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HGA-based Auto-tuning of Peltier coolers in PAIS project: New Environmental Monitoring and Early Wildfire Detection System

机译:基于HGA的PELIER冷却器的自动调整在PAI项目中:新的环境监测和早期野火检测系统

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This paper presents the PAIS system which is an innovative WSN (Wireless Sensor Network) for the environmental monitoring. The main goal of the PAIS system is to reduce the wildfire damages with early detection and suppression. Moreover, each PAIS node can integrate a number of heterogeneous sensors in order to operate a complete environmental monitoring. Usually the sensor nodes are located in wild areas and exposed to severe weather conditions, hence particular attention has been given to energy management, robustness and ruggedness to minimize maintenance costs and increase the dependability of the entire system. The fire detection is based on two infrared sensors whose accuracy is extremely affected by temperature. Hence, the sensor temperature is controlled by two Peltier coolers whose performances are automatically optimized with an innovative hybrid genetic algorithm. The proposed on-line hybrid optimization can be embedded as a fully-automated tool without any extrahardware the system. Experimental results prove the effectiveness of the proposed approach.
机译:本文介绍了PAI系统,该系统是一个用于环境监测的创新的WSN(无线传感器网络)。 PAI系统的主要目标是减少野火损害,早期检测和抑制。此外,每个PAI节点可以集成许多异构传感器,以便操作完整的环境监测。通常,传感器节点位于野外区域并暴露于恶劣天气条件,因此已经特别注意能量管理,稳健性和坚固性,以最大限度地减少维护成本并提高整个系统的可靠性。火灾检测基于两种红外传感器,其精度受温度极其影响。因此,传感器温度由两个珀耳帖冷却器控制,其性能通过创新的混合遗传算法自动优化。所提出的在线混合优化可以嵌入为完全自动化的工具,而没有任何外形软件。实验结果证明了提出的方法的有效性。

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