{"title":"流检测室内运动的框架","authors":"K. Curran","doi":"10.12928/telkomnika.v16i2.7393","DOIUrl":null,"url":null,"abstract":"There are many advantages to being able to track in real-time the movement of things or humans. This is especially important in tracking goods in the supply chain, in security and also in health and safety. The Global Positioning Satellite (GPS) system works well in outdoor environments but it cannot track items indoors. There is also the problem of power hungry sensor chips inherent in some GPS trackers. Mobile Cellular triangulation also works well for many outdoor solutions but problems with cost, accuracy and reliability make it difficult to deploy for indoor tracking scenarions. The levels of accuracy can vary by up to 50 meters which hinder its ability for adoption in many use case scenarios. There are also problems with poor cellular coverage in rural areas. Solutions built on WiFi–the IEEE 802.11 standard overcome many of these issues. WiFi location tracking works via sampling of the received signal strength (RSS) which along with triangulation and prior mapping allows systems to locate items or humans with fine-granularity. This WiFi fingerprinting is a viable cost-effective approach to determining movement within indoor enviroments. This paper presents an overview of popular techniques and off-the-shelf solutions which can be used to determine movement of people and objects indoors. We outline the Locator frameworks which is built on both active and passive indoor localisation techniques for tracking movement within indoor environments.","PeriodicalId":414053,"journal":{"name":"TELKOMNIKA : Indonesian Journal of Electrical Engineering","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Stream a Framework for Detecting Movement Indoors\",\"authors\":\"K. Curran\",\"doi\":\"10.12928/telkomnika.v16i2.7393\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are many advantages to being able to track in real-time the movement of things or humans. This is especially important in tracking goods in the supply chain, in security and also in health and safety. The Global Positioning Satellite (GPS) system works well in outdoor environments but it cannot track items indoors. There is also the problem of power hungry sensor chips inherent in some GPS trackers. Mobile Cellular triangulation also works well for many outdoor solutions but problems with cost, accuracy and reliability make it difficult to deploy for indoor tracking scenarions. The levels of accuracy can vary by up to 50 meters which hinder its ability for adoption in many use case scenarios. There are also problems with poor cellular coverage in rural areas. Solutions built on WiFi–the IEEE 802.11 standard overcome many of these issues. WiFi location tracking works via sampling of the received signal strength (RSS) which along with triangulation and prior mapping allows systems to locate items or humans with fine-granularity. This WiFi fingerprinting is a viable cost-effective approach to determining movement within indoor enviroments. This paper presents an overview of popular techniques and off-the-shelf solutions which can be used to determine movement of people and objects indoors. We outline the Locator frameworks which is built on both active and passive indoor localisation techniques for tracking movement within indoor environments.\",\"PeriodicalId\":414053,\"journal\":{\"name\":\"TELKOMNIKA : Indonesian Journal of Electrical Engineering\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"TELKOMNIKA : Indonesian Journal of Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12928/telkomnika.v16i2.7393\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"TELKOMNIKA : Indonesian Journal of Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12928/telkomnika.v16i2.7393","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
能够实时跟踪物体或人的运动有很多好处。这在跟踪供应链中的货物、安全以及健康和安全方面尤其重要。全球定位卫星(GPS)系统在室外环境下工作良好,但无法在室内跟踪物品。还有一些GPS跟踪器固有的耗电传感器芯片的问题。移动蜂窝三角测量也适用于许多室外解决方案,但成本、准确性和可靠性问题使其难以部署到室内跟踪场景中。精度水平可以相差50米,这阻碍了它在许多用例场景中的采用能力。此外,农村地区的手机覆盖率也很低。基于wi - fi (IEEE 802.11标准)的解决方案克服了许多这些问题。WiFi位置跟踪通过对接收到的信号强度(RSS)进行采样,再加上三角测量和预先映射,系统可以精确定位物品或人。这种WiFi指纹识别是一种可行的、经济有效的方法,可以确定室内环境中的运动。本文概述了流行的技术和现成的解决方案,可用于确定室内人员和物体的运动。我们概述了定位器框架,它建立在主动和被动室内定位技术上,用于跟踪室内环境中的运动。
There are many advantages to being able to track in real-time the movement of things or humans. This is especially important in tracking goods in the supply chain, in security and also in health and safety. The Global Positioning Satellite (GPS) system works well in outdoor environments but it cannot track items indoors. There is also the problem of power hungry sensor chips inherent in some GPS trackers. Mobile Cellular triangulation also works well for many outdoor solutions but problems with cost, accuracy and reliability make it difficult to deploy for indoor tracking scenarions. The levels of accuracy can vary by up to 50 meters which hinder its ability for adoption in many use case scenarios. There are also problems with poor cellular coverage in rural areas. Solutions built on WiFi–the IEEE 802.11 standard overcome many of these issues. WiFi location tracking works via sampling of the received signal strength (RSS) which along with triangulation and prior mapping allows systems to locate items or humans with fine-granularity. This WiFi fingerprinting is a viable cost-effective approach to determining movement within indoor enviroments. This paper presents an overview of popular techniques and off-the-shelf solutions which can be used to determine movement of people and objects indoors. We outline the Locator frameworks which is built on both active and passive indoor localisation techniques for tracking movement within indoor environments.