{"title":"Experimental analysis of RSSI-based distance estimation for wireless sensor networks","authors":"R. Mahapatra, N. Shet","doi":"10.1109/DISCOVER.2016.7806221","DOIUrl":null,"url":null,"abstract":"Research in Wireless Sensor Networks (WSNs) has revealed the location information of the sensor nodes seems to be the critical and the most important aspect, for the applications like environment monitoring, object tracking, health care etc. Estimation accuracy is needed in these kind of applications. In general, Signal strength decreases with the increase in distance. Hence the correlation that exists between the RSSI (Received Signal Strength Indication) value and distance is the key parameter for the ranging and localization of WSNs. This paper presents a model based on RSSI, which provides the distance estimation between sensor nodes in WSNs. Analysis of the model and performance evaluation is done in a real system, deployed in indoor environment using IRIS mote. Results of these evaluation would help to achieve accuracy in location estimation of WSNs.","PeriodicalId":383554,"journal":{"name":"2016 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DISCOVER.2016.7806221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Research in Wireless Sensor Networks (WSNs) has revealed the location information of the sensor nodes seems to be the critical and the most important aspect, for the applications like environment monitoring, object tracking, health care etc. Estimation accuracy is needed in these kind of applications. In general, Signal strength decreases with the increase in distance. Hence the correlation that exists between the RSSI (Received Signal Strength Indication) value and distance is the key parameter for the ranging and localization of WSNs. This paper presents a model based on RSSI, which provides the distance estimation between sensor nodes in WSNs. Analysis of the model and performance evaluation is done in a real system, deployed in indoor environment using IRIS mote. Results of these evaluation would help to achieve accuracy in location estimation of WSNs.