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Research on Logistic Warehouse Scheduling Management With IoT and Human-Machine Interface

Research on Logistic Warehouse Scheduling Management With IoT and Human-Machine Interface

Lanjing Wang, Alfred Daniel J., Thanjai Vadivel
Copyright: © 2022 |Volume: 15 |Issue: 4 |Pages: 15
ISSN: 1935-5726|EISSN: 1935-5734|EISBN13: 9781683180272|DOI: 10.4018/IJISSCM.305846
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MLA

Wang, Lanjing, et al. "Research on Logistic Warehouse Scheduling Management With IoT and Human-Machine Interface." IJISSCM vol.15, no.4 2022: pp.1-15. http://doi.org/10.4018/IJISSCM.305846

APA

Wang, L., J., A. D., & Vadivel, T. (2022). Research on Logistic Warehouse Scheduling Management With IoT and Human-Machine Interface. International Journal of Information Systems and Supply Chain Management (IJISSCM), 15(4), 1-15. http://doi.org/10.4018/IJISSCM.305846

Chicago

Wang, Lanjing, Alfred Daniel J., and Thanjai Vadivel. "Research on Logistic Warehouse Scheduling Management With IoT and Human-Machine Interface," International Journal of Information Systems and Supply Chain Management (IJISSCM) 15, no.4: 1-15. http://doi.org/10.4018/IJISSCM.305846

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Abstract

The automated deployment of the internet of things (IoT) and the human-machine interface provides the best advancement for dispersed warehouse scheduling management (WSM). In this paper, superior data systematic move toward warehouse scheduling management (WSM) has been suggested using the computational method to allow smart logistics. Furthermore, this paper introduces the human-machine interface framework (HMI) using IoT for collaborative warehouse order fulfillment. It consists of a layer of physical equipment, an ambient middleware network, a framework of multi-agents, and source planning. This approach is chosen to enhance the reaction capabilities of decentralized warehouse scheduling management in a dynamic environment. The simulation outcome has been performed, and the suggested method realizes a high product delivery ratio (96.5%), operational cost (94.9%), demand prediction ratio (96.5%), accuracy ratio (98.4%), and performance ratio (97.2%).