[ { "key": "NRSFDKHC", "version": 4, "library": { "type": "group", "id": 221546, "name": "WSN Localization", "links": { "alternate": { "href": "https://www.zotero.org/groups/wsn_localization", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/221546/items/NRSFDKHC", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/wsn_localization/items/NRSFDKHC", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1619659, "username": "laltoaimy", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/laltoaimy", "type": "text/html" } } }, "creatorSummary": "Zhu et al.", "parsedDate": "2013", "numChildren": 0 }, "data": { "key": "NRSFDKHC", "version": 4, "itemType": "conferencePaper", "title": "A Localization Algorithm for Mobile Wireless Sensor Networks", "creators": [ { "creatorType": "author", "firstName": "Haiping", "lastName": "Zhu" }, { "creatorType": "author", "firstName": "Xiaoyong", "lastName": "Zhong" }, { "creatorType": "author", "firstName": "Qianhong", "lastName": "Yu" }, { "creatorType": "author", "firstName": "Yunlong", "lastName": "Wan" } ], "abstractNote": "Localization is very important for wireless sensor networks. Many applications require the location information. In this paper, we propose a range based Monte Carlo localization algorithm, which builds upon the Monte Carlo localization algorithm. We improve the localization accuracy and efficiency by introducing the RSSI (received signal strength indication) ranging technique, which is a low power, low cost and low complexity ranging method. The ranging error of RSSI is always very large and always varying with the change of the real environment. Although the low accuracy and high uncertainty of the range measurements would appear to make the localization more difficult, our approach exploits it to improve the accuracy and efficiency of localization. Simulation results show that its performance is better than some other localization algorithms.", "proceedingsTitle": "2013 Third International Conference on Intelligent System Design and Engineering Applications (ISDEA)", "conferenceName": "2013 Third International Conference on Intelligent System Design and Engineering Applications (ISDEA)", "publisher": "", "place": "", "date": "2013", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "81-85", "series": "", "seriesNumber": "", "DOI": "10.1109/ISDEA.2012.27", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Accuracy", "type": 1 }, { "tag": "Filtering", "type": 1 }, { "tag": "Mobile communication", "type": 1 }, { "tag": "Mobile computing", "type": 1 }, { "tag": "Mobility", "type": 1 }, { "tag": "Monte Carlo Localization", "type": 1 }, { "tag": "Monte Carlo methods", "type": 1 }, { "tag": "RSSI", "type": 1 }, { "tag": "distance measurement", "type": 1 }, { "tag": "localization accuracy", "type": 1 }, { "tag": "location information", "type": 1 }, { "tag": "low complexity ranging method", "type": 1 }, { "tag": "low cost ranging method", "type": 1 }, { "tag": "low power ranging method", "type": 1 }, { "tag": "mobile radio", "type": 1 }, { "tag": "mobile wireless sensor network", "type": 1 }, { "tag": "range based", "type": 1 }, { "tag": "range based Monte Carlo localization algorithm", "type": 1 }, { "tag": "range measurement", "type": 1 }, { "tag": "ranging error", "type": 1 }, { "tag": "ranging technique", "type": 1 }, { "tag": "received signal strength indication", "type": 1 }, { "tag": "wireless sensor networks", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2013-10-08T20:23:54Z", "dateModified": "2013-10-08T20:23:54Z" } }, { "key": "4F2FHX5B", "version": 4, "library": { "type": "group", "id": 221546, "name": "WSN Localization", "links": { "alternate": { "href": "https://www.zotero.org/groups/wsn_localization", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/221546/items/4F2FHX5B", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/wsn_localization/items/4F2FHX5B", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1619659, "username": "laltoaimy", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/laltoaimy", "type": "text/html" } } }, "creatorSummary": "Zhang and Yu", "parsedDate": "2010", "numChildren": 0 }, "data": { "key": "4F2FHX5B", "version": 4, "itemType": "journalArticle", "title": "LSWD: localization scheme for wireless sensor networks using directional antenna", "creators": [ { "creatorType": "author", "firstName": "Baoli", "lastName": "Zhang" }, { "creatorType": "author", "firstName": "Fengqi", "lastName": "Yu" } ], "abstractNote": "In this paper, the accuracy of location estimation of ad hoc deployed sensor nodes for a wireless sensor network in the presence of noisy environment and obstacle is discussed. Considering estimation accuracy, energy efficiency, and range independency, we propose a localization scheme using a mobile anchor node equipped with a directional antenna based on the geometry technique, called LSWD: Localization Scheme for Wireless Sensor Networks using Directional Antenna, this scheme make use of directional antenna concentrates energy on a particularly direction with high gain and narrow covering area. Without increasing hardware and computational complexity, sensor nodes estimate their positions using the minimum number of beacon information. Our localization scheme is verified by network simulation software. The result shows that the proposed localization algorithm has higher accuracy and energy efficiency than other localization schemes.", "publicationTitle": "IEEE Transactions on Consumer Electronics", "publisher": "", "place": "", "date": "2010", "volume": "56", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "2208-2216", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1109/TCE.2010.5681092", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "0098-3063", "archive": "", "archiveLocation": "", "shortTitle": "LSWD", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Accuracy", "type": 1 }, { "tag": "Algorithm design and analysis", "type": 1 }, { "tag": "Directional antennas", "type": 1 }, { "tag": "Estimation", "type": 1 }, { "tag": "Mobile communication", "type": 1 }, { "tag": "ad hoc deployed sensor nodes", "type": 1 }, { "tag": "ad hoc networks", "type": 1 }, { "tag": "beacon information", "type": 1 }, { "tag": "computational complexity", "type": 1 }, { "tag": "directional antenna", "type": 1 }, { "tag": "directive antennas", "type": 1 }, { "tag": "energy efficiency", "type": 1 }, { "tag": "estimation accuracy", "type": 1 }, { "tag": "geometry technique", "type": 1 }, { "tag": "localization scheme", "type": 1 }, { "tag": "mobile anchor node", "type": 1 }, { "tag": "mobile radio", "type": 1 }, { "tag": "network simulation software", "type": 1 }, { "tag": "range independency", "type": 1 }, { "tag": "wireless sensor network, localization, directional, antenna, geometry.", "type": 1 }, { "tag": "wireless sensor networks", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2013-10-08T20:23:49Z", "dateModified": "2013-10-08T20:23:49Z" } }, { "key": "K8WEZA9F", "version": 4, "library": { "type": "group", "id": 221546, "name": "WSN Localization", "links": { "alternate": { "href": "https://www.zotero.org/groups/wsn_localization", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/221546/items/K8WEZA9F", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/wsn_localization/items/K8WEZA9F", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1619659, "username": "laltoaimy", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/laltoaimy", "type": "text/html" } } }, "creatorSummary": "Monfared et al.", "parsedDate": "2012-08-19", "numChildren": 0 }, "data": { "key": "K8WEZA9F", "version": 4, "itemType": "conferencePaper", "title": "Range Free Localization of Wireless Sensor Networks Based on Sugeno Fuzzy Inference", "creators": [ { "creatorType": "author", "firstName": "Arbabi", "lastName": "Monfared" }, { "creatorType": "author", "firstName": "Mostafa Arbabi", "lastName": "Monfared" }, { "creatorType": "author", "firstName": "Reza", "lastName": "Abrishambaf" }, { "creatorType": "author", "firstName": "Sener", "lastName": "Uysal" } ], "abstractNote": "", "proceedingsTitle": "", "conferenceName": "SENSORCOMM 2012 , The Sixth International Conference on Sensor Technologies and Applications", "publisher": "", "place": "", "date": "2012/08/19", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "36-41", "series": "", "seriesNumber": "", "DOI": "", "ISBN": "978-1-61208-207-3", "citationKey": "", "url": "http://www.thinkmind.org/index.php?view=article&articleid=sensorcomm_2012_2_10_10038", "accessDate": "2013-10-04T16:43:36Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "www.thinkmind.org", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-10-08T20:23:45Z", "dateModified": "2013-10-08T20:23:45Z" } }, { "key": "BARIE7DQ", "version": 3, "library": { "type": "group", "id": 221546, "name": "WSN Localization", "links": { "alternate": { "href": "https://www.zotero.org/groups/wsn_localization", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/221546/items/BARIE7DQ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/wsn_localization/items/BARIE7DQ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1619659, "username": "laltoaimy", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/laltoaimy", "type": "text/html" } } }, "creatorSummary": "Li et al.", "parsedDate": "2013-02-05", "numChildren": 0 }, "data": { "key": "BARIE7DQ", "version": 3, "itemType": "journalArticle", "title": "A Novel Lightness Localization Algorithm Based on Anchor Nodes Equilateral Triangle Layout in WSNs", "creators": [ { "creatorType": "author", "firstName": "Dazhou", "lastName": "Li" }, { "creatorType": "author", "firstName": "Hai", "lastName": "Zhao" }, { "creatorType": "author", "firstName": "Jian", "lastName": "Zhu" }, { "creatorType": "author", "firstName": "Yuanguo", "lastName": "Bi" } ], "abstractNote": "Localization, which determines the geographical locations of sensors, is a crucial issue in wireless sensor networks. In this paper, we propose a novel lightweight equilateral triangle localization algorithm (LETLA) that accurately localizes sensors and minimizes the power consumption. In the LETLA, the approximate coordinates substituted for the real coordinates of the unknown node, and the corresponding optimization problem is formulated to minimize the estimation error. With the sequences that represent the ranking of distances from the anchors to the unknown node, a simple and robust technique is developed to quickly and efficiently estimate a region containing the approximate coordinates, and a condition under which the approximate error can be minimized is given. This condition employs a new geometric construct of anchor layout called equilateral triangle diagrams. Extensive simulations show that the LETLA performs better than other state-of-the-art approaches in terms of energy consumption with the same localization precision.", "publicationTitle": "International Journal of Distributed Sensor Networks", "publisher": "", "place": "", "date": "2013/02/05", "volume": "2013", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1155/2013/958912", "citationKey": "", "url": "http://www.hindawi.com/journals/ijdsn/2013/958912/abs/", "accessDate": "2013-10-04T16:21:18Z", "PMID": "", "PMCID": "", "ISSN": "1550-1329", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.hindawi.com", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2013-10-08T20:23:12Z", "dateModified": "2013-10-08T20:23:12Z" } }, { "key": "P9KMZJMQ", "version": 3, "library": { "type": "group", "id": 221546, "name": "WSN Localization", "links": { "alternate": { "href": "https://www.zotero.org/groups/wsn_localization", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/221546/items/P9KMZJMQ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/wsn_localization/items/P9KMZJMQ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1619659, "username": "laltoaimy", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/laltoaimy", "type": "text/html" } } }, "creatorSummary": "Larios et al.", "parsedDate": "2011", "numChildren": 0 }, "data": { "key": "P9KMZJMQ", "version": 3, "itemType": "conferencePaper", "title": "Locating sensors with fuzzy logic algorithms", "creators": [ { "creatorType": "author", "firstName": "D.F.", "lastName": "Larios" }, { "creatorType": "author", "firstName": "J.", "lastName": "Barbancho" }, { "creatorType": "author", "firstName": "F.J.", "lastName": "Molina" }, { "creatorType": "author", "firstName": "C.", "lastName": "Leon" } ], "abstractNote": "In a system formed by hundreds of sensors deployed in a huge area it is important to know the position where every sensor is. This information can be obtained using several methods. However, if the number of sensors is high and the deployment is based on ad-hoc manner, some auto-locating techniques must be implemented. In this paper we describe a novel algorithm based on fuzzy logic with the objective of estimating the location of sensors according to the knowledge of the position of some reference nodes. This algorithm, called LIS (Localization based on Intelligent Sensors) is executed distributively along a wireless sensor network formed by hundreds of nodes, covering a huge area. The evaluation of LIS is led by simulation tests. The result obtained shows that LIS is a promising method that can easily solve the problem of knowing where the sensors are located.", "proceedingsTitle": "Merging Fields Of Computational Intelligence And Sensor Technology (CompSens), 2011 IEEE Workshop On", "conferenceName": "Merging Fields Of Computational Intelligence And Sensor Technology (CompSens), 2011 IEEE Workshop On", "publisher": "", "place": "", "date": "2011", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "57-64", "series": "", "seriesNumber": "", "DOI": "10.1109/MFCIST.2011.5949514", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Accuracy", "type": 1 }, { "tag": "Base stations", "type": 1 }, { "tag": "Fuzzy systems", "type": 1 }, { "tag": "Hardware", "type": 1 }, { "tag": "LIS", "type": 1 }, { "tag": "Sensors", "type": 1 }, { "tag": "ad hoc networks", "type": 1 }, { "tag": "ad-hoc sensor deployment", "type": 1 }, { "tag": "fuzzy logic", "type": 1 }, { "tag": "fuzzy logic algorithms", "type": 1 }, { "tag": "intelligent sensors", "type": 1 }, { "tag": "localization based on intelligent sensors", "type": 1 }, { "tag": "protocols", "type": 1 }, { "tag": "sensor location", "type": 1 }, { "tag": "sensor placement", "type": 1 }, { "tag": "wireless sensor network", "type": 1 }, { "tag": "wireless sensor networks", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2013-10-08T20:22:56Z", "dateModified": "2013-10-08T20:22:56Z" } }, { "key": "P8WWQFKG", "version": 2, "library": { "type": "group", "id": 221546, "name": "WSN Localization", "links": { "alternate": { "href": "https://www.zotero.org/groups/wsn_localization", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/221546/items/P8WWQFKG", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/wsn_localization/items/P8WWQFKG", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1619659, "username": "laltoaimy", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/laltoaimy", "type": "text/html" } } }, "creatorSummary": "Gu et al.", "parsedDate": "2012", "numChildren": 0 }, "data": { "key": "P8WWQFKG", "version": 2, "itemType": "conferencePaper", "title": "Fuzzy logic based localisation in wireless sensor networks for disaster environments", "creators": [ { "creatorType": "author", "firstName": "Shuang", "lastName": "Gu" }, { "creatorType": "author", "firstName": "Yong", "lastName": "Yue" }, { "creatorType": "author", "firstName": "C.", "lastName": "Maple" }, { "creatorType": "author", "firstName": "Chengdong", "lastName": "Wu" } ], "abstractNote": "Progress in micro-electromechanical systems (MEMS) and radio frequency (RF) technology has fostered the development of wireless sensor networks (WSNs). Although WSNs have been successfully applied in built environments, their applications and benefits have not been fully explored in the areas of disaster recovery and rescuing. In this paper, a novel probabilistic fuzzy logic based Range-free localisation algorithm (PFRL) is proposed. The proposed algorithm is compared with other range free localisation algorithms. Simulation results demonstrate the accurate and effectiveness of the proposed algorithm.", "proceedingsTitle": "2012 18th International Conference on Automation and Computing (ICAC)", "conferenceName": "2012 18th International Conference on Automation and Computing (ICAC)", "publisher": "", "place": "", "date": "2012", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "1-5", "series": "", "seriesNumber": "", "DOI": "", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Accuracy", "type": 1 }, { "tag": "Algorithm design and analysis", "type": 1 }, { "tag": "MEMS", "type": 1 }, { "tag": "Mathematical model", "type": 1 }, { "tag": "PFRL", "type": 1 }, { "tag": "Probabilistic logic", "type": 1 }, { "tag": "RF technology", "type": 1 }, { "tag": "Sensors", "type": 1 }, { "tag": "WSN", "type": 1 }, { "tag": "WSNs", "type": 1 }, { "tag": "disaster environments", "type": 1 }, { "tag": "disaster recovery", "type": 1 }, { "tag": "disasters", "type": 1 }, { "tag": "fuzzy logic", "type": 1 }, { "tag": "fuzzy logic based localisation", "type": 1 }, { "tag": "localisatin", "type": 1 }, { "tag": "microelectromechanical systems", "type": 1 }, { "tag": "micromechanical devices", "type": 1 }, { "tag": "probabilistic fuzzy logic based range-free localisation algorithm", "type": 1 }, { "tag": "radiofrequency technology", "type": 1 }, { "tag": "sensor placement", "type": 1 }, { "tag": "wireless sensor networks", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2013-10-08T20:16:53Z", "dateModified": "2013-10-08T20:16:53Z" } }, { "key": "CTWV9NT4", "version": 2, "library": { "type": "group", "id": 221546, "name": "WSN Localization", "links": { "alternate": { "href": "https://www.zotero.org/groups/wsn_localization", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/221546/items/CTWV9NT4", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/wsn_localization/items/CTWV9NT4", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1619659, "username": "laltoaimy", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/laltoaimy", "type": "text/html" } } }, "creatorSummary": "Chenji and Stoleru", "parsedDate": "2013", "numChildren": 0 }, "data": { "key": "CTWV9NT4", "version": 2, "itemType": "journalArticle", "title": "Toward Accurate Mobile Sensor Network Localization in Noisy Environments", "creators": [ { "creatorType": "author", "firstName": "H.", "lastName": "Chenji" }, { "creatorType": "author", "firstName": "R.", "lastName": "Stoleru" } ], "abstractNote": "The node localization problem in mobile sensor networks has received significant attention. Recently, particle filters adapted from robotics have produced good localization accuracies in conventional settings. In spite of these successes, state-of-the-art solutions suffer significantly when used in challenging indoor and mobile environments characterized by a high degree of radio signal irregularity. New solutions are needed to address these challenges. We propose a fuzzy logic-based approach for mobile node localization in challenging environments. Localization is formulated as a fuzzy multilateration problem. For sparse networks with few available anchors, we propose a fuzzy grid-prediction scheme. The fuzzy logic-based localization scheme is implemented in a simulator and compared to state-of-the-art solutions. Extensive simulation results demonstrate improvements in the localization accuracy from 20 to 40 percent when the radio irregularity is high. A hardware implementation running on Epic motes and transported by iRobot mobile hosts confirms simulation results and extends them to the real world.", "publicationTitle": "IEEE Transactions on Mobile Computing", "publisher": "", "place": "", "date": "2013", "volume": "12", "issue": "6", "section": "", "partNumber": "", "partTitle": "", "pages": "1094-1106", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1109/TMC.2012.82", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1536-1233", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Accuracy", "type": 1 }, { "tag": "Epic motes", "type": 1 }, { "tag": "Equations", "type": 1 }, { "tag": "Mathematical model", "type": 1 }, { "tag": "Mobile communication", "type": 1 }, { "tag": "Mobile computing", "type": 1 }, { "tag": "Mobility", "type": 1 }, { "tag": "Node localization", "type": 1 }, { "tag": "Noise measurement", "type": 1 }, { "tag": "fuzzy grid-prediction scheme", "type": 1 }, { "tag": "fuzzy logic", "type": 1 }, { "tag": "fuzzy logic-based approach", "type": 1 }, { "tag": "fuzzy logic-based localization scheme", "type": 1 }, { "tag": "fuzzy multilateration problem", "type": 1 }, { "tag": "hardware implementation", "type": 1 }, { "tag": "iRobot mobile hosts", "type": 1 }, { "tag": "indoor environments", "type": 1 }, { "tag": "indoor radio", "type": 1 }, { "tag": "localization accuracies", "type": 1 }, { "tag": "mobile environments", "type": 1 }, { "tag": "mobile radio", "type": 1 }, { "tag": "mobile sensor network localization", "type": 1 }, { "tag": "node localization problem", "type": 1 }, { "tag": "noisy environments", "type": 1 }, { "tag": "particle filtering (numerical methods)", "type": 1 }, { "tag": "particle filters", "type": 1 }, { "tag": "radio signal irregularity", "type": 1 }, { "tag": "robotics", "type": 1 }, { "tag": "robots", "type": 1 }, { "tag": "sensor placement", "type": 1 }, { "tag": "sparse networks", "type": 1 }, { "tag": "wireless sensor networks", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2013-10-08T20:16:42Z", "dateModified": "2013-10-08T20:16:42Z" } } ]