Shinichi Minamimoto, S. Fujii, H. Yamaguchi, T. Higashino
{"title":"使用移动节点的位置和通信历史生成本地地图","authors":"Shinichi Minamimoto, S. Fujii, H. Yamaguchi, T. Higashino","doi":"10.1109/PERCOM.2010.5466999","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an algorithm to estimate 2D shapes and positions of obstacles such as buildings using GPS and wireless communication history of mobile nodes. Our algorithm enables quick recognition of geography, which is required in broader types of activities such as rescue activities in emergency situations. Nevertheless, detailed building maps might not be immediately available in private regions such as large factories, warehouses and universities, or prepared maps might not be effective due to collapse of buildings or roads in disaster situations. Some methodologies adopt range measurement sensors like infra-red and laser sensors or cameras. However, they require dedicated hardware and actions for the measurement. Meanwhile, the proposed method can create a rough 2D view of buildings and roads using only wireless communication history between mobile nodes and position history from GPS receivers. The results from the experiment conducted in 150m×190m region on our university campus assuming rescue and treatment actions by 15 members have shown that our method could generate a local map with 85% accuracy within 350 seconds. We have also validated the performance of our algorithm by simulations with various settings.","PeriodicalId":207774,"journal":{"name":"2010 IEEE International Conference on Pervasive Computing and Communications (PerCom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Local map generation using position and communication history of mobile nodes\",\"authors\":\"Shinichi Minamimoto, S. Fujii, H. Yamaguchi, T. Higashino\",\"doi\":\"10.1109/PERCOM.2010.5466999\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an algorithm to estimate 2D shapes and positions of obstacles such as buildings using GPS and wireless communication history of mobile nodes. Our algorithm enables quick recognition of geography, which is required in broader types of activities such as rescue activities in emergency situations. Nevertheless, detailed building maps might not be immediately available in private regions such as large factories, warehouses and universities, or prepared maps might not be effective due to collapse of buildings or roads in disaster situations. Some methodologies adopt range measurement sensors like infra-red and laser sensors or cameras. However, they require dedicated hardware and actions for the measurement. Meanwhile, the proposed method can create a rough 2D view of buildings and roads using only wireless communication history between mobile nodes and position history from GPS receivers. The results from the experiment conducted in 150m×190m region on our university campus assuming rescue and treatment actions by 15 members have shown that our method could generate a local map with 85% accuracy within 350 seconds. We have also validated the performance of our algorithm by simulations with various settings.\",\"PeriodicalId\":207774,\"journal\":{\"name\":\"2010 IEEE International Conference on Pervasive Computing and Communications (PerCom)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Pervasive Computing and Communications (PerCom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PERCOM.2010.5466999\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Pervasive Computing and Communications (PerCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERCOM.2010.5466999","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Local map generation using position and communication history of mobile nodes
In this paper, we propose an algorithm to estimate 2D shapes and positions of obstacles such as buildings using GPS and wireless communication history of mobile nodes. Our algorithm enables quick recognition of geography, which is required in broader types of activities such as rescue activities in emergency situations. Nevertheless, detailed building maps might not be immediately available in private regions such as large factories, warehouses and universities, or prepared maps might not be effective due to collapse of buildings or roads in disaster situations. Some methodologies adopt range measurement sensors like infra-red and laser sensors or cameras. However, they require dedicated hardware and actions for the measurement. Meanwhile, the proposed method can create a rough 2D view of buildings and roads using only wireless communication history between mobile nodes and position history from GPS receivers. The results from the experiment conducted in 150m×190m region on our university campus assuming rescue and treatment actions by 15 members have shown that our method could generate a local map with 85% accuracy within 350 seconds. We have also validated the performance of our algorithm by simulations with various settings.