Crane Safety AI
Event Gates Crane Safety AI
Event Gates Crane Safety AI is the popular overhead crane safety solution built with . It works with cameras installed under the trolley of the over head crane. VIS processes the camera feed, runs Event Gates proprietary AI models to detect violations and interact with the crane to slow it down, stop or prevent from starting.
Features
Crane Safety AI is a VIS solution therefore it has all VIS features and functions where applicable:
- Disconnected solution, deployed to the edge devices on the crane trolley or bridge, does not need internet or corporate network access.
- Proprietary high performance person detection model Event Gates PF, specially trained for top down view in industrial environments.
- Built-in trustworthiness features: Heartbeat, Short Term Memory, Emergency Preset of IPIO.
- Logging features including system logs, event logs and optional emailing features.
- All flexibility of regions(ROI), including polygons and multiple regions.
Risks Assessment
Lift-off Hazards
Lifting operations involving heavy loads, such as body dies, carry significant risks from the moment the load is lifted off the ground. During lift-off, dynamic forces and changes in sling tension can cause the load to sway or move unpredictably. If personnel are present within the immediate vicinity of the load, this unexpected movement creates a high risk of crushing injuries, as workers may be caught between the moving load and fixed structures or the ground.
In busy industrial environments, where multiple operations occur simultaneously and visibility or communication may be limited, the likelihood of personnel inadvertently entering these hazardous zones increases. The combination of the load’s substantial mass, momentum, and unpredictable motion during lift-off demands strict spatial controls and operational discipline to prevent severe injury or fatality.
Object drops
In many industrial lifting scenarios, the transported load may consist of multiple components or unsecured parts that are not rigidly fixed to the main body. During transit, especially when the crane accelerates, decelerates, or changes direction, these parts can shift, slide, or fall if not properly secured. Such partial load drops pose significant hazards to personnel working nearby and may result in damage to equipment, tooling, or infrastructure. These incidents are particularly difficult to anticipate, as the main load may appear stable while internal or secondary elements are at risk of displacement.
This risk is especially pronounced in operations involving tools, dies, stacked materials, or custom fixtures where secondary elements are present. The appearance of a stable load can be misleading, as internal movement or external impact during transit may lead to partial drops. Such events are difficult to predict through visual inspection alone and are often exacerbated by limited visibility, time constraints, or assumptions about load integrity.
Sling placement
Slings are widely used in industrial lifting operations to secure and transport loads with overhead cranes. However, improper sling configurations present significant operational and safety risks. Incorrect placement—such as asymmetrical alignment, twisting, or slings positioned at non-optimal angles—can result in unstable lifting conditions, unintended load movement, or contact with fixed structures. These issues are often introduced during manual rigging and may not be visually detected during standard pre-lift checks.
A second critical risk arises during the unloading phase, where slings may become unintentionally entangled or remain attached to the load. If the crane continues operation while the sling is still engaged, it can lead to sudden shifts in load position or uncontrolled release, both of which pose a danger to nearby personnel and equipment. These failure modes are difficult to prevent through procedural controls alone and often require automated systems capable of detecting unsafe sling conditions in real time.
Solutions
Operator Safety
In this patented solution, two or four cameras are mounted beneath the trolley to monitor the area around the load, depending on the geometry and required coverage. VIS processes the video feeds and alerts the crane PLC when individuals are detected in hazardous proximity. While the use of a PLC is not mandatory, it is recommended for handling load cell data and crane movement. A load cell is also advised to distinguish between loaded and unloaded states and to enable proper logging in case of safety violations during lifting operations.
Sling Safety
Two additional cameras, positioned to view the slings from above at an appropriate angle, allow VIS to detect the angle and condition of the slings. The Safety AI Sling Safety add-on prevents the crane from lifting if the slings are not properly positioned—whether during heavy lifting or empty lifting. When used in conjunction with a load cell and PLC, the system can also detect sling entrapment, identified by the crane registering a load while performing what should be an empty lift.
The Sling Safety add-on is compatible with both chain and fiber slings. When used with wire rope slings, additional buoys are required to ensure proper detection.