Deep learning (DL) is becoming popular among HAR researchers due to its outstanding performance over conventional ML techniques. The use of sensors in the field of HAR opens new avenues for machine learning (ML) researchers to accurately recognize human activities. These sensors measure various aspects of an object, and are easy to use with less cost. accelerometer, gyroscope, GPS, compass, camera, microphone etc. The latest smart gadgets are equipped with most of the wearable sensors i.e. The ubiquitous nature of sensors makes them a good choice to use for activity recognition. Human activity recognition (HAR) is a renowned research field in recent years due to its applications such as physical fitness monitoring, assisted living, elderly–care, biometric authentication and many more.
