IoT-Based Wearable Devices for Personal Safety and Accident Prevention Systems

This paper proposed an Internet of Things (IoT)-based wearable device system to protect the person's safety and prevent accidents. The wearable device and main processor are the Raspberry Pi, while other sensors monitor the user's surroundings and health. Such sensor types include the heart rate monitor, gyroscope, proximity sensor, and accelerometer. The wearable device provides the system with its most recent position information using its integrated GPS module. Real-time wearer tracking is possible with the Raspberry Pi using GPS data. The RF module makes wireless data transfer and communication between the wearable device's many parts possible. After gathering sensor data, the RF module transfers data wirelessly to a cloud-based database. The sensor data and alerts notification quickly send to the cloud. The cloud database is a flexible and easily available data management platform that saves up data storage, access, and analysis. To detect risks to security, the system analyzes data from sensors saved in the cloud. The system can generate real-time warnings and notifications in the case of a potential threat to the user's safety. The system allows continuous monitoring, wireless interaction, centralized data storage, and analytical processing. The potential of IoT technology to improve human safety and accident avoidance in a wide range of settings is shown by this integrated solution. The technology can improve security and reduce risks in various scenarios by providing real-time monitoring, wireless connection, efficient data storage, and analysis.