H. Y. Shwe, Chenchao Wang, P. Chong, Arun K. Kumar
{"title":"基于鲁棒立方的无线传感器网络三维定位","authors":"H. Y. Shwe, Chenchao Wang, P. Chong, Arun K. Kumar","doi":"10.4236/WSN.2013.59020","DOIUrl":null,"url":null,"abstract":"The rapid progress of wireless communication and the availability of \nmany small-sized, light-weighted and low-cost communication and computing devices \nnowadays have greatly impacted the development of wireless sensor network. \nLocalization using sensor network has attracted much attention for its \ncomparable low-cost and potential use with mon- itoring and \ntargeting purposes in real and hostile application scenarios. Currently, there \nare many available approaches to locating persons/things based on global \npositioning system (GPS) and radio-frequency identification (RFID) technologies. \nHowever, in some application scenario, e.g., disaster rescue application, such \nlocalization devices may be damaged and may not provide the location \ninformation of the survivors. The main goal of this paper is to design and develop a \nrobust localization technique for human existence detection in case of \ndisasters such as earthquake or fire. In this paper, we propose a 3-D \nlocalization technique based on the hop-count data collected from sensor \nanchors to estimate the location of the activated sensor mote in 3-D coordination. \nOur algorithm incorporates two salient features, cubic-based output \nand event-triggering mechanism, to guarantee both improved accuracy and power efficiency. Both simulation and experimental results indicate \nthat the proposed algorithm can improve the localization precision of the human \nexistence and work well in real environment.","PeriodicalId":58712,"journal":{"name":"无线传感网络(英文)","volume":"48 1","pages":"169-179"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Robust Cubic-Based 3-D Localization for Wireless Sensor Networks\",\"authors\":\"H. Y. Shwe, Chenchao Wang, P. Chong, Arun K. Kumar\",\"doi\":\"10.4236/WSN.2013.59020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid progress of wireless communication and the availability of \\nmany small-sized, light-weighted and low-cost communication and computing devices \\nnowadays have greatly impacted the development of wireless sensor network. \\nLocalization using sensor network has attracted much attention for its \\ncomparable low-cost and potential use with mon- itoring and \\ntargeting purposes in real and hostile application scenarios. Currently, there \\nare many available approaches to locating persons/things based on global \\npositioning system (GPS) and radio-frequency identification (RFID) technologies. \\nHowever, in some application scenario, e.g., disaster rescue application, such \\nlocalization devices may be damaged and may not provide the location \\ninformation of the survivors. The main goal of this paper is to design and develop a \\nrobust localization technique for human existence detection in case of \\ndisasters such as earthquake or fire. In this paper, we propose a 3-D \\nlocalization technique based on the hop-count data collected from sensor \\nanchors to estimate the location of the activated sensor mote in 3-D coordination. \\nOur algorithm incorporates two salient features, cubic-based output \\nand event-triggering mechanism, to guarantee both improved accuracy and power efficiency. Both simulation and experimental results indicate \\nthat the proposed algorithm can improve the localization precision of the human \\nexistence and work well in real environment.\",\"PeriodicalId\":58712,\"journal\":{\"name\":\"无线传感网络(英文)\",\"volume\":\"48 1\",\"pages\":\"169-179\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"无线传感网络(英文)\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.4236/WSN.2013.59020\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"无线传感网络(英文)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.4236/WSN.2013.59020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust Cubic-Based 3-D Localization for Wireless Sensor Networks
The rapid progress of wireless communication and the availability of
many small-sized, light-weighted and low-cost communication and computing devices
nowadays have greatly impacted the development of wireless sensor network.
Localization using sensor network has attracted much attention for its
comparable low-cost and potential use with mon- itoring and
targeting purposes in real and hostile application scenarios. Currently, there
are many available approaches to locating persons/things based on global
positioning system (GPS) and radio-frequency identification (RFID) technologies.
However, in some application scenario, e.g., disaster rescue application, such
localization devices may be damaged and may not provide the location
information of the survivors. The main goal of this paper is to design and develop a
robust localization technique for human existence detection in case of
disasters such as earthquake or fire. In this paper, we propose a 3-D
localization technique based on the hop-count data collected from sensor
anchors to estimate the location of the activated sensor mote in 3-D coordination.
Our algorithm incorporates two salient features, cubic-based output
and event-triggering mechanism, to guarantee both improved accuracy and power efficiency. Both simulation and experimental results indicate
that the proposed algorithm can improve the localization precision of the human
existence and work well in real environment.