Mining Sensor Data in Smart Environment for Temporal Activity Prediction

Technological enhancements aid development and advanced research in smart homes and intelligent environments. The temporal nature of data collected in a smart environment provides us with a better understanding of patterns over time. Prediction using temporal relations is a complex and challenging task. To solve this problem, we suggest a solution using probability based model on temporal relations. Temporal pattern discovery based on modified Allen’s temporal relations [8] has helped discover interesting patterns and relations on smart home datasets [17]. This paper describes a method of discovering temporal relations in smart home datasets and applying them to perform activity prediction on the frequently-occurring events. We also include experimental results, performed on real and synthetic datasets.