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International Journal of Frontiers in Engineering Technology, 2021, 3(10); doi: 10.25236/IJFET.2021.031006.

Intelligent Logistics Tracking System Based on Wireless Sensor Network

Author(s)

Xiaoxia Han

Corresponding Author:
Xiaoxia Han
Affiliation(s)

Department of Management and Information, Shandong Transport Vacational College, Weifang, 261206, Shandong, China

Abstract

Wireless sensor networks are widely used to collect and monitor data in the physical world and play a vital role. This article mainly studies the intelligent logistics tracking system based on wireless sensor network. In this paper, the compressed sensing theory is used to reconstruct the environment monitoring data in the cabin to verify the validity of the theory. The five types of sensors are placed in the specified position in the carriage for multi-point sampling, and each node performs data collection every 45 seconds. This paper uses the entropy weight fuzzy comprehensive evaluation method to evaluate the platform planning scheme. The wireless network adopts a multi-zone network networking method, which divides the entire coverage area into multiple sub-areas. Each wireless access point is responsible for controlling a sub-area. At the same time, each wireless access point will also become a mobile terminal and the backbone network. In the actual image transmission, there are two data transmission modes of Zigbee module involved, transparent transmission and point-to-point mode. In the transparent transmission mode, only the communication between the gateway device and the edge device can be carried out, and the communication between the edge devices cannot be carried out. In order to test that the wireless sensor node can actively track the logistics status of the logistics object, this paper uses a temperature sensor to test to test whether the wireless sensor node can actively track the logistics object at different temperatures. In order to achieve the goal of performance testing, a test program was written to simulate a large number of users logging into the system at the same time to perform operations to test the performance of the system. Starting from 15m, the communication radius increases by 5m each time to 50m, and the average positioning error is gradually decreasing. The results show that the introduction of Internet technology and mobile communication network positioning technology into the logistics tracking system can greatly improve the utilization of existing resources.

Keywords

Wireless Sensor Network, Intelligent Logistics Tracking System, Positioning Algorithm, Vehicle Routing Problem, System Evaluation

Cite This Paper

Xiaoxia Han. Intelligent Logistics Tracking System Based on Wireless Sensor Network. International Journal of Frontiers in Engineering Technology (2021), Vol. 3, Issue 10: 45-58. https://doi.org/10.25236/IJFET.2021.031006.

References

[1] Chen, Wang, Hongzhi, et al. CANS: Towards Congestion-Adaptive and Small Stretch Emergency Navigation with Wireless Sensor Networks[J]. IEEE Transactions on Mobile Computing, 2016, 15(5):1077-1089.

[2] Hassani []A, Plata-Chaves J , Bahari M H , et al. Multi-Task Wireless Sensor Network for Joint Distributed Node-Specific Signal Enhancement, LCMV Beamforming and DOA Estimation[J]. IEEE Journal of Selected Topics in Signal Processing, 2017, 11(3):518-533.

[3] Naranjo P G V, Shojafar M, Mostafaei H, et al. P-SEP: A prolong stable election routing algorithm for energy-limited heterogeneous fog-supported wireless sensor networks [J]. Journal of Supercomputing, 2017, 73(2):1-23.

[4] Han G , Liu L , Jiang J , et al. Analysis of Energy-Efficient Connected Target Coverage Algorithms for Industrial Wireless Sensor Networks[J]. IEEE Transactions on Industrial Informatics, 2017, 13(1):135-143.

[5] Van Hoesel L , Nieberg T , Wu J , et al. Prolonging the lifetime of wireless sensor networks by cross-layer interaction[J]. IEEE Wireless Communications, 2017, 11(6):78-86.

[6] Hong Y W , Scaglione A . Energy-efficient broadcasting with cooperative transmissions in wireless sensor networks[J]. IEEE Transactions on Wireless Communications, 2016, 5(10):2844-2855.

[7] Lee S S , Park C , Sohn I . A Distributed Multi-Channel Scheduling Algorithm for Low Latency Wireless Sensor Network[J]. The Journal of Korean Institute of Communications and Information Sciences, 2020, 45(9):1566-1569.

[8] Ren J , Zhang Y , Zhang K , et al. Lifetime and Energy Hole Evolution Analysis in Data-Gathering Wireless Sensor Networks[J]. IEEE Transactions on Industrial Informatics, 2016, 12(2):788-800.

[9] Latif K , Javaid N , Saqib M N , et al. Energy consumption model for density controlled divide-and-rule scheme for energy efficient routing in wireless sensor networks.[J]. International Journal of Ad Hoc & Ubiquitous Computing, 2016, 21(2):130-139.

[10] Zhang H , Xing H , Cheng J , et al. Secure Resource Allocation for OFDMA Two-Way Relay Wireless Sensor Networks Without and With Cooperative Jamming[J]. IEEE Transactions on Industrial Informatics, 2017, 12(5):1714-1725.

[11] Deng Y , Wang L , Elkashlan M , et al. Physical Layer Security in Three-Tier Wireless Sensor Networks: A Stochastic Geometry Approach[J]. IEEE Transactions on Information Forensics and Security, 2017, 11(6):1128-1138.

[12] Oller J , Demirkol I , Casademont J , et al. Has Time Come to Switch From Duty-Cycled MAC Protocols to Wake-Up Radio for Wireless Sensor Networks?[J]. IEEE/ACM Transactions on Networking, 2016, 24(2):674-687.

[13] Fei Z , Li B , Yang S , et al. A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems[J]. IEEE Communications Surveys & Tutorials, 2017, 19(1):550-586.

[14] Luo X , Zhang D , Yang L T , et al. A kernel machine-based secure data sensing and fusion scheme in wireless sensor networks for the cyber-physical systems[J]. Future Generation Computer Systems, 2016, 61(8):85-96.

[15] Wang Q , Jiang J . Comparative Examination on Architecture and Protocol of Industrial Wireless Sensor Network Standards[J]. IEEE Communications Surveys & Tutorials, 2016, 18(3):2197-2219.

[16] Amin R , Islam S K H , Biswas G P , et al. Design of an anonymity-preserving three-factor authenticated key exchange protocol for wireless sensor networks[J]. Computer Networks, 2016, 101(6):42-62.

[17] Ding X , Tian Y , Yu Y . A Real-Time Big Data Gathering Algorithm Based on Indoor Wireless Sensor Networks for Risk Analysis of Industrial Operations[J]. IEEE Transactions on Industrial Informatics, 2016, 12(3):1232-1242.

[18] Jiang J , Han G , Guo H , et al. Geographic multipath routing based on geospatial division in duty-cycled underwater wireless sensor networks[J]. Journal of Network & Computer Applications, 2016, 59(1):4-13.

[19] Xu Z , Chen L , Chen C , et al. Joint Clustering and Routing Design for Reliable and Efficient Data Collection in Large-scale Wireless Sensor Networks[J]. IEEE Internet of Things Journal, 2016, 3(4):520-532.

[20] Kumari S , Li X , Wu F , et al. A user friendly mutual authentication and key agreement scheme for wireless sensor networks using chaotic maps[J]. Future Generation Computer Systems, 2016, 63(10):56-75.

[21] Zou Y , Wang G . Intercept Behavior Analysis of Industrial Wireless Sensor Networks in the Presence of Eavesdropping Attack[J]. IEEE Transactions on Industrial Informatics, 2016, 12(2):780-787.

[22] Ebrahimi D, Assi C. On the Interaction between Scheduling and Compressive Data Gathering in Wireless Sensor Networks [J]. IEEE Transactions on Wireless Communications, 2016, 15(4):2845-2858.

[23] Hong Z, Wang R , Li X . A Clustering-tree Topology Control Based on the Energy Forecast for Heterogeneous Wireless Sensor Networks[J]. IEEE/CAA Journal of Automatica Sinica, 2016, 3(01):70-79.

[24] Pak J M , Ahn C K , Shi P , et al. Distributed hybrid particle/FIR filtering for mitigating NLOS effects in TOA-based localization using wireless sensor networks[J]. IEEE Transactions on Industrial Electronics, 2017, 64(6):5182-5191.

[25] Deniz F , Bagci H , Korpeoglu I , et al. An adaptive, energy-aware and distributed fault-tolerant topology-control algorithm for heterogeneous wireless sensor networks[J]. Ad Hoc Networks, 2016, 44(7):104-117.

[26] Liu W , Zhou X , Durrani S , et al. Energy Harvesting Wireless Sensor Networks: Delay Analysis Considering Energy Costs of Sensing and Transmission[J]. IEEE Transactions on Wireless Communications, 2016, 15(7):4635-4650.