Air Care – Machine Learning Approach to Develop a Supportive and Monitoring System for an Elder

Elderly people are one of the greatest assets of our nation, and it suits all the countries. Due to the improper way of living, bad health habits, and because of many other factors, they need to be monitored. In these days of our lives, people are coming up with a lot of tools and technologies, but none of them suggested a good, sophisticated approach. Both human and technology has some downsides by themselves. This creates the need for an application that can fill all the downsides of the available approaches. Air Care is a cost-efficient, minimalistic, sophisticated approach to monitor elders by their activities. Mainly targets on loco-motions, high-level activities, restricting their motions, monitoring people who visit home and notify, and monitoring the attentiveness of caregivers like so. Accuracy rate of 89% gained through the process. The primary objective of our research project is to find a solution using Machine learning, and deep learning to overcome the monitoring issues. Therefore, this paper focuses on developing and deploying a monitoring application by clustering data and using algorithms (SVM & K-Means) and neural network in a minimalistic way.