Dataset for IoT Assisted Human Posture Recognition

The ability of detecting human postures is particularly important in several fields like ambient intelligence, surveillance, elderly care, and human-machine interaction. Most of the earlier works in this area are based on computer vision. However, mostly these works are limited in providing real time solution for the detection activities. Therefore, we are currently working toward the Internet of Things (IoT) based solution for the human posture recognition. To achieve the objective, in the first phase, dataset of 37419 samples has been prepared consisting of healthy and unhealthy postures with sitting, standing and sleeping activities. In the second phase, this dataset will be used to classify different human postures as healthy and unhealthy using machine learning algorithm.