Logistic & Supply Chain

AI & ML solutions

Artificial Intelligence in Logistics and Supply Chain is assisting companies to solve the complexities of logistical networks. AI-enabled systems raise the quality of service, improve customer satisfaction, and increase the degree of transparency within these networks.

COMPUTER VISION - Surveillance

Automated Port Tracking

Port Authorities need to capture information on shipping containers that move into their premise, to track cargo flow. Data such as container numbers, ISO number of containers which are printed on the containers, and license plate of the vehicle carrying the container are crucial to this process. These attributes are identified manually by port inspectors and can be misread due to oversight, which can result in delivery delays and be very costly to shipment providers. CCTV cameras at port terminals, backed with An Optical Character Recognition (OCR) system, can easily capture this information, removing the dependency on error-prone manual inspection.

Automated Port Tracking

NATURAL LANGUAGE PROCESSING - Named Entity Recognition

Procurement Matching

In procurement, both the buyers and vendors have to ensure that the documentations remain consistent in the transaction. The contents of purchase orders, invoices, and order receipt notes, etc. have to match. Manually checking these documents is resource heavy and complex, due to variances in format, nomenclature differences, and unstructured language. This can lead to delivery and payment delays, over or understocking, and loss of revenue. AI streamlines this process, using NER to extract information like delivery address, vendor names, product details, quantity, and pricing from these documents. Using the extracted data, AI can be taught to seamlessly match PO’s with their Invoices and ORN’s, maintaining transaction consistency.

Procurement Matching

COMPUTER VISION - Image Detection

Freight Container Inspection

To adhere to regulatory compliance, freight containers need to be monitored while out for shipment. Port Authorities inspect the containers for heavy exterior damages, proper sealing practices, hazardous or dangerous material stickers or tags, and container leakages. Manual inspections can be error-prone due to distance, container stacking, insufficient lighting, and poor positioning between the inspector and the container. A Computer Vision model, using ‘Object Detection’, can identify these attributes of the containers much more consistently. CCTV cameras placed around yards and container zones can capture container images. AI notifies Port Authorities if it detects any non-compliance in the container's attributes.

Freight Container Inspection

More Case Studies and Blogs

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Computer Vision in Artificial Intelligence

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Computer Vision in Inventory Management- Top 5 Applications

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Check List

How to Ensure That Your Machine Learning Project Is Successful

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