
Visual detection for safety and efficiency

Vision
In logistics and manufacturing, there are many situations that traditional sensors cannot capture in context.
Vision uses camera systems, neural networks, and smart analytics to replace multiple hardware sensors with a single flexible solution.
The result is higher detection accuracy, lower costs, and an overview of what is actually happening in the operation—in real time.
Why it makes sense to address Vision right now
Contact us if:
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you do not have an accurate overview of the movement of people, goods, or equipment,
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you only address security risks retrospectively, after an incident,
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visual inspection of the quality or condition of machines is manual,
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OEE is based on incomplete or delayed data,
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you use multiple sensors that do not communicate with each other,
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you are planning AMR, M2L, or automation, but you lack the "eyes of the system."
Object detection, inventory, monitoring, and real-time visual inspection of machine condition (OEE).
AUTOMATION AND OPTIMIZATION
01.
Prevention of collisions between people and machinery using cameras, light and sound signals.
EMPLOYEE SAFETY
02.
Safe movement within the premises, minimization of unauthorized access, and integration with the attendance and visitor management system (Veasy).
FACE RECOGNITION AND ACCESS CONTROL
03.
Plug & Play solution, quick deployment, and easy integration with M2L, AMR, and other systems.
EASY INSTALLATION AND SCALABILITY
04.
Monitoring performance, space occupancy, goods movement, and route optimization without delay.
Real-time monitoring and analysis

Who is Vision suitable for?
Vision is suitable for companies that:
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deal with logistics, manufacturing, or a combination of both,
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have movement of people, equipment, and materials in one space,
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want to increase safety without physical barriers,
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need accurate data for OEE and process optimization,
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integrate AMR, M2L, or other smart systems.
Vision is not worthwhile if:
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the operation is simple and stable,
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visual risks and changes do not arise.













































