A Survey on Human Activity Identification using Machine Learning and Deep Learning Approach
Abstract: Human activity recognition (HAR) is very interesting and active area of research era from past one or two decades. HAR is also an impotent research topic in computer vision field. It is extensively utilized in various fields such as remote monitoring, person to person interaction system, health care monitoring, robotics and so on. The major motivation of this survey paper is to introduce various human activities in the series of video utilizing different postures video done by the people. Creation of data is done by the utilization of static kinetic and wearable sensor devices which are collect the data using accelerometer, magneto meter and gyroscope. Analysis of human activity is to carry out using machine learning and deep learning techniques named SVM, Logistic regression, KNN, Random Forest, Navie Byes, CNN, LSTM and so many. In this paper, monitoring of activities is possible by the use of modern available Kinetic, accelerometer and gyroscope sensor device with GPS and vision based technology.
Keywords: Human Activity recognition, Accelerometer, Gyroscope, Artificial intelligence, Machine learning, NNN
How to Cite?: Shiv Shankar Kumar, Dr. Ayonija Pathre, "A Survey on Human Activity Identification using Machine Learning and Deep Learning Approach", Volume 11 Issue 12, December 2022, International Journal of Science and Research (IJSR), Pages: 33-37, https://www.ijsr.net/getabstract.php?paperid=SR221128143302, DOI: https://dx.doi.org/10.21275/SR221128143302