The intelligent drug cabinet integrates technologies such as the Internet of Things, big data, and artificial intelligence to build a precise traceability and efficient management system covering the entire lifecycle of chemicals. Its core implementation path is as follows:

1、 Full process digital identification, achieving precise traceability of "one item, one code"

Electronic tag binding: Each bottle of chemical is attached with an RFID tag or QR code, storing key information such as ID, name, CAS number, concentration, production date, etc. RFID tags support long-distance batch reading (recognition distance up to 3-5 meters), while QR codes serve as a low-cost supplementary solution, both of which are synchronized with the Laboratory Management System (LIMS) data.

Automatic registration of incoming and outgoing goods: The system automatically records the time, operator, and purpose of chemical collection and return through an ultra-high frequency RFID reader or barcode scanner. For example, when researchers collect concentrated sulfuric acid, the scanning code is triggered as soon as the cabinet door is opened, and the system synchronously updates the inventory and generates an electronic ledger to avoid the problem of missing or incorrect entries in manual registration.

2、 Intelligent perception and dynamic control enhance management efficiency

Environmental monitoring integration: The cabinet is equipped with temperature and humidity sensors, gas detectors, and real-time monitoring of storage conditions. If the organic solvent volatilization exceeds the standard, the system will automatically activate the exhaust device and push an alarm message to the administrator's mobile phone to prevent safety hazards.

Hierarchical management of permissions: Based on the Role Based Access Control (RBAC) model, different permission levels are set. For example, graduate students can only receive low toxicity reagents, while professors can apply for highly toxic or hazardous chemicals. The system automatically records the operation trajectory to achieve traceability of responsibilities.

Inventory warning and automatic replenishment: By analyzing historical usage data, the system predicts the trend of chemical consumption. When inventory falls below the safety threshold, it automatically generates a purchase request and pushes it to the supply chain platform, reducing experimental interruptions caused by stockouts.

3、 Data driven decision-making, optimizing resource allocation

The system aggregates data on chemical usage frequency, storage period, and waste volume to generate visual reports, helping laboratory managers identify high-frequency reagents (such as ethanol and acetone) and optimize procurement plans; Meanwhile, by analyzing idle reagents and promoting internal allocation or compliant disposal, inventory costs and safety risks can be reduced.

Application Effectiveness

After deploying intelligent drug cabinets in a chemistry laboratory of a certain university, the efficiency of chemical management has increased by 60%, the number of violations has decreased by 90%, and the inventory turnover rate has increased by 35%. This has achieved a leap from "manual control" to "intelligent autonomy", providing strong support for scientific research safety and efficient resource utilization.