This book provides an extensive knowledge of the most important aspects of Wireless Sensor Networks, especially the data collection performance in WSNs.The primary goal of optimization is to minimize the traveling distance by the robot. The problem can be regarded as a special case of the Travelling Salesman Problem with Neighborhoods (TSPN), tiny sensor nodes, equipped with sensing, communication capabilities and computation can be deployed in large numbers in geographical areas to monitor, detect and report events. The problem of irregularities detection is to find those sensory values that deviate significantly from the norm. This problem is important in the sensor network setting because it can be used to identify abnormal or interesting events or faulty sensors. A new approach named pattern variation discovery is used to solve this problem.Detection of irregularities is tightly interrelated to modeling of sensor data. Therefore, we propose to detect irregular single-attribute sensor data with respect to time or space by building models. This problem is important in the sensor network setting because it can be used to identify abnormal or interesting events or faulty sensors.
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Dr.Mohd Muntjir is working in College of Computers and Information Technology Taif University.He received his M.C.A.degree from H.N.B.Garhwal University Uttarakhand India and Ph.D. degree in Computer Science from OPJS University, Rajasthan India.He is a member of professional societies like ACM, IEEE, IAENG, IRED, ISRD,VAS,IJETAE,CSTA.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides an extensive knowledge of the most important aspects of Wireless Sensor Networks, especially the data collection performance in WSNs.The primary goal of optimization is to minimize the traveling distance by the robot. The problem can be regarded as a special case of the Travelling Salesman Problem with Neighborhoods (TSPN), tiny sensor nodes, equipped with sensing, communication capabilities and computation can be deployed in large numbers in geographical areas to monitor, detect and report events. The problem of irregularities detection is to find those sensory values that deviate significantly from the norm. This problem is important in the sensor network setting because it can be used to identify abnormal or interesting events or faulty sensors. A new approach named pattern variation discovery is used to solve this problem.Detection of irregularities is tightly interrelated to modeling of sensor data. Therefore, we propose to detect irregular single-attribute sensor data with respect to time or space by building models. This problem is important in the sensor network setting because it can be used to identify abnormal or interesting events or faulty sensors. 244 pp. Englisch. Seller Inventory # 9783330047457
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Muntjir MohdDr.Mohd Muntjir is working in College of Computers and Information Technology Taif University.He received his M.C.A.degree from H.N.B.Garhwal University Uttarakhand India and Ph.D. degree in Computer Science from OPJS Uni. Seller Inventory # 151234453
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Taschenbuch. Condition: Neu. Data Collection Performance in WSNs by Pattern Variation Discovery | Wireless Sensor Networks | Mohd Muntjir | Taschenbuch | 244 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330047457 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 108575244
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides an extensive knowledge of the most important aspects of Wireless Sensor Networks, especially the data collection performance in WSNs.The primary goal of optimization is to minimize the traveling distance by the robot. The problem can be regarded as a special case of the Travelling Salesman Problem with Neighborhoods (TSPN), tiny sensor nodes, equipped with sensing, communication capabilities and computation can be deployed in large numbers in geographical areas to monitor, detect and report events. The problem of irregularities detection is to find those sensory values that deviate significantly from the norm. This problem is important in the sensor network setting because it can be used to identify abnormal or interesting events or faulty sensors. A new approach named pattern variation discovery is used to solve this problem.Detection of irregularities is tightly interrelated to modeling of sensor data. Therefore, we propose to detect irregular single-attribute sensor data with respect to time or space by building models. This problem is important in the sensor network setting because it can be used to identify abnormal or interesting events or faulty sensors.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 244 pp. Englisch. Seller Inventory # 9783330047457
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides an extensive knowledge of the most important aspects of Wireless Sensor Networks, especially the data collection performance in WSNs.The primary goal of optimization is to minimize the traveling distance by the robot. The problem can be regarded as a special case of the Travelling Salesman Problem with Neighborhoods (TSPN), tiny sensor nodes, equipped with sensing, communication capabilities and computation can be deployed in large numbers in geographical areas to monitor, detect and report events. The problem of irregularities detection is to find those sensory values that deviate significantly from the norm. This problem is important in the sensor network setting because it can be used to identify abnormal or interesting events or faulty sensors. A new approach named pattern variation discovery is used to solve this problem.Detection of irregularities is tightly interrelated to modeling of sensor data. Therefore, we propose to detect irregular single-attribute sensor data with respect to time or space by building models. This problem is important in the sensor network setting because it can be used to identify abnormal or interesting events or faulty sensors. Seller Inventory # 9783330047457
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