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In recent years, the design and the fabrication of satisfactory air monitoring systems have been a focus of attention in growing reports of health diseases allied to poor atmospheric quality levels [1-9]. Identify pollutants in the air and defining polluted locations adopting an air monitoring system is paramount as the preliminary process of standard air-quality improvement techniques (e.g. improved ventilation, air cleaning and air sanitation ) [10,11]. At the same time recent advances in micro-electro-mechanical systems (MEMS), electrochemical gas sensors and wireless sensor network (WSN) technology have allowed the creation of a low-power, low-cost air pollutant monitoring system and its placement in real environments [12-24]. Moreover, the combination of an air monitoring system with remote wireless sensor networks technology will shorten installation prices enabling at the same time the rapid and simple reshaping of the data acquisition/control systems. In addition, networked air pollutant monitoring grants low-cost and continuous observation. However, remote monitoring needs rugged and reliable sensor nodes to integrated in a potentially wide and distributed net. Crucial issues for these wireless node developments is that they require high levels of power-efficiency for autonomous operation, in which it is reasonable that nodes will need deployment for very long periods (i.e. years) since the cost associate with battery replacement would eventually become impractical or to high. This can definitely be presented as a “set and forget” scenario. In a first approach, batteries seem to insure the optimum source of energy for wireless sensor systems adopting commercial battery technologies giving powerful energy capacities i... ... middle of paper ... ...are ongoing to extract power from the environment using energy scavenging (also harvesting) techniques [25-35]. The following energy harvesting techniques can be mentioned: the vibration/motion, the thermal gradients, the radio frequency signals and the solar energy. This paper addresses some of the key issues relating to the delivery of autonomous power for wireless sensor systems with the aim to develop a multi-parametric smart SENNO (SENsor NOde) dedicated to air quality monitoring systems. This paper is structured as follows: Section II presents related work in the field of air quality monitoring. The design goals and system configuration are discussed in Section III. Section IV describes the implementation of SENNO and first experimental results. In section V future work is reported while section VI and VII (acknowledgments and conclusion) complete the paper.

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