Smart Inventory System using IoT and Cloud Technology


  • Vijaya N. Aher Vishwakarma Institute of Information Technology, Pune, India
  • Rahul S. Pol Vishwakarma Institute of Information Technology, Pune, India
  • Sandeep V. Gaikwad SCTR’s Pune Institute of Computer Technology, Pune, India
  • Daulappa G. Bhalke Dr. D. Y. Patil Institute of Technology Pimpri, Pune
  • Ajay Yadaorao Borkar Cusrow Wadia Institute of Technology, Pune
  • Mahesh T. Kolte Pimpri Chinchwad College of Engineering Pune


IoT, Cloud Server, Android application, ESP 32, Smart Inventory, Industrial Automation


A smart inventory system is a computational time efficient system that helps businesses to manage and track their inventory levels, orders, and deliveries. It facilitate companies to have real-time visibility into their inventory and helps them make more informed and quick decisions about restock and how much to order. One key feature of a smart inventory system is its ability to automatically reorder items when they reach a certain threshold, eliminating the need for manual intervention. This helps to ensure that businesses always have the right amount of inventory on hand, reducing the risk of running out of stock or having excess inventory that takes up valuable storage space. This paper include deployment of this system in real world which benefits to handle smart inventory system with  improved accuracy 30% and efficiency in inventory tracking around 10%, reduced lead times for ordering and restocking, and the ability to track inventory across multiple locations. This paper briefly elaborates the implementation of smart inventory system that greatly improves a business's inventory management process, leading to increased profitability by more than 50%, average foot fall increased to 25% and reducing the waiting time of customer by nearly 75% making customer more satisfied.


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Kunal Singh,” Smart Warehouse Management Using Electronic Sensor-Based Computational Intelligence, SCI, Volume 823,March (2019).

A. Madhu Vamsi,” IOT Based Autonomous Warehouse Management for Warehouses”, EAISICC October(2019), pp 371-376.

B. Sai SubrahmanyaTejesh,(2018) “ Warehouse management system using IoT and open source framework” Alexandria Engineering Journal, Volume 57, Issue4, December (2018),Pages 3817-3823

Ming-Chih Chen, Yin-Ting Cheng,* and Chung-Yu Siang, “ Development of Inventory Management System Based on Radio Frequency Identification Technology”, Sensors and Materials, Vol. 34, No. 3 (2022) 1163–1177

Rashidah Funke Olanrewaju,” Cloud-Based Warehouse System for Effective Management of Under and Over-stock Hazards”,ICCCE,(2021), pp 274-278

lkerKorkmaz,” A cloud-based and Android-supported scalable home automation system”, compeleceng, Volume 43, April 2015, pp. 112-128.

Chih-Chin Liang, “Smart Inventory Management System of Food-Processing-andDistribution Industry”, International Conference on Information Technology and Quantitative Management, Procedia Computer Science, Sciverse Science Direct, Eleevier,17 ( 2013 ) 373 – 378

Souvik Paul, “Study of Smart Inventory Management System ased on The Internet of Things”, International Journal on Recent Trends in business and Tourism. Vol 3 No. 3 (2019):

Rajesh Bose, Haraprasad Mondal, Indranil Sarkar, Sandip Roy, “Design of smart inventory management system for construction sector based on IoT and cloud computing”, e-Prime - Advances in Electrical Engineering, Electronics and Energy, Volume 2, 2022.

Miss. Supriya P. Gawande1, Prof. Dr. Sagar B. Tambe2, “Inventory Management System for Warehous”, International Research Journal of Engineering and Technology (IRJET), June 2019, Volume: 06 Issue: 06, pp. 3454-3458

Weng Chun Tan, Manjit Singh Sidhu,” Review of RFID and IoT integration in supply chain management”, Operations Research Perspectives, Volume 9, 2022, pp. 1342-1348.

Apurva S Zope, Mayuri S Jambhale, Nimisha M Korde, Hajra A Khan, Prof.Akansha Bhargav, 2017, Iot Based Industrial Automation, International Journal of Engineering Reseach and Technology, 2017 Volume 5 – Issue 01, pp. 821-827

Mane, P. B. et al. (2017). Watermarking and cryptography based image authentication on reconfigurable platform. Bulletin of Electrical Engineering and Informatics, 6(2), 181-187.

Mandwale, A. J. et al. (2015, January). Different Approaches For Implementation of Viterbi decoder on reconfigurable platform. In 2015 International Conference on Pervasive Computing (ICPC) (pp. 1-4). IEEE.

Mane, P. B., & Mulani, A. O. (2018). High speed area efficient FPGA implementation of AES algorithm. International Journal of Reconfigurable and Embedded Systems, 7(3), 157-165.

Kashid, M. M et al. (2022, November). IoT-Based Environmental Parameter Monitoring Using Machine Learning Approach. In Proceedings of the International Conference on Cognitive and Intelligent Computing: ICCIC 2021, Volume 1 (pp. 43-51). Singapore: Springer Nature Singapore.

Yadav, D. ., & Gangwar, S. . (2023). Generic Home Automation System Using IoT Gateway Based on Wi-Fi and ant+ Sensor Network . International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 153–165.

Rossi, G., Nowak, K., Nielsen, M., García, A., & Silva, J. Enhancing Collaborative Learning in Engineering Education with Machine Learning. Kuwait Journal of Machine Learning, 1(2). Retrieved from

Kumar, A., Dhabliya, D., Agarwal, P., Aneja, N., Dadheech, P., Jamal, S. S., & Antwi, O. A. (2022). Cyber-internet security framework to conquer energy-related attacks on the internet of things with machine learning techniques. Computational Intelligence and Neuroscience, 2022 doi:10.1155/2022/8803586




How to Cite

Aher , V. N. ., Pol , R. S. ., Gaikwad , S. V. ., Bhalke, D. G. . ., Borkar, A. Y. ., & Kolte, M. T. . (2023). Smart Inventory System using IoT and Cloud Technology. International Journal of Intelligent Systems and Applications in Engineering, 12(4s), 187–192. Retrieved from



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