Computer Vision in Logistics
Due to the increasing global diversity of goods and globalization of markets, supply chains and logistics systems are becoming more complex and challenging.
This results in an increasing need for automation and digitalization of logistics processes and the related flow of information.
The implementation of smart logistics objects and smart logistic.
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Equipment Condition Monitoring
AI vision systems are widely used for conditions monitoring of logistics equipment.
Practical examples include image processing technologies used for condition monitoring and predictive maintenance of long belt conveyors, which otherwise would need to be inspected manually.
In another application, thermal cameras provide images to detect defects in.
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Inspection and Quality Control of Goods
Computer Vision in logistics has many use cases to ensure the quality of goods throughout the supply chain.
Cameras for vision inspection tasks are integrated into the manufacturing and packaging processes of goods.
An important use case is visual documentation and monitoring to prove the integrity of goods.
Optical systems are further used in the .
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Occupancy of Storage and Traffic Areas
Since the availability of logistics areas is critical for efficient storage and transportation processes, several use cases provide ways to monitor space occupancy.
Relevant objects include pallets stored in warehouses, vehicles parked in parking lots, and packages that are loaded onto delivery trucks.
Camera-based approaches have been implemented .
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Optimize Manual Picking and Packing
While there is a significant trend towards automation in logistics, the share of manual work in handling processes is still substantial.
This is because of the diversity of goods which makes automation very challenging.
Since manual work is very error-prone, vision systems help to assist in picking and packing operations to reduce the error rates a.
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Process Modeling and Simulation
For planning and predicting the performance of logistics systems, simulation methods are of great importance.
Image recognition systems are helpful in collecting process data for close-to-reality simulation.
With object detection and object tracking, material flow parameters such as number, state, flow directions, throughput, and throughput time ca.
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Security and Protection of Infrastructure
Infrastructure and logistics facilities are the basis for logistics processes.
Therefore, it is of great importance to protect them against internal or external hazards such as accidents, theft, terror attacks, and others.
AI video surveillance is a widely popular, effective solution to increase security in logistics facilities such as warehouses. .
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Traceability and Tracking of Objects
Smart tracing applications aim to identify and localize logistics objects such as goods, containers, vehicles, or persons within logistics systems.
It can be achieved by attaching optical codes to objects such s barcodes or QR-codes and using image processing algorithms to capture and read the optical codes.
Such identification systems are widely p.
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Volumetric Properties of Goods
In logistics processes, the volumetric properties of goods are critical for planning and billing quantities.
Its automation enables significant time savings and optimization of operational efficiency.
Hence, vision-based systems to detect dimensions of goods are widely popular to detect parcel dimensions on conveyor systems.
The degree of automatio.
