Internet of Things (IoT) Impact on Inventory Management: A Review

Introduction

Inventory management is critical in supply chain management because it addresses both production and price problems. Its primary purpose is to lower inventory costs while improving customer service levels through the use of efficient restocking methods. Because it comprises raw materials, work-in-process components, and finished commodities, inventory is a vital component of the supply chain. Figure 1.0 demonstrates the recent rapid development in the deployment and use of IoT devices across a variety of industries, including logistics, healthcare, retail, and manufacturing, to name a few. The Internet of Things (IoT) is a network of interconnected devices that comprise sensors, software, and communication capabilities for data collection and sharing. This technology has revolutionized inventory management by allowing for real-time visibility, automation, and better decision-making. This book chapter examines the impact of IoT on inventory management. This chapter is divided into eight sections. The first section provides background information on IoT in inventory management, as well as the objectives, scope, methodology, and review structure of the study. The second section introduces inventory management, including its definition, purpose, typical inventory management techniques, and related difficulties. Section 3 discusses the notion of IoT in inventory management, covering IoT understanding, definition, core principles, major components of IoT systems, communication protocols, standards, and architectures. Section 4 investigates several Internet of Things inventory management solutions such as real-time tracking, automated inventory replenishment, procurement, predictive maintenance, quality control, supply chain visibility, optimization, demand forecasting, and customer analytics. Section 5 investigates IoT-enabled Inventory Management Systems, covering RFID, sensor networks, data collection, cloud computing, big data analytics, and the integration of IoT with existing inventory management systems. Section 6 investigates the benefits and challenges of IoT in inventory management, such as improved inventory tracking accuracy and efficiency, reduced stockouts and overstocks, improved supply chain visibility and collaboration, cost savings, operational optimization, and security and privacy concerns. Section 7 contains case studies and examples of real-world uses of IoT in inventory management across various sectors, as well as success stories and lessons gained from using IoT in inventory management. Finally, Section 8 examines the future trends and implications of IoT in inventory management with an emphasis on emerging technologies, advancements, potential impacts on inventory management practices, industry trends, policy, and regulatory concerns for IoT-enabled inventory systems.

Figure 1.

Emerging trend: Widespread IoT Device installations(statista)

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  Background and significance of IoT in inventory management

IoT stands for Internet of Things, and it refers to the process of connecting any device having an on/off switch to the Internet. Sensors in IoT devices monitor and report on environmental variables such as location, temperature, light, humidity, movement, and handling speed. The IoT has a substantial influence on inventory management, which is the monitoring of multiple procedures starting form ordering, storing, utilizing, transferring, and selling the firm's goods. IoT devices provide assistance with inventory management by providing real-time data insights, reducing human labor, increasing precision and efficacy, ensuring quality management, and meeting consumer demand and expectations. IoT devices, on the other hand, provide several challenges, including high prices, security and privacy risks, integration and compatibility concerns, and scalability and reliability issues. These challenges may be overcome by using best practices such as selecting the appropriate IoT devices and platforms, implementing strong security measures, utilizing cloud-based services and edge computing, and applying data analytics and artificial intelligence.