Software Lab - Practical Lab "Data Mining Techniques in Sensor Networks"
|Lecturer:||Univ.-Prof. Dr. rer. nat. T. Seidl
Dipl.-Ing. M. Hassani
Dipl.-Inform. S. Fries
Clustering is an established data mining technique for grouping data based on similarity. This technique is useful for many applications such as wireless sensor networks (WSNs). WSNs consist usually of sensor nodes which are energy, processing and storage limited devices. Sensor nodes are usually distributed over a certain area covered by the WSN to observe phenomena (light, temperature, humidity, ...) by collecting data. Physical clustering of sensor nodes aims at grouping together sensor nodes that are sensing correlated data and selecting one of them as a representative, while turning others off. This minimizes the energy consumption and thus extends the lifetime of the nodes. The aim of our software project is to use Java for implementing existing data mining techniques and an evaluation framework. After the implementation, the evaluation framework will be used to measure how fast the sensor network detects changes in the observed phenomenon (like spreading of fire events). Another requirement is calculating the energy consumption of the total sensor network when having such events. After attending this lab, the following skills are supposed to be gained: