Data Collection in Wireless Sensor Networks for Noise Pollution Monitoring

Focusing on the assessment of environmental noise pollution in urban areas, we provide qualitative considerations and experimental results to show the feasibility of wireless sensor networks to be used in this context. To select the most suitable data collection protocol for the speci c noise monitoring application scenario, we evaluated the energy consumption performances of the CTP (Collection Tree Protocol) and DMAC protocols. Our results show that CTP, if used enabling the LPL (Low Power Listening) option, provides the better performances trade-o for noise monitoring applications. 1 Environmental noise monitoring Conservative estimations give in about 300 millions the number of citizens within the European Community that are exposed to alarming levels of noise pollution [1]. Raising the public's awareness of this problem, the Directive 2002/49/EC of the European Parliament has made the avoidance, prevention, and reduction of environmental noise a prime issue in European policy. To better assess the extension of the problem, the European Commission required member states to regularly provide an accurate mapping of environmental noise levels for all urban areas with more than 250′000 inhabitants. While current noise maps are mostly based on sparse data and ad-hoc noise propagation models, a recent position paper by the Commission has stressed that every e ort should be made to obtain accurate real data on noise sources, [2, p.6]. The demand for accurate data about noise exposure levels will increase dramatically, as this statement makes its way into mandatory regulation. Nowadays noise measurements in urban areas are mainly carried out by designated o cers that collect data at a location of interest for successive analysis and storage, using a sound level meter or similar device. This manual collection method does not scale as the demand for higher ? Partially supported by the Swiss National Science Foundation (NCCR-MICS, grant number 5005-67322). ?? Partially supported by the FRONTS FET Project (215270).