# Safety Hotspot Mapping

> Identification and visualisation of areas with high incident frequency or hazard concentration

- Skill: `construct-ai-primary/safety-hotspot-mapping` (Agent Skill)
- Install (CLI): `npx skillmds@latest add construct-ai-primary/safety-hotspot-mapping`
- Raw SKILL.md: https://api.skillmd.com/api/skills/construct-ai-primary/safety-hotspot-mapping/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: Construct-AI-primary (https://skillmd.com/u/construct-ai-primary)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/construct-ai-primary/safety-hotspot-mapping

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# Safety Hotspot Mapping

## Overview
Identification and visualisation of geographic areas on site where incidents and hazard concentration are above average. Primary agent: Predictive Analytics Specialist.

## Steps
1. **Data Collection** → Gather incident locations with coordinates, inspection findings by zone
2. **Geospatial Analysis** → Map incidents onto site layout and overlay zones with higher frequency
3. **Density Analysis** → Calculate incident density and identify areas exceeding the average threshold
4. **Hotspot Classification** → Classify areas as low, medium, high, or critical risk
5. **Recommendations** → Generate targeted interventions for hotspot areas
6. **Reporting** → Create visual hotspot maps for management review

## Success Criteria
- Hotspots accurately reflect incident patterns
- Maps clear and actionable for site teams
- Targeted interventions reduce hotspot risk

## Common Pitfalls
1. Small area of data → Insufficient incidents for reliable hotspot identification
2. Changing site layout → Hotspots become invalid when work moves
3. Ignoring context → Not considering work activity density in hotspot analysis

## Cross-References
- `safety-incident-tracking/SKILL.md` — Incident location data
- `safety-predictive-risk/SKILL.md` — Predictive analytics input