Multimodal Posture Monitoring and Eye Health Surveillance

Addressing concerns that prolonged use of devices in today’s digital landscape has led to increased negative personal representation, leading to disruption and health issues, our research offers a new framework to enhance postural alignment and eye health is meant. Utilizing state-of-the-art Flex sensors and machine learning algorithms, our system delivers real-time feedback to users, designing an ergonomically sound work environment that integrates MQTT communication for Flex sensor data and imagery paragraph based webcam. We used a multimodal approach combining data from flex sensors and computer vision to perform a comprehensive postural analysis. In addition, the system monitors eye health by analyzing blink frequency and screen-to-screen distance. Our project shows promising results, helping to develop proactive solutions for continuous well-being in the digital age.