In the realm of scientific research, the domain of Human Activity Recognition (HAR) stands as a well-established field, tirelessly committed to the task of automating the identification and categorization of human activities. This endeavor relies on an array of sensors as data sources, nurturing a multitude of applications across diverse domains such as healthcare, sports analysis, surveillance, and human-computer interaction. Within the pages of this comprehensive survey paper, our purpose is to embark on a journey through the contemporary landscape of HAR. In this paper, we shall examine on meaningful components, including sensor-based modalities that incorporate different types of sensors being used. The various kind of feature extractors used to find meaningful patterns from the input raw data and the kind of various classification algorithm developed to recognize these human activities along with measuring parameters to measure the efficiency of the HAR system deployed in real time environment.