Computer Vision + AI for Warehouse Efficiency
Automated barrel detection using computer vision and AI improved warehouse accuracy, minimized manual labor, and optimized decanting operations efficiently.
The Challenge
Manual barrel counting during the decanting process was time-consuming, error-prone, and dependent on human supervision. The absence of a reliable system caused dispatch delays, audit mismatches, and labor inefficiencies.
The Solution
iCubes implemented a Computer Vision–based automation system using real-time video feeds to count barrels during the decanting process with minimal human intervention.
By deploying YOLO & Faster R-CNN models trained on barrel imagery and integrating them with CCTV infrastructure, the system provides highly accurate and real-time barrel counts along with day/month-wise reporting.
- AI/ML ModelsYOLO, Faster R-CNN
- LibrariesTensorFlow, OpenCV
- HardwareCCTV Camera (existing infrastructure)
- IntegrationReal-time feed processing and reporting
100% Automation
of barrel counting
98% Accuracy
in count reports
70% Time Reduction
in end-to-end decanting process
Daily + Monthly Reports
auto-generated for compliance
Have a project in mind or questions about our services? We’re here to help you turn ideas into impactful digital solutions tailored to your business needs.
Call Us
+44 (0)7586697547
Email Id
sales@i-cubes.net