Department of Computer Engineering and Computational Sciences
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Browsing Department of Computer Engineering and Computational Sciences by Subject "Air monitoring"
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Item Feasibility of air quality monitoring systems based on environmental energy harvesting(Institute of Electrical and Electronics Engineers Inc., 2015) Touati, Farid; Galli, Alessio; Crescini, Damiano; Crescini, Paolo; Mnaouer, Adel BenCapillary wireless sensor networks dedicated to air quality monitoring have provided essential information on hazardous air condition, generating early warnings to prevent danger situation for human health. The arising problem connected to capillary networks is the adoption of environmental energy as primary and/or unique energy source instead of the replacement of hundreds or even thousands of batteries on a regular basis that leads to high costs and practical problems of devices management. Aim of this paper is to presents a multiparametric sensor node for air quality monitoring, able to work without battery and human intervention, harvesting energy from the surrounding environment for perpetual operation. A complete autonomy system has been designed, experimental results of the harvest energy section and the budget allocation of the power consumption of the system are presented. Moreover the paper shows the experimental results of the studies conducted on the sensors section. A tailored calibration process for the sensors and the energy recovery section could effectively lead the system to trace the air quality levels in indoor and outdoor application, in a sort of 'set and forget' scenario. approach could effectively report and trace air quality levels. © 2015 IEEE.Item Renewable energy-harvested sensor systems for air quality monitoring(Institute of Electrical and Electronics Engineers Inc., 2014) Touati, Farid; Legena, Claudio; Galli, Alessio; Crescini, Damiano; Crescini, Paolo; Mnaouer, Adel BenWireless sensor networks (WSNs) devoted to environmental monitoring has preponderantly assumed the adoption of a portable and limited energy source, (e.g. lithium, alkaline, NiMH batteries), to support the sensor functionalities. The usage of environmental resources as energy booster is now rising up as a workable energy source dedicated to embedded and wireless computing systems where manual replacement of hundreds or even thousands of batteries on a regular basis is not practical. Consequently, substantial research efforts have been spent on designing energy-efficient smart sensor nodes and networks to maximize the lifetime of WSNs. However, in air quality monitoring systems sensors are required to operate for much longer durations (like years or even decades) after they are deployed. Following the above approach this paper presents SENNO (SENsor NOde), a renewable energy-harvested sensor node that intelligently manages energy transfer for continuous operation without human intervention during air quality monitoring. This paper discusses the challenges of designing an autonomous system powered by ambient energy harvesting. Preliminary results show that, the presented approach could effectively report and trace air quality levels. © 2014 IEEE.