Path Prediction Method for Effective Sensor Filtering in Sensor Registry System
The Internet of Things (IoT) has emerged and several issues have arisen in the area such as sensor registration and management, semantic interpretation and processing, and sensor searching and filtering in Wireless Sensor Networks (WSNs). Also, as the number of sensors in an IoT environment increase...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/613473 |
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| _version_ | 1849690440358428672 |
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| author | Sukhoon Lee Dongwon Jeong Doo-Kwon Baik Dae-Kyoo Kim |
| author_facet | Sukhoon Lee Dongwon Jeong Doo-Kwon Baik Dae-Kyoo Kim |
| author_sort | Sukhoon Lee |
| collection | DOAJ |
| description | The Internet of Things (IoT) has emerged and several issues have arisen in the area such as sensor registration and management, semantic interpretation and processing, and sensor searching and filtering in Wireless Sensor Networks (WSNs). Also, as the number of sensors in an IoT environment increases significantly, sensor filtering becomes more important. Many sensor filtering techniques have been researched. However most of them do not consider real-time searching and efficiency of mobile networks. In this paper, we suggest a path prediction approach for effective sensor filtering in Sensor Registry System (SRS). SRS is a sensor platform to register and manage sensor information for sensor filtering. We also propose a method for learning and predicting user paths based on the Collective Behavior Pattern. To improve prediction accuracy, we consider a time feature to measure weights and predict a path. We implement the method and the implementation and its evaluation confirm the improvement of time and accuracy for processing sensor information. |
| format | Article |
| id | doaj-art-eb7538c5faab4a36be846f9d40debb2c |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-eb7538c5faab4a36be846f9d40debb2c2025-08-20T03:21:18ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-07-011110.1155/2015/613473613473Path Prediction Method for Effective Sensor Filtering in Sensor Registry SystemSukhoon Lee0Dongwon Jeong1Doo-Kwon Baik2Dae-Kyoo Kim3 Department of Computer and Radio Communications Engineering, Korea University, 1, Anam-dong 5-ga, Seongbuk-gu, Seoul 136-701, Republic of Korea Department of Statistics and Computer Science, Kunsan National University, 558 Daehangro, Gunsan, Jeollabuk-do 573-701, Republic of Korea Department of Computer and Radio Communications Engineering, Korea University, 1, Anam-dong 5-ga, Seongbuk-gu, Seoul 136-701, Republic of Korea Department of Computer Science and Engineering, Oakland University, 2200 N. Squirrel Road, Rochester, MI 48309-4401, USAThe Internet of Things (IoT) has emerged and several issues have arisen in the area such as sensor registration and management, semantic interpretation and processing, and sensor searching and filtering in Wireless Sensor Networks (WSNs). Also, as the number of sensors in an IoT environment increases significantly, sensor filtering becomes more important. Many sensor filtering techniques have been researched. However most of them do not consider real-time searching and efficiency of mobile networks. In this paper, we suggest a path prediction approach for effective sensor filtering in Sensor Registry System (SRS). SRS is a sensor platform to register and manage sensor information for sensor filtering. We also propose a method for learning and predicting user paths based on the Collective Behavior Pattern. To improve prediction accuracy, we consider a time feature to measure weights and predict a path. We implement the method and the implementation and its evaluation confirm the improvement of time and accuracy for processing sensor information.https://doi.org/10.1155/2015/613473 |
| spellingShingle | Sukhoon Lee Dongwon Jeong Doo-Kwon Baik Dae-Kyoo Kim Path Prediction Method for Effective Sensor Filtering in Sensor Registry System International Journal of Distributed Sensor Networks |
| title | Path Prediction Method for Effective Sensor Filtering in Sensor Registry System |
| title_full | Path Prediction Method for Effective Sensor Filtering in Sensor Registry System |
| title_fullStr | Path Prediction Method for Effective Sensor Filtering in Sensor Registry System |
| title_full_unstemmed | Path Prediction Method for Effective Sensor Filtering in Sensor Registry System |
| title_short | Path Prediction Method for Effective Sensor Filtering in Sensor Registry System |
| title_sort | path prediction method for effective sensor filtering in sensor registry system |
| url | https://doi.org/10.1155/2015/613473 |
| work_keys_str_mv | AT sukhoonlee pathpredictionmethodforeffectivesensorfilteringinsensorregistrysystem AT dongwonjeong pathpredictionmethodforeffectivesensorfilteringinsensorregistrysystem AT dookwonbaik pathpredictionmethodforeffectivesensorfilteringinsensorregistrysystem AT daekyookim pathpredictionmethodforeffectivesensorfilteringinsensorregistrysystem |