Smart City Gnosys

Smart city article details

Title 3D Localization Of Wireless Sensor Iot Nodes Based On Weighted Dv-Hop Algorithm
ID_Doc 136
Authors Zhang K.; Cui H.; Yan X.
Year 2024
Published Advanced Control for Applications: Engineering and Industrial Systems, 6, 4
DOI http://dx.doi.org/10.1002/adc2.212
Abstract With the widespread popularity of smart wearable devices and the rise of emerging Internet of Things applications, such as smart cities, smart homes, and smart cars, the demand for Internet of Things devices is growing. The technology for positioning Internet of Things nodes using traditional wireless sensors only provides approximate location information, which is insufficient for high-precision applications. To achieve accurate sensor node location in a specific area, this study proposes an advanced weighted distance vector jump location algorithm. This paper proposes using optical wireless networks, a new wireless communication technology, to enhance the distance vector jump algorithm. It is considered the core technology in researching the three-dimensional positioning of wireless sensor IoT nodes. The experimental data validated that by comparing with existing positioning algorithms, the improved algorithm significantly improved the location accuracy, and its average orientation error was significantly lower than other algorithms. In three cases where the wireless sensor communication radius was between 10 and 30 m, the average positioning errors of the improved algorithm were 0.363, 0.264, and 0.258, respectively. Compared with the pre improved Distance Vector Hop algorithm, its accuracy has increased by 41.1%, indicating the better positioning performance. Overall, the improved weighted algorithm significantly improves the positioning effect, providing strong technical support for the three-dimensional positioning of wireless sensor Internet of Things nodes. © 2024 John Wiley & Sons Ltd.
Author Keywords improved DV-hop; internet of things; node positioning technology; optimal anchor node; wireless sensor network


Similar Articles


Id Similarity Authors Title Published
53758 View0.873Ghorpade S.; Zennaro M.; Chaudhari B.Survey Of Localization For Internet Of Things Nodes: Approaches, Challenges And Open IssuesFuture Internet, 13, 8 (2021)
4261 View0.87Basri C.; Elkhadimi A.A Review On Indoor Localization With Internet Of ThingsInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 44, 4/W3 (2020)
7341 View0.858Arroub O.; Darif A.; Saadane R.; Rahmani M.D.; Aarab Z.An Accurate Hop-Based Localization Algorithm Under Random Deployment Of Nodes For Wsn6th International Conference on Intelligent Computing in Data Sciences, ICDS 2024 (2024)
23498 View0.858Zhang B.; Shen L.; Yao J.; Luo W.; Tang S.-K.Energy-Efficient Mobile Node Localization Using Cva Technology And Sai AlgorithmFrontiers in Energy Research, 12 (2024)
6603 View0.857Xie W.; Zhao Z.; Jiang M.; Yuan T.; Wang J.; Li X.Advances And Future Directions In Range-Free Localization Techniques For Self-Organizing NetworksIEEE Communications Standards Magazine (2025)
2828 View0.857Wang P.; Du L.; Cui Z.; Cai X.; Xie L.A Multi-Objective Localization Algorithm With Real Average Distance In WsnProceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019 (2019)
35695 View0.853Lee W.; Jeong C.-S.Low Power Sensor Location Prediction Using Spatial Dimension Transformation And Pattern RecognitionEnergies, 15, 12 (2022)