An Inventory Management using BIG DATA and IOT

Food Industry

Abstract

This review paper examines the application of big data analytics and the Internet of Things (IoT) to enhance inventory management practices in the food industry. The food sector faces unique challenges, such as short shelf-life, perishability, and the need for strict temperature and quality control, which necessitate a more sophisticated approach to inventory management. The paper explores how the integration of real-time data from IoT-enabled sensors, coupled with the power of big data processing and predictive analytics, can lead to improved demand forecasting, inventory optimization, and waste reduction. It delves into case studies and empirical evidence showcasing the benefits of this approach, including increased product availability, reduced spoilage, and enhanced supply chain visibility. The review also discusses the technological enablers, data management strategies, and decision-making frameworks that can drive the adoption of these innovative inventory management practices in the food industry. The aim is to provide a comprehensive understanding of the current state of research and practical applications in this domain, highlighting the potential for food businesses to gain a competitive edge through the strategic use of big data and IoT.