Human Activitity Recognition System Using Accelerometer and Zigbee

With the advent of miniaturized sensing technology, which can be body worn, it is now possible to collect and store data on different aspects of human activities under the conditions of free living. This technology has the potential to be used in automated activity profiling systems which produce a continuous record of bodily activity patterns over extended periods of time. Such activity profiling systems are dependent on recognition algorithms which can effectively interpret body worn sensor data and identify different activities. The automated recognition of bodily activities (stationary, walking, running, jogging) using body worn accelerometer data is a challenging area of work. In this book existing activity recognition system were discussed. In Existing activity recognition systems suffer from several obvious practical limitations such as the location and nature of sensors that people will tolerate. Other issues include ease of use, discretion, cost, and the ability to perform daily activities unimpeded. The results are getting from the Accelerometers with different subjects are collected through pc and can be analysed by Matlab software by activity variance and DT algorithm.

Mr. M. Muni Sankar received his M.Tech degree in Digital Electronics and communication systems from JNTU, Anantapur, India in 2012. After completing Masters degree he has joined as Assistant Professor of ECE at Siddharth institute of engineering & technology, Puttur, India and published several papers in journals of international repute.