# Car-Sense: Vehicle Occupant Legacy Hazard Detection Method Based on DFWS
## 2 Related Work  
The use of wireless devices to achieve vehicle interior sensing technology has a wide range of applications and can achieve a variety of states of identification of personnel. There are three specific types: infrared and other sensor-based methods, machine vision-based methods, and radio frequency sensing-based methods. * Sensor-based approach: IoT sensors for detecting persons in vehicles generally include human infrared sensors, gas sensors, and temperature sensors. These methods generate sensory signals by sensing specific wavelengths of infrared light, specific  
Figure 1: Car-Sense, ESP32-based contactless in-vehicle occupant sensing. compositions of gases, and specific ambient temperatures to indirectly infer the status of people. [PERSON] [8] used Android apps with Bluetooth devices to warn parents or guardians that their children are being left in the car. Alternatively, using a microcontroller, Hall sensor, infrared, temperature, carbon dioxide sensor, and other modules, we have realized an alarm for children stranded in the car by setting the detection threshold. Alternatively, with the use of photoelectric sensors and other situation monitors inside the car, when stranded children are found in the car, the original car air conditioning system and windows can be alarmed and activated to protect the safety of the occupants. The above systems, because they rely on simple sensors with weak detection capabilities and are influenced by the environment, often achieve insufficient accuracy and, in practice, also depend on changes in the different states of the target. * Computer vision-based approach: Based on image recognition methods arising from the development and application of neural networks in recent years, the technology of image recognition has crossed into a new stage. The camera takes photos of the interior of the car, extracts the characteristics of the person for analysis of the target state, and grasps the words and behaviors of the person inside the car. Using the age-recognition-based image recognition method, combined with machine learning, the Internet of things, cloud communication, and other technologies, around the face age recognition analysis of a variety of scenes and appropriate processing. The use of cameras and multiple IoT sensors combined to determine the true parking of vehicles and the presence of people. However, it is still not the best solution due to the lack of good privacy of image recognition and the fact that the recognition effect is greatly reduced when the photo is too dark in the absence of light or dark light. * RF signal-based methods: wireless RF sensing technology has also been used as one of the sensing means due to its advantages, such as good privacy. The popularity of millimeter-wave radar and the maturity of the technology allows the millimeter-wave radar to achieve more fine-grained detection than Wi-Fi [9], whereas mm-Pose [10] uses millimeter-wave radar to achieve higher resolution accuracy; however, due to the high price of the equipment and the difficulty of deployment, it will not be available as a mainstream solution for some time in the future. The gradual maturity of Wi-Fi-CSI recognition technology has made it possible to use Wi-Fi signals for in-vehicle personnel detection. WiCAR [11] used commercial Wi-Fi to build a model to sense in-vehicle personnel movements with a recognition accuracy of about 95%. Although the resolution of Wi-Fi will never be as detailed as that of cameras and radar, there is greater scope for the devices to be deployed more easily. Each of the above approaches has its own advantages and disadvantages. While cameras still seem to be the best solution, they are still not much used in the broad field of in-vehicle security because of privacy concerns. The means for wireless sensing becomes the optimal alternative to image sensing.