In the realm of inventory management, traditional systems often necessitate extensive human involvement and consuming considerable time. Moreover, the susceptibility to human errors introduce an additional layer of complexity. To address these challenges, the proposed system advocates for the integration of Internet of Things (IoT) technology with inventory management practices, thereby streamlining operations for inventory owners. The envisioned smart inventory management system leverages Radio-Frequency Identification (RFID) tags strategically placed on products, vehicles facilitating transportation, and employees. This integration ensures precise tracking of inventory movements and elevates security measures. By harnessing machine learning algorithms, the system further augments its capabilities by offering sophisticated purchases forecasting. This data-driven approach provides strategic insights. to optimize stock management, contributing to enhanced efficiency and accuracy in the inventory industry.

In our project we aim to :

• Implementing RFID technology to enable precise tracking of inventory movements.

• Enhance access control with RFID Tags on Employees

• Automate Inventory Counts

• Utilize Odoo’s stock control techniques, such as ABC analysis, EOQ, and FIFO, to optimize inventory management.

• Utilize Machine Learning for Purchase Forecasting

• Provide a user-friendly interface for businesses to access sales forecasts, optimize inventory levels, and monitor inventory-related activities.

1. Implement RFID-based Inventory Tracking with RFID Tags on Goods.

2. Integrate RFID tags on employees to monitor personnel access and enhance security within

the inventory management system.

3. Use Odoo’s effective Stock Control Techniques.

4. Using machine learning algorithms to forecast future demand and provide strategic insights

for stock management.

5. Enable business owners to track inventory levels in real time