𝗦𝗼𝗺𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝘀𝗮𝗳𝗲𝘁𝘆 𝘀𝗶𝗴𝗻𝗮𝗹𝘀 𝗺𝗮𝘆 𝗻𝗲𝘃𝗲𝗿 𝗺𝗮𝗸𝗲 𝗶𝘁 𝗶𝗻𝘁𝗼 𝗮𝗻 𝗘𝗛𝗦 𝘀𝘆𝘀𝘁𝗲𝗺. 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 𝗔𝗜 𝗰𝗮𝗻 𝗵𝗲𝗹𝗽 𝘁𝗲𝗮𝗺𝘀 𝘀𝗲𝗲 𝗺𝗼𝗿𝗲 𝗼𝗳 𝘄𝗵𝗮𝘁 𝗶𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴 𝗯𝗲𝗳𝗼𝗿𝗲 𝗮 𝗿𝗶𝘀𝗸 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝗮𝗻 𝗶𝗻𝗰𝗶𝗱𝗲𝗻𝘁.
At the 2026 Europe IMPACT Conference, the Automated Near Miss Reporting with Computer Vision AI session explored how existing CCTV infrastructure can support more proactive safety visibility.
Subhash Sharma, Founder & CEO of Hawkvision AI, shared how Computer Vision AI can help identify defined safety events such as PPE non-compliance, unsafe pedestrian and vehicle interactions, walkway issues, spills, and potential near misses that may otherwise go unreported.
When those signals are connected with Benchmark Gensuite Concern Reporting, they can move directly into established EHS workflows for review, investigation, action, and follow-up.
The discussion highlighted several practical considerations:
• Use existing camera infrastructure to identify previously unseen safety signals
• Focus Computer Vision AI on defined, site-specific risks and use cases
• Connect AI-detected events directly into structured EHS workflows
• Prioritise the signals that require action rather than creating more alerts
• Build privacy, transparency, and clear safety purpose into deployment from the start
The opportunity is not simply to detect more events. It is to turn relevant safety signals into information EHS teams can assess, prioritise, and act on.
Read the full blog to explore how Computer Vision AI can strengthen near miss reporting and proactive risk visibility:
https://hubs.la/Q04tG5jJ0
EHSManagement WorkplaceSafety ArtificialIntelligence ComputerVision
