Samaneh Zolfaghari - Department of Computer Engineering Alzahra University Tehran, Iran
Raziyeh Zall - Department of Computer Engineering Alzahra UniversityTehran, Iran
Mohammad Reza Keyvanpour - Department of Computer Engineering Alzahra University Tehran, Iran

Ambient Intelligence is a new paradigm in information technology to empower people. Such a paradigm that highlights human interaction with machines makes smart technologies a good candidate for development of various real-life solutions in the field of health care, including human activity recognition in smart homes. Since the description of user activity plays an important role in a smart environment, recognition and tracking user activities of daily living can provide unprecedented opportunities for health monitoring, applications, and assistive life utilities, particularly for the elderly, disabled, and people with dementia or Alzheimer disease. Due to sensor data nature with different sampling rates and complex correlations, significant challenges arise due to storage, presentation, exchange and manipulate of this data category. One rational solution to solve such challenges is to use techniques which are based on Semantic Web and Ontology. Recently there have been large varieties of proposed approaches in which they use such techniques. The vast amount of human activity recognition in smart home while using Ontological approaches has made it difficult to make adequate comparisons and accurate assessment. This article presents a framework for analyzing each of the approaches proposed in this regard. Using the proposed SOnAr framework for Ontology-based activity recognition approaches can be effective in analyzing and evaluating different methods in different application areas and dealing with various challenges.

Human Activity Recognition, Semantic Web, Ambient Intelligence,Context awareness, Pervasive Computing, Smart homes