IOT - based Fall Prevention for Child Care using Motion Sensor
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| Formato: | Recurso digital |
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2025
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| _version_ | 1866901605861818368 |
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| author | Krunali Bhatt Dr. Sakena Benazer S |
| author_facet | Krunali Bhatt Dr. Sakena Benazer S |
| contents | This paper presents the design and development of a smart motion sensing system aimed at preventing child falls from heights, a leading cause of injury among young children. The system integrates motion sensors, including PIR motion sensor, to continuously monitor a child's position and behaviour in high-risk areas such as windows, balconies, and stairs. By analysing real- time data, the system detects potentially dangerous movements or posture shifts that indicate fall risks. In response, it triggers immediate alerts to caregivers via mobile apps or activates automated safety measures, such as locking windows or deploying barriers. Combining sensor fusion, data processing algorithms, and wireless communication, the system offers a scalable, non- intrusive solution for enhancing child safety. Prototype testing and simulations demonstrate its effectiveness as a preventive tool, highlighting its potential for both home and institutional use. Keywords: Child fall prevention, Fall detection system, Fall risk assessment, Safety monitoring |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18074781 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | IOT - based Fall Prevention for Child Care using Motion Sensor Krunali Bhatt Dr. Sakena Benazer S This paper presents the design and development of a smart motion sensing system aimed at preventing child falls from heights, a leading cause of injury among young children. The system integrates motion sensors, including PIR motion sensor, to continuously monitor a child's position and behaviour in high-risk areas such as windows, balconies, and stairs. By analysing real- time data, the system detects potentially dangerous movements or posture shifts that indicate fall risks. In response, it triggers immediate alerts to caregivers via mobile apps or activates automated safety measures, such as locking windows or deploying barriers. Combining sensor fusion, data processing algorithms, and wireless communication, the system offers a scalable, non- intrusive solution for enhancing child safety. Prototype testing and simulations demonstrate its effectiveness as a preventive tool, highlighting its potential for both home and institutional use. Keywords: Child fall prevention, Fall detection system, Fall risk assessment, Safety monitoring |
| title | IOT - based Fall Prevention for Child Care using Motion Sensor |
| url | https://doi.org/10.5281/zenodo.18074781 |