DIGITAL TWIN AND CYBER-PHYSICAL SYSTEM FOR SMART WAREHOUSE
Author
Varun Kumar B,Madhumitha S, Praveena P, Parthini B , Parmila Sri P
Abstract
This paper presents a Digital Twin and Cyber-Physical System (CPS) framework for smart warehouse optimization using real-time operational monitoring, IoT sensor simulation, intelligent decision support, and interactive analytics. Conventional warehouse management systems often provide isolated inventory, order, and equipment monitoring, resulting in limited operational visibility and delayed decision-making. The proposed system addresses these limitations by developing a virtual representation of warehouse operations that continuously reflects simulated physical warehouse conditions. The framework integrates a React-based frontend, Node.js and Express.js backend, and MySQL database to manage inventory, orders, sensor readings, AGV tracking, equipment health, alerts, and warehouse analytics. The Digital Twin represents storage racks, conveyor belts, Automated Guided Vehicles (AGVs), forklifts, loading areas, and sensor checkpoints. Simulated IoT data are used to monitor temperature, humidity, vibration, energy consumption, occupancy, and equipment status. A route optimization mechanism is incorporated to reduce AGV travel distance and congestion, while rule-based predictive maintenance identifies potential equipment risks based on temperature, vibration, and runtime conditions. The system also provides automated safety alerts for events such as restricted-area entry, high temperature, fire, and gas leakage. An interactive dashboard presents warehouse Key Performance Indicators (KPIs), inventory trends, AGV movements, equipment health, energy consumption, and recent alerts. The proposed framework demonstrates how Digital Twin and CPS concepts can be integrated into a web-based smart warehouse environment to improve operational visibility, resource utilization, safety monitoring, and managerial decision support.
Keywords
Digital Twin, Cyber-Physical System, Smart Warehouse, Internet of Things, AGV, Inventory Optimization, Route Optimization, Predictive Maintenance, Real-Time Analytics, Decision Support.
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References
[1] M. Grieves and J. Vickers, “Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems,” in Transdisciplinary Perspectives on Complex Systems, Springer, 2017.
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[3] M. Qi and X. Tao, “Digital Twin and Cyber-Physical Systems for Smart Manufacturing and Logistics,” relevant peer-reviewed literature should be verified before submission.
[4] F. Tao, H. Zhang, A. Liu, and A. Y. C. Nee, “Digital Twin in Industry: State-of-the-Art,” IEEE Transactions on Industrial Informatics, relevant bibliographic details should be verified before submission.
[5] Additional verified papers on smart warehouses, IoT, AGV routing, predictive maintenance, CPS, and warehouse Digital Twins should be added from IEEE Xplore, ScienceDirect, Springer, ACM Digital Library, or other scholarly databases.