Bedridden Disabled People's Monitoring System
R.R. Maghade1, Saiprasad Darekar2, Parth Jadhav3, Aditya Shinde4, Rushikesh Dahiphale5
1Professor, Dept. of Computer Technology, P.Dr.V.V.P. Institute of Technology and Engineering, Loni,
Maharashtra, India
2,3,4,5 Final year Diploma Student, P.Dr.V.V.P. Institute of Technology and Engineering, Loni,
Maharashtra, India
Abstract - People who are bedridden because of a disability, a long-term disease, or old age often have a hard time letting others know what they need and keeping them safe. Traditional caring approaches depend a lot on having somebody around all the time, which isn't always possible. This project offers a new Bedridden Disabled People's Monitoring System that will keep an eye on their health and safety in real time, make it easier for them to talk to each other, and improve the overall quality of care for people who are stuck in bed. The device uses a convolutional neural network (CNN) to keep an eye on how the body moves. It also has sensors that can tell you about the room's temperature, humidity, and air quality. Deep learning-based algorithms (CNN) can find strange patterns, such irregular heartbeats, sudden immobility, or indicators of distress, and send alerts to caregivers or healthcare experts right away through mobile notifications, alarms, or cloud dashboards. Caregivers can easily access live health data, get automatic alarms, and talk to the patient from a distance using a user-friendly interface. The system may have voice control, gesture recognition, or a single-button emergency call feature to make it easy for patients with restricted movement or speech problems to ask for help. Cloud-based storage makes sure that all the data that is collected is safely kept so that medical professionals can analyze it over time and make diagnoses from afar. This system uses cutting-edge technologies including the Internet of Things (IoT), wearable biosensors, wireless connectivity, and AI-based anomaly detection to make life easier for caregivers, make patients safer, and help find medical problems sooner. In the end, the suggested option gives bedridden impaired people the ability to keep their dignity, independence, and improved health while reducing stress for caregivers.
Key Words: Bedridden patients, Disabled people monitoring, IoT-based healthcare, Remote patient monitoring, Wearable biosensors, Deep learning in healthcare
