The mAP50 That Lied to Me: A Debugging Story About On-Device Safety AI
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I'm building GroundCheck , an offline-first field inspection app for construction safety managers. One of the things we bet on early was on-device hazard detection — a YOLO model that runs entirely on the phone, no internet required, spotting missing hardhats and safety vests in a photo the moment you take it. No competitor in this space does that; everyone else ships cloud-only detection that falls over the second you lose signal, which on a job site is often. This is the story of a metric…
1Key Takeaways
- I'm building GroundCheck , an offline-first field inspection app for construction safety managers.
- One of the things we bet on early was on-device hazard detection — a YOLO model that runs entirely on the phone, no internet required, spotting missing hardhats and safety vests in a photo the moment you take it.
- No competitor in this space does that; everyone else ships cloud-only detection that falls over the second you lose signal, which on a job site is often.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that i'm building GroundCheck , an offline-first field inspection app for construction safety managers.
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