The high flexibility of WSNs makes it possible to deploy nodes swiftly in a disaster spot, and the low cost of the sensing node provides the possibility to control the cost of AT monitoring at an acceptable level.ĭue to these advantages of WSNs, we established a meteorological WSN using our own sensing nodes to collect data of AT and other meteorological factors in a practical environment, involving our campus and other weather stations of meteorological departments. During the last decade, WSNs have been broadly utilized in various fields, including air temperature observation, water monitoring, forest monitoring, industrial monitoring, agriculture monitoring, battlefield surveillance, intelligent transportation, smart homes, animal behavior monitoring and disaster prevention. In order to reduce the cost and to advance the flexibility of AT observation, wireless sensor networks (WSNs) have been take into consideration.
It accordingly becomes challenging when applying a high-density AWS system for weather disaster monitoring. Plus, an AWS will cost more to guarantee the accuracy of AT sensing due to the requirement of additional facilities, such as a thermometer screen. HMP45D is a typical AT sensor used in AWS with its price ranging from 500 to 600 dollars. However, a meteorological sensor costs too much to be applied in a large-scale scenario. Based on the use of meteorological temperature sensors, accurate AT data can be collected. In recent years, numerous approaches have been presented for AT monitoring, in which a conventional scheme, called automatic weather stations (AWS), has been applied widely in the meteorological departments all over the world. The prosperity of sensors and automated devices has fostered the feasibility of automatic meteorological observation applications, in which air temperature (AT) is regarded as one of the most significant meteorological factors. Thus, it is imperative for us to take drastic measures by monitoring meteorological factors and forecasting weather disasters. Unexpected meteorological calamities, such as floods, bring much damage to our community and ourselves. Meteorology monitoring is highly required in many domains, e.g., weather forecasting, agricultural, traffic, etc. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE) and SR. Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. Previous research has confirmed that there is a close relation between AT and solar radiation (SR). However, the temperature sensor on the sensing node can be easily influenced by environmental factors. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS). Air temperature (AT) is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc.
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