This project explores a practical implementation of a domotics fall detection system that uses off-the-shelf IoT devices interconnected through the Home Assistant platform. The objective of this study is to experiment and test that the design concept and the proposal is feasible for enhancing convenience, and security within the residential environment. The project begins by selecting a set of motion sensors and presence sensors commercially available. These devices are integrated into a unified ecosystem using the Raspberry Pi 4 and Home Assistant platform, which act as a central hub for device management and data analysis. The results of the implementation demonstrate the system's effectiveness in providing assistance when a fall is detected by collection and analysis of the sensor data. Furthermore, the integration of the two motion sensors and a presence sensor help discriminate between regular walking/sitting/raising and a dangerous fall followed by an alarm system for immediate assistance. This implementation highlights the potential of utilizing readily available IoT technologies and the Home Assistant platform to demonstrate a fall detection system.
This project explores a practical implementation of a domotics fall detection system that uses off-the-shelf IoT devices interconnected through the Home Assistant platform. The objective of this study is to experiment and test that the design concept and the proposal is feasible for enhancing convenience, and security within the residential environment. The project begins by selecting a set of motion sensors and presence sensors commercially available. These devices are integrated into a unified ecosystem using the Raspberry Pi 4 and Home Assistant platform, which act as a central hub for device management and data analysis. The results of the implementation demonstrate the system's effectiveness in providing assistance when a fall is detected by collection and analysis of the sensor data. Furthermore, the integration of the two motion sensors and a presence sensor help discriminate between regular walking/sitting/raising and a dangerous fall followed by an alarm system for immediate assistance. This implementation highlights the potential of utilizing readily available IoT technologies and the Home Assistant platform to demonstrate a fall detection system.
Proof-of-concept of a fall detection system based on low-cost IoT devices
VARDHARAJAN, MONISHA
2022/2023
Abstract
This project explores a practical implementation of a domotics fall detection system that uses off-the-shelf IoT devices interconnected through the Home Assistant platform. The objective of this study is to experiment and test that the design concept and the proposal is feasible for enhancing convenience, and security within the residential environment. The project begins by selecting a set of motion sensors and presence sensors commercially available. These devices are integrated into a unified ecosystem using the Raspberry Pi 4 and Home Assistant platform, which act as a central hub for device management and data analysis. The results of the implementation demonstrate the system's effectiveness in providing assistance when a fall is detected by collection and analysis of the sensor data. Furthermore, the integration of the two motion sensors and a presence sensor help discriminate between regular walking/sitting/raising and a dangerous fall followed by an alarm system for immediate assistance. This implementation highlights the potential of utilizing readily available IoT technologies and the Home Assistant platform to demonstrate a fall detection system.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/60586