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Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 10 No 5 (2026): Volume 10, Issue 5, May 2026 | Pages: 241-253
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 13-05-2026
Traditional on-premise inventory management systems have long struggled with scalability bottlenecks, high infrastructure maintenance costs, siloed data repositories, and the inability to support distributed, multi-warehouse operations in real time. The digital transformation wave driven by cloud computing, Internet of Things (IoT), and Artificial Intelligence (AI) presents a compelling opportunity to re-architect inventory management from the ground up. This paper presents the design, implementation, and evaluation of a comprehensive Cloud-Based Inventory Management System (CBIMS) built on a microservices architecture deployed across a multi-region cloud infrastructure (Amazon Web Services). CBIMS integrates seven core functional modules: real-time stock tracking via IoT RFID and barcode sensors, demand forecasting using LSTM-based time-series models, automated procurement workflows with vendor portal integration, multi-warehouse location management, role-based access control with full audit trails, a RESTful API gateway for ERP integration, and an interactive analytics dashboard with drill-down reporting. The system is implemented using a React.js frontend, Node.js/Express.js microservices backend, PostgreSQL and Redis for persistent and cache storage respectively, Apache Kafka for event streaming, and deployed on AWS using ECS Fargate with auto-scaling policies. Security is enforced through OAuth 2.0 / JWT authentication, AES-256 data encryption at rest, and TLS 1.3 in transit. Evaluation results demonstrate 99.97% system availability across a six-month pilot, sub-200 ms API response at 1,000 concurrent users, a 34.7% reduction in stockout incidents, a 28.3% reduction in excess inventory carrying costs, and a System Usability Scale (SUS) score of 86.4, classifying CBIMS as an Excellent system. The proposed architecture provides a replicable blueprint for cloud-native inventory transformation in small-to-medium enterprises (SMEs) and educational institutions.
Cloud Computing, Inventory Management System, Microservices Architecture, AWS, IoT Integration, RFID Tracking, LSTM Demand Forecasting, Apache Kafka, Role-Based Access Control, RESTful API, Real-Time Analytics, ERP Integration, Digital Supply Chain, Auto-Scaling.
Mohan Bodne, Vicky Patar, Shantanu Sontakke, Vanshraj Turankar, & Bhagyashree V. Kale. (2026). Cloud-Based Inventory Management System: Architecture, Real-Time Analytics, Automation, and Security for Modern Enterprise Supply Chains. International Research Journal of Innovations in Engineering and Technology - IRJIET, 10(5), 241-253. Article DOI https://doi.org/10.47001/IRJIET/2026.105034
This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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