Activity recognition is an important technology in pervasive computing because it can be applied to many real-life, human-centric problems such as elder care and health care. Successful research has so far focused on recognizing simple human activities. Recognizing complex activities remains a challenging and active area of research. Specifically, the nature of human activities poses the following challenges:
- Recognizing concurrent activities: People can do several activities at the same time. For example, people can watch television while talking to their friends. These behaviors should be recognized using a different approach from that for sequential activity.
- Recognizing interleaved activities: Certain real life activities may be interleaved. For instance, while cooking, if there is a call from a friend, people pause cooking for a while and after talking to their friend, they come back to the kitchen and continue to cook.
- Ambiguity of interpretation:Depending on the situation, the interpretation of similar activities may be different. For example, an activity “open refrigerator” can belong to several activities, such as “cooking” or “cleaning”.
- Multiple residents: In many environments more than one resident is present. The activities that are being performed by the residents in parallel need to be recognized, even if the activity is performed together by the residents in a group.
Once activities are discovered, they can provide the basis for a model to recognize the activity, track its occurrence, and even use the information to assess an individual's wellbeing or provide activity-aware services. These activity discovery and recognition technologies are thus valuable for providing pervasive assistance in an individual's everyday environments.
Source: E. Kim, S. Helal and D. Cook:" Human Activity Recognition and Pattern Discovery"
