A traditional warehouse typically includes several core functions such as receiving, storing, tracking and tracing, picking, and shipping. It also involves interactions with both upstream and downstream stakeholders, as well as a centralized management system. While a planning function is recommended, it is often considered optional in traditional warehousing setups. When goods arrive at a warehouse, they need to be tagged. Tagging can occur at multiple levels—truck, pallet, tray, or individual product—but pallet and tray tagging are the most commonly used due to their efficiency and ability to distinguish between different product types. Once tagged, goods are stored either manually or through automated systems like conveyor belts. If the incoming products are hazardous, compatibility checks are performed before storage to ensure safe handling.
In traditional warehouses, tracking is usually done manually using handheld scanners. The planning department plays a key role in determining the order fulfillment schedule and allocating the necessary resources. After planning, the order-picking process begins, which is also typically manual. Orders can be picked by entire trays or pallets, but often require manual assembly of different items to fulfill custom orders. Once picked, orders are packed and shipped to the customers. The warehouse supply chain involves both upstream and downstream stakeholders. Upstream stakeholders, typically suppliers, are responsible for delivering goods to the warehouse. Downstream stakeholders, usually customers, place orders that the warehouse fulfills. In some cases, the same entity may serve as both an upstream and downstream stakeholder—for example, manufacturers storing surplus products in warehouses. Clear communication with stakeholders is crucial, particularly when notifying them about order readiness, inventory levels, or any disruptions in the delivery process.
Effective warehouse operations also require a robust management system that covers finance and accounting, data processing, and sales management. Sales management focuses on handling orders and inventory, ensuring supply meets demand. Finance and accounting oversee the warehouse's financial health and ensure operational continuity. Data processing manages information from scanners and other sources, working closely with sales management to maintain accurate stock levels and support efficient supply intake.
While smart warehouses share many of the same high-level components as traditional warehouses, smart warehouses make planning a mandatory component and incorporate a warehouse communication network for enhanced coordination and efficiency. Each feature in the top layer has various optional and obligatory elements.
A smart warehouse functions through the seamless communication and integration of multiple systems. Within its business process management (BPM) structure, various technologies support the overarching warehouse management system (WMS). Advanced Planning and Scheduling (APS) software is used to oversee the planning and scheduling operations, ensuring that resources are optimally allocated. Simultaneously, an inventory management system is employed to maintain optimal stock levels and streamline inventory control. Financial and sales management modules handle all monetary interactions—ranging from processing incoming orders to managing restocking events—ensuring smooth financial operations throughout the warehouse. Order picking is directed by an Automated Storage and Retrieval System (AS/RS), which interfaces with Automated Guided Vehicles (AGVs) and other material-handling equipment to carry out tasks efficiently. Furthermore, a Transport Management System (TMS) is integrated into the process, coordinating with AGVs to prepare and load shipments onto trucks.
The figure outlines three key roles in the system—represented as swimlanes: the Supplier/Client, the Warehouse Management System (WMS), and the Warehouse. The client initiates a request, which is processed by the supplier. The WMS manages the planning and coordination of that request, while the Warehouse role executes the operational tasks. Each role consists of specific actions that may trigger related tasks across the system.
Architecture design of smart warehouses need to consider various viewpoints. In the following context diagram for a smart warehouse, the Warehouse Management System (WMS) serves as the central hub, orchestrating the core operations of receiving, storing, picking, and shipping goods. The WMS interfaces with a range of human operators, including corporate supervisors, warehouse managers, and floor-level employees. These users interact with the system to log actions, monitor activities, make operational decisions, and extract performance reports from the collected data. Depending on warehouse policy, truck drivers may also interact with the WMS as external operators.
To function effectively, the WMS depends on real-time data inputs gathered through scanners and sensors. These devices are often mounted on Automated Guided Vehicles (AGVs) or embedded within Augmented Reality (AR) systems. The Transport Management System (TMS) uses this data to guide AGVs and employees—via AR devices—to specific locations within the warehouse. This operational flow is further supported by the Advanced Planning and Scheduling (APS) system, which determines which goods should be retrieved. In some configurations, an Order Picking Operation System (OPOS) is also integrated to enhance the efficiency of picking tasks, and shelves may be outfitted with RFID tags to enable adaptive, self-adjusting storage.
To further enhance warehouse performance, Multi-Agent System (MAS) methodologies can be implemented. In such setups, robotic agents operate collaboratively within a distributed architecture. Intelligent agent-based communication allows for decentralized task allocation, optimizing efficiency through distributed algorithms. This approach helps to reduce battery usage and latency while maximizing utilization through task decomposition techniques.
The finance/accounting and sales management components manage all monetary and transactional functions within the warehouse. These include procurement, order processing, employee payroll, and broader financial oversight. In an optimized smart warehouse, seamless information sharing occurs between internal systems and external partners, enabled through automated data exchanges and system integration. This real-time visibility enhances responsiveness, reduces uncertainty, and helps maintain operational stability.
Reliable communication is critical for the success of smart warehouse operations. To ensure low-latency and high-reliability connections, the WMS communicates with other systems via robust 4G LTE and 5G networks. These technologies provide the infrastructure needed for agile, responsive operations within the Industry 4.0 framework. Additionally, cloud-based smart warehouses often leverage hardware virtualization to enable resource pooling, improving scalability and resource efficiency.
The decomposition view shown below outlines all essential modules required for smart warehousing. It includes not only the top-level functional components but also the sub-modules associated with each enabling technology. Key technologies featured in this view include barcoding, Augmented Reality (AR), Automated Guided Vehicles (AGVs), the Internet of Things (IoT), Warehouse Management Systems (WMS), scanning, RFID, and communication infrastructure.
For example, within the IoT module, several sub-components are identified: Artificial Intelligence (AI), Ambient Intelligence (AmI), a Security Module, and Real-Time Information processing. These elements highlight the critical considerations a smart warehouse designer must account for when implementing IoT-based solutions.
The AI sub-module encompasses techniques such as machine learning and deep learning algorithms, which enable predictive analytics, anomaly detection, and adaptive process control. Closely related, Ambient Intelligence (AmI) builds on AI, sensor networks, and pervasive computing to create an environment that dynamically adapts to the needs and behaviors of users and stakeholders. In this context, AmI contributes to making the warehouse responsive, intelligent, and context-aware.
Real-time information gathered from distributed sensors and devices supports the execution of both AI and AmI functions, enabling timely decision-making and responsive automation. A critical aspect of any Industrial IoT system is security—hence, the inclusion of a dedicated Security Module. This module ensures that proper security controls are in place to protect IoT devices, data transmissions, and system integrity from potential threats.
Together, these sub-packages form the technological backbone of a smart warehouse, ensuring that operations are not only efficient and intelligent but also secure and adaptable to evolving operational demands.
The uses view is presented below. The two core modules in the smart warehouse architecture are the Warehouse Management System (WMS) and the warehouse communication network. The WMS serves as the central control unit, interacting with various back-end systems and external modules to coordinate operations. The communication network functions as a critical link between the WMS and front-end technologies such as Augmented Reality (AR) hardware and Automated Guided Vehicles (AGVs). Additionally, other systems—including the Transport Management System (TMS), Internet of Things (IoT) devices, RFID infrastructure, and various external platforms—connect directly to the communication network to enable seamless data exchange and real-time coordination across the warehouse ecosystem.
Finally, in the deployment view, the mapping of software modules to their corresponding hardware components is illustrated. The data processing module is deployed on both the Warehouse Management Server and Warehouse Manager nodes, which serve as the central hubs for managing operations and analytics. Additional nodes are dedicated to cameras, sensors, scanners, and augmented reality (AR) hardware.
Automated Guided Vehicles (AGVs) are equipped with their own onboard cameras, sensors, and scanners, enabling autonomous navigation and interaction with the warehouse environment. Similarly, smart shelves are outfitted with embedded sensors to monitor inventory and environmental conditions. Each of these hardware components is represented as a separate node within the deployment architecture, emphasizing the distributed and interconnected nature of the smart warehouse system.
Source: https://doi.org/10.1016/j.compind.2020.103343