Real-Time Inventory Monitoring and Smart Ordering System for Small Warehouses Using IoT

Abstract : In today’s fast-paced supply chain environment, efficient inventory management is essential for small and medium-sized warehouses striving to reduce manual errors, avoid stockouts, and improve operational productivity. This paper presents the design and implementation of a smart warehouse system that leverages Internet of Things (IoT) technologies for real-time inventory monitoring and automated order fulfilment. The proposed system integrates RFID readers, barcode scanners, and various IoT sensors—including weight, temperature, and motion detectors—with a cloud-based inventory management platform. These components work together to continuously monitor stock levels, detect item movement, and maintain environmental conditions for sensitive goods. When stock falls below a predefined threshold, the system automatically triggers restocking requests and can even notify or place orders with suppliers. A predictive analytics engine powered by machine learning analyses historical data to optimize reorder points, minimize waste, and forecast demand. The implementation demonstrates how IoT based automation can enhance transparency, reduce costs, and increase scalability for small warehouse operations. Experimental results confirm improved efficiency, higher picking accuracy, and reduced operational downtime. This research offers a cost-effective and scalable solution tailored to meet the growing demands of inventory control in the digital era.

Keyword: IoT, Smart Warehouse, Real-Time Inventory Monitoring, Automated Reordering, Predictive Analytics, Cloud Computing.