SmartLab: AI-Based College Laboratory Equipment Tracking and Predictive Maintenance System

College laboratories contain equipment that must be identified, tracked, and maintained to support practical learning. Manual registers and periodic inspections can make it difficult to know the current status of each item, find maintenance history quickly, and identify equipment that may need servicing. SmartLab proposes a software-based system for registering laboratory equipment, tracking its status, maintaining service records, and using equipment usage and maintenance history to estimate maintenance needs. The application provides a staff dashboard for equipment registration, tracking, maintenance updates, and reports. Equipment can be assigned a unique ID and a status such as Available, In Use, Faulty, or Under Maintenance. A predictive-maintenance module can analyse recorded usage and service history to flag equipment for inspection. The system is intended to improve record accessibility, support timely maintenance, and reduce avoidable disruption in college laboratories. Predictions are decision-support suggestions and should be verified by laboratory staff.