Optimising Cold Chain Warehousing Through Autonomous Robotics, IoT Monitoring and Intelligent Inventory Management in Saudi Arabia's Food Distribution Sector

Cold-chain warehouses are expected to preserve food safety while meeting increasingly variable distribution demand. Yet robotics, environmental monitoring and inventory software are often assessed independently, leaving the mechanisms through which their integration affects product quality insufficiently explained. This critical integrative review synthesises 30 DOI-identifiable publications from 2020–2025 and interprets their relevance to Saudi Arabian food distribution. Its aim is to develop a safety-led operating model linking autonomous material handling, connected temperature evidence, remaining shelf-life estimation and stock allocation. The review distinguishes demonstrated findings from proposed applications, compares technical and organisational constraints, and identifies measurable implementation requirements. The synthesis indicates that robotic throughput is valuable only when product release decisions remain governed by validated temperature histories, traceability and quality rules. A proposed layered architecture connects sensors, warehouse systems, predictive models and supervised robotic execution. An associated performance framework balances temperature excursions, expiry losses, service reliability, worker safety and refrigeration energy. Saudi deployment priorities include heat-resilient infrastructure, segregated food categories, reliable connectivity, verifiable data governance and staged piloting. Evidence for integrated implementations in Saudi facilities remains limited; consequently, claims of productivity or waste reduction require local field validation rather than extrapolation from unrelated warehouses.