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.
HGA-based Auto-tuning of peltier coolers in PAIS project: New environmental monitoring and early wildfire detection system / Giliberti, G.; Lorusso, G.; Marano, Giuseppe Carlo; Cascella, G. L.. - (2009), pp. 188-192. (Intervento presentato al convegno 3rd International Workshop on Advances in Sensors and Interfaces tenutosi a Trani nel 25-26 June 2009) [10.1109/IWASI.2009.5184793].
HGA-based Auto-tuning of peltier coolers in PAIS project: New environmental monitoring and early wildfire detection system
MARANO, Giuseppe Carlo;
2009
Abstract
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.Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2727684
Attenzione
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo