IoT-Based Real-Time Tracking Systems: Enhancing Efficiency in Dynamic Supply Chains
Keywords:
Cloud computing, Digital transformation, IoT, Logistics optimization, Predictive analytics, Real-Time monitoring, Smart supply chainsAbstract
The integration of IoT in supply chain management enhances transparency, efficiency, and adaptability. This research presents a real-time IoT-enabled tracking system addressing inefficiencies, delays, and visibility gaps. Utilizing IoT sensors, cloud architecture, and predictive analytics, the system ensures asset monitoring, proactive disruption management, and workflow optimization. Key innovations include sensor-integrated tracking, continuous data transmission, and AI-driven insights, improving inventory control, asset tracking, and cold storage logistics. A simulated implementation achieved 98.5% tracking accuracy and a 70% reduction in manual interventions. The study also examines IoT adoption challenges, offering a strategic framework for scalable, secure, and efficient supply chain transformation.
Beyond its technical advancements, this study also examines the challenges associated with IoT adoption, including security risks, high implementation costs, and network reliability issues. To address these concerns, a strategic framework is proposed for ensuring a scalable, secure, and efficient IoT-based supply chain transformation. The findings highlight IoT’s transformative potential in modern logistics, paving the way for more resilient, data-driven, and automated supply chain ecosystems. This research contributes valuable insights into the role of IoT in supply chain optimization, providing a foundation for future advancements and large-scale industry adoption.
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