Human activity detection is one of the challenging job, however, artificial intelligence made it easier. This detection is more useful in surveillance and monitoring purposes. The dataset with 6 activities is considered for training, which includes boxing, hand waving, hand clapping, jogging, running, walking.

Deep learning algorithm Convolutional Neural Network (CNN) is used for activity classification project. The accuracy of the model is as high as 50%. Source code execution needs keras and tensorflow environment. The demo of the activity recognition is can be seen below

More works on human monitoring is available are

Helmet wear detection using artificial intelligence

Human face emotion detection by deep learning

Driver drowsiness detection by deep learning model

Face detection and attendance monitoring through artificial intelligence

Human Speech emotion detection by deep learning

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