IEEE Transactions on Instrumentation and Measurement · 2009 · 242 citations · 13 references
EngineeringEnvironmental EngineeringComputer NetworksEnvironmental MonitoringSensorsAir QualityGas SensorsHumidity SensorsSensor NetworksSmart SensorsWireless Sensor NetworksAir Quality Sensor NetworksEnvironmental Monitoring NetworksGas Concentration MonitoringGas Detection SystemsPower ConsumptionRoom Temperature Gas SensorsSensor ArraysWireless Gas Sensors
The paper proposes a network for indoor and outdoor air quality monitoring. The network uses tin dioxide sensor arrays in each node, connected via wired or wireless links to a central unit, and applies MISO neural networks to compensate temperature and humidity effects for accurate gas concentration readings. The study discusses anomalous node operation and power consumption.
This paper presents a network for indoor and outdoor air quality monitoring. Each node is installed in a different room and includes tin dioxide sensor arrays connected to an acquisition and control system. The nodes are hardwired or wirelessly connected to a central monitoring unit. To increase the gas concentration measurement accuracy and to prevent false alarms, two gas sensor influence quantities, i.e., temperature and humidity, are also measured. Advanced processing based on multiple-input-single-output neural networks is implemented at the network sensing nodes to obtain temperature and humidity compensated gas concentration values. Anomalous operation of the network sensing nodes and power consumption are also discussed.
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