Automated Child Rescue System from Borewells using Artificial Intelligence and Wireless Tech

This project shows a creative and effective technological solution to the problem of children falling into unprotected borewells. Any uncovered borewells that are a danger due to India’s excessive reliance on groundwater for irrigation usually endanger children. Conventional rescue methods are hampered by human error, limited time, and inefficiency; so, an automated and accurate approach is needed. Using machine learning techniques, the automated monitoring system is improved by including a camera module and the VGG-16 algorithm for higher detection accuracy. During the rescue operation, the child receives comfort with peaceful sounds while the emotion recognition algorithms measure the child’s level of distress. For an interactive audio module, we utilize the F1-score algorithm to evaluate the child’s consciousness, which will increase the system’s capability. Final decision-making regarding the child’s emotion is provided by a dedicated Python application. Comprehensive AI monitoring, coupled with real-time communication, makes it possible to achieve efficient and rapid emotional recognition, enabling this system to offer a solid solution for the rescue of children from bore wells, thus improving safety.