The HKUST Frog Pond – A Case Study of Sensory Data Analysis

Many sensor network applications are data-centric, and data analysis plays an important role in these applications. However, it is a challenging task to find out what specific problems and requirements sensory data analysis will face, because these applications are tightly embedded in the physical world and the sensory data reflect the physical phenomena being monitored. In this paper, we propose to use field studies as an alternative for identifying these problems and requirements. Specifically, we deployed an experimental sensor network for monitoring the frog pond in our university and analyzed the collected sensory data. We present our methodology of sensory data collection and analysis. We also discuss preliminary analytical results from the collected sensory data, together with our generalization for similar sensor network applications. We find that this case study helped us identify and understand several problems, either general or specific, in real-world sensor network application deployment and sensory data analysis.