door opening and closing structure can be easily exploited by people with ulterior motives, which obviously increases the safety risks of people and property in the car.

[0005] While the control method in existing patent CN107600019A is simple in structure, it lacks a step to determine whether a person is inside the vehicle. This significantly increases the system burden and disrupts the driver's normal life. Furthermore, this control method utilizes audible and visual alarms and lowering windows, which could be exploited by those with ulterior motives, significantly increasing the safety risk to occupants and property.

[0006] Although the existing patent CN109532665A uses facial recognition technology and mobile applications to notify car owners, its in-car environment monitoring data is not diverse enough and cannot be visualized. Its danger judgment logic is too simple and cannot adapt to external changes. There is no clear anti-false alarm mechanism, and its response measures are not satisfactory.

[0007] This shows that traditional solutions rely on the driver's awareness and lack or have no effective data visualization, proactive monitoring, and emergency response mechanisms. Therefore, it is crucial to develop low-cost, highly reliable in-car environment monitoring and automatic distress call systems by integrating the Internet of Things. Summary of the Invention

[0008] The object of the present invention is to provide an in-vehicle anti-suffocation device based on the Internet of Things and a working method thereof.

[0009] The technical solutions of the present invention are as follows:

[0010] An in-vehicle anti-suffocation device based on the Internet of Things and its working method, the in-vehicle anti-suffocation device includes a main control component and an environmental perception module connected to the main control component, an emergency communication module, and a danger judgment algorithm used by the main control component. The main control component includes an in-vehicle controller and a battery, and the battery supplies power to the main control component. The environmental perception module includes a camera, a temperature and humidity sensor, an air quality sensor, and a thermal imaging sensor. The camera is installed in the vehicle and obtains in-vehicle images in real time. The temperature and humidity sensor is installed in the vehicle and monitors the temperature and humidity in the vehicle in real time. The air quality sensor is installed in the vehicle and monitors the concentration of each gas component in the vehicle in real time. The thermal imaging sensor is installed The emergency communication module includes a 4G-LTE terminal and a voice synthesis device, and is pre-installed with a web page that matches the emergency communication module. The owner's smart terminal is pre-installed with a mobile application that matches the emergency communication module. The emergency communication module is used to upload the in-vehicle environmental data to the web page and mobile application for visual analysis, as well as remote communication and remote warning with the owner in the event of a dangerous situation. At the same time, the main control component will communicate with the on-board computer to start the on-board air conditioning for ventilation. The danger judgment algorithm includes multi-sensor data integration, dynamic threshold adjustment and false alarm prevention modules; it is characterized in that the anti-suffocation method includes the following steps:

[0011] Step 1: After the vehicle turns off the engine and locks the doors, the device completes initialization and starts working;

[0012] Step 2: Read the data sent back by the temperature and humidity sensor and the air quality sensor in real time and automatically analyze it;

[0013] Step 3: After shutting down the engine and locking the doors, the main control component determines whether the data returned by the temperature and humidity sensor and the air quality sensor exceeds the danger threshold based on the danger judgment algorithm: if yes, execute step 4; otherwise, execute step 2;

[0014] In step 4, the main control component determines whether there is anyone inside the vehicle based on the real-time interior image transmitted by the camera and the interior heat distribution data transmitted by the thermal imaging sensor. If so, it proceeds to step 5. Otherwise, it enters a silent state and only uploads the interior environment data to the website and mobile application for visual analysis to facilitate the owner's understanding.

[0015] Step 5: The main control component processes the analysis results. If a person is trapped in the vehicle and the environmental data reaches the first-level danger threshold, the emergency response light will light up in a conspicuous location, and the owner will be notified via a push notification message on the owner's mobile app. At this time, the person trapped in the vehicle can manually turn off the device after multiple anti-accidental touch verifications. If the device is turned off, it will enter a silent state and only upload the vehicle's environmental data to the website and mobile app for visual analysis to facilitate the owner's understanding. If the device is not turned off, step 6 will be executed.

[0016] Step 6: The main control component processes the following based on the analysis results: When a person is stranded in the vehicle and the environmental data reaches the second-level danger threshold, while keeping the emergency response light of the device on, the main control component will communicate with the on-board computer to start the vehicle battery to power the vehicle air conditioner and start the vehicle air conditioner for ventilation. At the same time, the main control component will continuously push messages through the owner's mobile application, and the 4G-LTE terminal will continuously send text messages to the emergency contact number preset in the owner's mobile application to notify the owner. At this time, the person stranded in the vehicle must pass multiple anti-accidental touch verifications and must also obtain authorization from the owner's mobile application before the device can be manually turned off. If the device is turned off, it will enter a silent state and only upload the vehicle's environmental data to the website and mobile application for visual analysis so that the owner can understand it. If the device is not turned off, proceed to step 7.

[0017] Step 7: The main control component processes based on the analysis results: When there are people stranded in the car and the environmental data reaches the third-level danger threshold, the device does not allow manual shutdown. While keeping the device's emergency response light on and the vehicle air conditioning ventilated, the 4G-LTE terminal will dial the emergency contact phone number preset in the car owner's mobile application, and cooperate with the mobile application to make the emergency contact's smart terminal ring and vibrate. If the person answers the call, the voice synthesis module broadcasts the warning information, and all modules are closed after the car door is unlocked to end the work. If the person does not answer the call, the call will be called repeatedly. If the person does not answer the call three times, the relevant department will be alerted after the final strict anti-false alarm verification, and all modules will be closed after the car door is unlocked to end the work.

[0018] Furthermore, the environmental perception module includes a temperature and humidity sensor, an air quality sensor, a thermal imaging sensor, and a camera arranged in the vehicle, and the above sensors are all connected to the main control component.

[0019] Furthermore, the main control component is pre-installed with a facial feature database obtained by training facial images through a deep learning network. The main control analyzes and identifies people in the images inside the car taken by the camera based on the facial feature database, and controls the system based on the analysis results and the monitoring data of the environmental perception module.

[0020] Furthermore, the danger judgment algorithm includes multi-sensor data integration, dynamic threshold adjustment and false alarm prevention modules, wherein the specific method of dynamic threshold adjustment is to calculate the average value based on seasonal differences or local historical weather data, and use this value as the weather data suitable for the human body when the device is running, and dynamically adjust the danger thresholds at all levels accordingly. The specific method of false alarm prevention is time window filtering technology, using the EWMA (exponentially weighted moving average) algorithm. After the calculated value exceeds the predetermined number of danger thresholds at each level within a predetermined time, it is combined with the camera and thermal imaging sensor data for review to confirm that people are stranded in the car and the environment has deteriorated.

[0021] Furthermore, the emergency communication module includes a 4G-LTE terminal, which has a SIM card or supports eSIM, so that emergency contacts or relevant departments can be contacted when there is no Internet connection.

[0022] The beneficial effects of the present invention are as follows:

[0023] The multi-dimensional environmental monitoring and high-precision judgment system of this invention integrates temperature and humidity sensors, air quality sensors, thermal imaging sensors, and cameras to achieve comprehensive monitoring of vehicle temperature, humidity, gas component concentrations, heat distribution, and occupant retention. Combined with a dynamic threshold adjustment algorithm and false alarm prevention, it significantly improves the accuracy of hazard judgment and reduces the false alarm rate, effectively avoiding the susceptibility of traditional single sensors to interference.

[0024] The hierarchical emergency response mechanism of the present invention balances safety and resource optimization. It sets three levels of danger thresholds based on environmental data and triggers differentiated emergency measures step by step. This can reduce unnecessary intervention, balance safety and energy consumption, and ensure timely rescue under the highest risks. This mechanism avoids the waste of resources caused by the "one-size-fits-all" response of traditional systems, and significantly improves emergency rescue efficiency.

[0025] The present invention's IoT-based intelligent interaction and remote management enables real-time visualization and analysis of in-vehicle environmental data through 4G-LTE terminals, supporting web pages, and mobile applications. Car owners can remotely view key indicators such as temperature, humidity, and gas concentrations, and receive customized alerts. The system supports seamless communication with the vehicle's onboard computer, automatically triggering ventilation equipment, reducing reliance on manual operation and improving response speeds to milliseconds.

[0026] The high compatibility and low power consumption design of the present invention allows the main control component to support multiple vehicle interface protocols and adapt to different platforms such as fuel vehicles and new energy vehicles. The use of low-power sensors and optimization algorithms, dynamic power supply configuration, and full-power endurance extended to more than 72 hours to meet long-term needs. The system's modular design supports future expansion and significantly reduces the cost of technology iteration.

[0027] This invention has significant social benefits, reducing public safety risks. By leveraging a coordinated mechanism between relevant departments, the system automatically issues an alarm and provides vehicle location information when emergency contacts are unable to be contacted, shortening rescue response times. This invention is particularly suitable for scenarios such as school buses and family vehicles, and offers significant social security benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the implementation of the present invention or the existing technical solutions, the following is a brief introduction to the drawings required for the embodiments or the description of the prior art:

[0029] Figure 1 This is a structural diagram of an in-vehicle anti-suffocation device based on the Internet of Things according to the present invention;

[0030] Figure 2 This is a workflow diagram of an in-vehicle anti-suffocation device based on the Internet of Things and its working method of the present invention. DETAILED DESCRIPTION

[0031] like Figure 1 As shown, the present invention discloses an in-vehicle anti-suffocation device based on the Internet of Things. The in-vehicle anti-suffocation device adopted includes a main control component and an environmental perception module connected to the main control component, an emergency communication module, and a danger judgment algorithm used by the main control component. The main control component includes an in-vehicle controller and a battery, and the battery supplies power to the main control component. The environmental perception module includes a camera, a temperature and humidity sensor, an air quality sensor, and a thermal imaging sensor. The emergency communication module includes a 4G-LTE terminal and a speech synthesis device. At the same time, a web page matching the emergency communication module is pre-installed. The owner's smart terminal is pre-installed with a mobile application matching the emergency communication module. The danger judgment algorithm includes multi-sensor data integration, dynamic threshold adjustment, and false alarm prevention modules.

[0032] Furthermore, the environmental perception module includes a temperature and humidity sensor, an air quality sensor, a thermal imaging sensor, and a camera arranged in the vehicle. The camera is installed in the vehicle and obtains images of the vehicle in real time. The temperature and humidity sensor is installed in the vehicle and monitors the temperature and humidity in the vehicle in real time. The air quality sensor is installed in the vehicle and monitors the concentration of each gas component in the vehicle in real time. The thermal imaging sensor is installed in the vehicle and monitors the heat distribution in the vehicle in real time. The above sensors are all connected to the main control component.

[0033] Furthermore, the emergency communication module is used to upload the in-vehicle environmental data to web pages and mobile applications for visual analysis, as well as remote communication and remote warning with the car owner in the event of an emergency. At the same time, the main control component will communicate with the on-board computer to start the on-board air conditioning for ventilation.

[0034] like Figure 2 As shown, its working method includes the following processes:

[0035] Step 1: After the vehicle turns off the engine and locks the doors, the device completes initialization and starts working;

[0036] Step 2: Read the data sent back by the temperature and humidity sensor and the air quality sensor in real time and automatically analyze it;

[0037] Step 3: After shutting down the engine and locking the doors, the main control component determines whether the data returned by the temperature and humidity sensor and the air quality sensor exceeds the danger threshold based on the danger judgment algorithm: if yes, execute step 4; otherwise, execute step 2;

[0038] In step 4, the main control component determines whether there is anyone inside the vehicle based on the real-time interior image transmitted by the camera and the interior heat distribution data transmitted by the thermal imaging sensor. If so, it proceeds to step 5. Otherwise, it enters a silent state and only uploads the interior environment data to the website and mobile application for visual analysis to facilitate the owner's understanding.

[0039] Step 5: The main control component processes the analysis results. If a person is trapped in the vehicle and the environmental data reaches the first-level danger threshold, the emergency response light will light up in a conspicuous location, and the owner will be notified via a push notification message on the owner's mobile app. At this time, the person trapped in the vehicle can manually turn off the device after multiple anti-accidental touch verifications. If the device is turned off, it will enter a silent state and only upload the vehicle's environmental data to the website and mobile app for visual analysis to facilitate the owner's understanding. If the device is not turned off, step 6 will be executed.

[0040] Step 6: The main control component processes the following based on the analysis results: When a person is stranded in the vehicle and the environmental data reaches the second-level danger threshold, while keeping the emergency response light of the device on, the main control component will communicate with the on-board computer to start the vehicle battery to power the vehicle air conditioner and start the vehicle air conditioner for ventilation. At the same time, the main control component will continuously push messages through the owner's mobile application, and the 4G-LTE terminal will continuously send text messages to the emergency contact number preset in the owner's mobile application to notify the owner. At this time, the person stranded in the vehicle must pass multiple anti-accidental touch verifications and must also obtain authorization from the owner's mobile application before the device can be manually turned off. If the device is turned off, it will enter a silent state and only upload the vehicle's environmental data to the website and mobile application for visual analysis so that the owner can understand it. If the device is not turned off, proceed to step 7.

[0041] Step 7: The main control component processes based on the analysis results: When there are people stranded in the car and the environmental data reaches the third-level danger threshold, the device does not allow manual shutdown. While keeping the device's emergency response light on and the vehicle air conditioning ventilated, the 4G-LTE terminal will dial the emergency contact phone number preset in the car owner's mobile application, and cooperate with the mobile application to make the emergency contact's smart terminal ring and vibrate. If the person answers the call, the voice synthesis module broadcasts the warning information, and all modules are closed after the car door is unlocked to end the work. If the person does not answer the call, the call will be called repeatedly. If the person does not answer the call three times, the relevant department will be alerted after the final strict anti-false alarm verification, and all modules will be closed after the car door is unlocked to end the work.

[0042] Furthermore, the main control component is pre-installed with a facial feature database obtained by training facial images through a deep learning network. The main control analyzes and identifies people in the images inside the car taken by the camera based on the facial feature database, and controls the system based on the analysis results and the monitoring data of the environmental perception module.

[0043] Furthermore, the danger judgment algorithm includes multi-sensor data integration, dynamic threshold adjustment and false alarm prevention modules, wherein the specific method of dynamic threshold adjustment is to calculate the average value based on seasonal differences or local historical weather data, and use this value as the weather data suitable for the human body when the device is running, and dynamically adjust the danger thresholds at all levels accordingly. The specific method of false alarm prevention is time window filtering technology, using the EWMA (exponentially weighted moving average) algorithm. After the calculated value exceeds the predetermined number of danger thresholds at each level within a predetermined time, it is combined with the camera and thermal imaging sensor data for review to confirm that people are stranded in the car and the environment has deteriorated.

[0044] Furthermore, the emergency communication module includes a 4G-LTE terminal, which has a SIM card or supports eSIM, so that emergency contacts or relevant departments can be contacted when there is no Internet connection.

[0045] The present invention adopts the above technical solutions, through multi-dimensional environmental monitoring and high-precision judgment, hierarchical emergency response mechanism, intelligent interaction and remote management based on the Internet of Things, high compatibility and low power consumption design, to achieve a significant improvement in the accuracy of danger judgment and reduce the false alarm rate, reduce unnecessary intervention, balance safety and energy consumption, ensure timely rescue under the highest risk, automatically trigger to reduce dependence on manual operation and increase response speed to milliseconds, support future expansion and significantly reduce the cost of technology iteration, with significant social benefits and reduced public safety risks. In addition, the dynamic threshold adjustment and false alarm prevention module in the danger judgment algorithm, the hierarchical response in the emergency response mechanism, data visualization and linkage of relevant departments adopted by the present invention are far ahead of existing patents, significantly improving rescue efficiency, optimizing resource allocation, and better preventing false alarms compared with existing patents.

[0046] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, can make equivalent replacements or changes based on the technical solution and inventive concept of the present invention, which should be within the scope of protection of the present invention.

Claims

1. An in-vehicle anti-asphyxia device based on the Internet of Things and its working method, the in-vehicle anti-asphyxia device comprises a main control component and an environmental perception module connected to the main control component, an emergency communication module, and a danger determination algorithm used by the main control component. The main control component comprises an in-vehicle controller and a battery, the battery supplies power to the main control component, the environmental perception module comprises a camera, a temperature and humidity sensor, an air quality sensor, and a thermal imaging sensor. The camera is installed in the vehicle and acquires in-vehicle images in real time. The temperature and humidity sensor is installed in the vehicle and monitors the temperature and humidity in the vehicle in real time. The air quality sensor is installed in the vehicle and monitors the concentration of various gas components in the vehicle in real time. An imaging sensor is installed inside the vehicle and monitors heat distribution in real time. The emergency communication module includes a 4G-LTE terminal and a voice synthesis device, and is pre-installed with a webpage that matches the emergency communication module. The owner's smart terminal is pre-installed with a mobile application that matches the emergency communication module. The emergency communication module is used to upload in-vehicle environmental data to the webpage and mobile application for visual analysis, as well as to remotely communicate with the owner and issue remote warnings in the event of a dangerous situation. At the same time, the main control component will communicate with the on-board computer to activate the on-board air conditioning for ventilation. The danger determination algorithm includes multi-sensor data integration, dynamic threshold adjustment, and false alarm prevention modules. It is characterized by: The anti-choking method includes the following steps: Step 1: After the vehicle turns off the engine and locks the doors, the device completes initialization and starts working. Step 2: Read the data sent back by the temperature and humidity sensor and the air quality sensor in real time and automatically analyze it. Step 3: After shutting down the engine and locking the doors, the main control component determines whether the data returned by the temperature and humidity sensor and the air quality sensor exceeds the danger threshold based on the danger judgment algorithm: if yes, execute step 4; otherwise, execute step 2; In step 4, the main control component determines whether there is anyone inside the vehicle based on the real-time interior image transmitted by the camera and the interior heat distribution data transmitted by the thermal imaging sensor. If so, it proceeds to step 5. Otherwise, it enters a silent state and only uploads the interior environment data to the website and mobile application for visual analysis to facilitate the owner's understanding. Step 5: The main control component processes the analysis results. If a person is trapped in the vehicle and the environmental data reaches the first-level danger threshold, the emergency response light will light up in a conspicuous location, and the owner will be notified via a push notification message on the owner's mobile app. At this time, the person trapped in the vehicle can manually turn off the device after multiple anti-accidental touch verifications. If the device is turned off, it will enter a silent state and only upload the vehicle's environmental data to the website and mobile app for visual analysis to facilitate the owner's understanding. If the device is not turned off, step 6 will be executed. Step 6: The main control component processes the following based on the analysis results: When a person is stranded in the vehicle and the environmental data reaches the second-level danger threshold, while keeping the emergency response light of the device on, the main control component will communicate with the on-board computer to start the vehicle battery to power the vehicle air conditioner and start the vehicle air conditioner for ventilation. At the same time, the main control component will continuously push messages through the owner's mobile application, and the 4G-LTE terminal will continuously send text messages to the emergency contact number preset in the owner's mobile application to notify the owner. At this time, the person stranded in the vehicle must pass multiple anti-accidental touch verifications and must also obtain authorization from the owner's mobile application before the device can be manually turned off. If the device is turned off, it will enter a silent state and only upload the vehicle's environmental data to the website and mobile application for visual analysis so that the owner can understand it. If the device is not turned off, proceed to step 7. Step 7: The main control component processes based on the analysis results: When there are people stranded in the car and the environmental data reaches the third-level danger threshold, the device does not allow manual shutdown. While keeping the device's emergency response light on and the vehicle air conditioning ventilated, the 4G-LTE terminal will dial the emergency contact phone number preset in the car owner's mobile application, and cooperate with the mobile application to make the emergency contact's smart terminal ring and vibrate. If the person answers the call, the voice synthesis module broadcasts the warning information, and all modules are closed after the car door is unlocked to end the work. If the person does not answer the call, the call will be called repeatedly. If the person does not answer the call three times, the relevant department will be alerted after the final strict anti-false alarm verification, and all modules will be closed after the car door is unlocked to end the work.

2. The in-vehicle anti-suffocation device based on the Internet of Things and the working method thereof according to claim 1, characterized in that: The environmental perception module includes a temperature and humidity sensor, an air quality sensor, a thermal imaging sensor, and a camera arranged in the vehicle, and all of the above sensors are connected to the main control component.

3. The in-vehicle anti-suffocation device based on the Internet of Things and the working method thereof according to claim 1, characterized in that: The main control component is pre-installed with a facial feature database obtained by training facial images through a deep learning network. The main control analyzes and identifies people in the images of the vehicle taken by the camera based on the facial feature database, and controls the system based on the analysis results and the monitoring data of the environmental perception module.

4. The in-vehicle anti-suffocation device based on the Internet of Things and the working method thereof according to claim 1, characterized in that: The danger judgment algorithm includes multi-sensor data integration, dynamic threshold adjustment and false alarm prevention modules, among which the specific method of dynamic threshold adjustment is to calculate the average value based on seasonal differences or local historical weather data, and use this value as the weather data suitable for the human body when the device is running, and dynamically adjust the danger thresholds at all levels accordingly. The specific method of false alarm prevention is time window filtering technology, using the EWMA (exponentially weighted moving average) algorithm. After the calculated value exceeds the predetermined number of danger thresholds at each level within a predetermined time, it is combined with the camera and thermal imaging sensor data for review to confirm that people are stranded in the car and the environment has deteriorated.

5. The in-vehicle anti-suffocation device based on the Internet of Things and the working method thereof according to claim 1, characterized in that: The emergency communication module includes a 4G-LTE terminal with a SIM card or an eSIM-enabled terminal, which can be used to contact emergency contacts or relevant departments when there is no Internet connection.

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