Fire and Smoke Detection

Problem Addressed

In industrial parks, warehouses, forests, and similar high-risk sites, early fires may first appear as localized smoke, color shifts, or texture changes. Manual monitoring can miss subtle signals or be misled by lighting changes, night vision, and steam. This skill focuses on a practical alerting workflow: detecting fire and smoke in images or video streams, locating suspected sources, and producing structured warnings rather than only labeling a single frame.

How It Works and Where It Fits

It uses color features, dynamic texture analysis, and smoke diffusion models to identify flames and smoke, then provides location marking, confidence assessment, and fire severity grading. Inputs can be local files or network URLs, and outputs include structured reports, risk notes, and report links. Historical report queries are expected to come from the cloud API instead of local memory or manual aggregation. It is useful for security monitoring triage and alert coordination, and can feed into alarm workflows, but it does not replace on-site professional response. Use clear monitoring footage with minimal occlusion; common supported formats include jpg, png, mp4, avi, and mov, up to 10MB. Treat results as safety alerts only, and notify qualified personnel immediately for on-site verification.