This project focuses on building a smarter and more reliable system for women’s safety using a combination of Artificial Intelligence and IoT. The idea came from a simple but important problem most existing safety solutions depend on the user taking action, which may not always be possible in real life situations. To address this, the system is designed to work automatically. It uses different sensors to monitor movement, location, and basic health signals, and tries to identify unusual or risky situations. For example, sudden movements, irregular patterns, or signs of distress can be detected without the need for manual input. Once such a situation is recognized, the system immediately sends alerts along with the user’s location to emergency contacts. One of the key strengths of this system is its reliability. Instead of depending on a single network, it uses multiple communication methods so that alerts can still be sent even in low network conditions. Along with this, features like alarms and visual signals are included to help attract attention in critical moments. This work also tries to go a step further than existing solutions by focusing on prevention and early detection rather than just reacting after something happens. It brings together both hardware and software in a way that is practical and can be used in real-world conditions, especially in busy urban environments like Delhi. Overall, the aim of this project is to explore how technology can be used more effectively to improve personal safety, making systems smarter, faster, and more dependable when it matters the most.
Aadhar Gupta (Mon,) studied this question.