Safe Steps: A Smart Security System for Elderly

Falls are one of the primary causes of injuries among older adults, which lowers their quality of life and has detrimental effects on their health. As the global population ages, it's crucial that they maintain their independence and safety. The proposed model aims to provide a comprehensive solution to enhance senior citizen protection. Promptly identifying and avoiding falls can improve the well-being of elderly individuals and greatly reduce risks. Traditional methods of fall detection are prone to errors. Thus, the proposed model is designed to overcome such errors and accurately predict the falls. Tiny ML simplifies the deployment of machine learning models on low-power microcontrollers and edge devices, making it a great choice for lightweight and energy efficient applications by designing a small wearable device that can process data locally for quick detection and alert generation which helps to improve the safety and independence of elderly people. The proposed model also includes camera-based fall detection for indoor navigation.