Abstract-We present AALO: a novel Activity recognition system for single person smart homes using Active Learning in the presence of Overlapped activities. AALO applies data mining techniques to cluster in-home sensor firings so that each cluster represents instances of the same activity. Users only need to label each cluster as an activity as opposed to labeling all instances of all activities. Once the clusters are associated to their corresponding activities, our system can recognize future activities. To improve the activity recognition accuracy, our system preprocesses raw sensor data by identifying overlapping activities. The evaluation of activity recognition performance on a 26-day dataset shows that compared to Naive Bayesian
An active learning approach for recognition in the presence of overlapping activities (AALO) first performs location based frequent item set mining to find the activity patterns and then DBSCAN clustering is applied to form the activity clusters REF .
AALO: Activity recognition in smart homes using Active Learning in the presence of Overlapped activities
2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops
2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops
Computer Science