Journal
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 58, Issue 24, Pages 7490-7506Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2020.1720928
Keywords
logistics sustainability; Internet of Things; industrial hazardous chemical vehicles; indoor parking; self-learning
Categories
Funding
- Natural Science Foundation of Jiangsu Province [BK20180749]
- Natural Science Research of Jiangsu Higher Education Institutions of China [19KJB580016]
- Hong Kong ITF Innovation and Technology Support Program [ITP/079/16LP]
- National Natural Science Foundation of China [61571241, 61872423]
- Nanjing University of Post and Telecommunications research start-up fund [NY218125, NY218126, NY219112]
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Logistics sustainability practices in industrial cases gain more attention recently especially when transportation efficiency becomes a bottleneck. The research of smart parking develops rapidly especially the thriving of Internet of Things (IoT). In this research, the industrial hazardous chemical vehicle (IHCV) consists of tractor and trailer. The vehicle coupling and decoupling occur frequently in order to fulfil logistics missions. The real-time dynamic indoor location information of both tractors and trailers are of great significance among users. Excessive time and human effort consumed in locating the vehicles lead to the transportation delay and disorderly parking exacerbate congestion inside the indoor parking garage. In this paper, we propose an IoT-enabled smart indoor parking system for logistics vehicles. A self-learning genetic tracking algorithm is developed to ensure the tracking performance. The feasibility and effectiveness of this solution architecture and algorithm are verified in a real-life chemical logistics company. The results show that the proposed algorithm not only performs constant improving location accuracy up to 96.7% after learning but also ensure the long-term use compared to the triangulation method. Moreover, disorderly parking can be identified by location cell partition as to eliminate potential risks. Improved logistics efficiency and lowered congestion situation contribute to the sustainable logistics.
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