AbstractThe convergence of the Internet of Things (IoT), Artificial Intelligence (AI), Next-Generation Networks (5G),and distributed ledger technologies is fundamentally restructuring the foundational architecture of global supplychain management (SCM) and logistics. This comprehensive research report investigates the multidimensionalimpacts of IoT-enabled smart logistics, transitioning traditional, fragmented supply chains into autonomous,predictive, and resilient ecosystems. By integrating sensor-driven data collection with advanced machine learningalgorithms, modern logistics frameworks achieve unprecedented visibility, operational efficiency, andsustainability. This paper synthesizes current architectural paradigms—ranging from perception and networklayers to cloud and edge computing middlewares—and rigorously evaluates the performance of core IoTcommunication protocols, specifically MQTT and CoAP, in constrained environments. Quantitative analysesdemonstrate substantial operational improvements, including a 69% reduction in production line stoppages, animpressive 186% return on investment (ROI) over three years, and measurable reductions in carbon emissionsand material waste across major global freight forwarders. Furthermore, the report examines the integration ofblockchain technology and hardware-level security to mitigate the critical cybersecurity vulnerabilities inherentin massive IoT deployments. Finally, the analysis contextualizes these technological advancements within therapidly evolving logistics landscape of India, with a specific focus on systemic infrastructure developments, skillgap mitigation, and smart city initiatives in the state of Jharkhand. The findings indicate that the holistic integrationof these cyber-physical systems is essential for building responsive, future-ready logistics ecosystems. KeywordsInternet of Things (IoT), Smart Logistics, Supply Chain Management, Artificial Intelligence (AI), EdgeComputing, Blockchain Traceability