Abstract
The objective of this research paper is to analyse a dataset consist of, dataset consist of slog from accelerometer & gyroscope of a smartphone carried by diff men and women volunteers while doing activities using different machine learning analysed and compared in terms of precision & efficiency. We also try to see whether we can separate the individuals based on their walking styles and find any additional verdict Such insights can be utilized to implement real-time human asset monitoring in highly secure locations, track older citizens with movement disorders or illnesses for any issues based on movement patterns, and so on., decide whether an individual is fatigued or not, and so on. We discovered that our work has a recognition accuracy of over 94%.
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