Autonomous Inventory and Logistics Using AIoT Swarm Intelligence: A Framework for Next-Generation Industrial Optimization
Description
Swarm Intelligence, coupled with Artificial Intelligence of Things (AIoT), offers a transformative approach to managing dynamic industrial logistics. This paper presents an AIoT-enabled framework for autonomous warehouse operations using distributed robotic swarms. Simulating 1000 rows of operational data across five smart hubs, the study reveals swarm intelligence's potential in enhancing order picking, delivery coordination, and inventory tracking. The model leverages edge AI, cooperative sensing, and decentralized routing to adapt in real time. Results suggest marked improvements in operational efficiency, sustainability, and scalability, positioning swarm-driven logistics as foundational to future autonomous supply chains.
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The modern supply chain is under pressure to deliver faster, cheaper, and more sustainably. Traditional warehouse systems struggle with inflexible routing, inventory mismatches, and centralized bottlenecks. Swarm Intelligence, modeled on the collective behavior of ants and bees, offers a decentralized, adaptive mechanism for autonomous coordination. When fused with AIoT infrastructure—edge-based processing, real-time sensing, and intelligent analytics—these systems become self-managing and resilient.
Institutions
- Independent University
- North South University