What it is good at
Video AI is strongest when the event can be described as a rule in a defined area: a person in an exclusion zone, a vehicle and a pedestrian too close together, a missing item of PPE, someone entering a restricted area, or a vehicle moving too fast. Each detection can be kept as a timestamped clip, which gives safety teams evidence instead of recollection.
Where conditions set the limits
Accuracy depends on the scene. Camera angle, distance, lighting, weather, glare and obstructions all affect what can be detected reliably, and some events are simply not visible from the cameras you have. Existing cameras are often a workable starting point, but they should be assessed view by view rather than assumed to be suitable.
False alarms and the human in the loop
No system gets every event right. Too many false alerts and people stop paying attention, so the rules need tuning to each area and alerts need to reach the right person, with escalation if nobody acknowledges them. The aim is to put the relevant events in front of a person, not to remove the person.
Privacy and workplace obligations
Surveillance and privacy rules differ between states and depend on how footage is used and who is identifiable. Consult your own legal advice, tell workers what is monitored and why, and decide how long clips are kept and who can view them before you switch anything on.
Pilot before you scale
Choose one site or a few camera views, define the events that matter, and measure detections against your own footage and rules. A short pilot shows whether the approach fits your environment and what it would take to extend it, before you commit to a wider rollout.
Solutions: Validate
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