Critical sectors like healthcare, hospitality, smart cities, office infrastructure, and emergency systems still rely on slow, manual, and fragmented crisis response workflows. These delays increase loss, risk, and recovery time.
This project generates a structured, hackathon-ready intelligence report:
- 50 real-world crisis problems
- Evenly distributed across 5 sectors (10 each)
- Root-cause analysis for every problem
- AI solution blueprint with architecture and deployment path
- India-focused implementation constraints and ethics coverage
The output can be used directly for:
- Hackathon submissions
- Problem-solution storytelling in pitch decks
- Technical discussion with mentors and judges
- Early product discovery for an AI resilience platform
- Hospitality (Hotels and Resorts)
- Healthcare (Hospitals and Clinics)
- Smart Cities
- Office Buildings and Corporate Spaces
- Public Safety and Emergency Systems
- generate-report.js: Report generation logic
- AI_Based_Crisis_Response_Report.md: Generated markdown report
- package.json: Node.js dependencies and scripts
- Node.js 18+
- npm
npm installnpm run buildAfter build, the project generates:
- AI_Based_Crisis_Response_Report.md
Depending on your local script version, a DOCX file may also be generated by the same run.
- Open the generated report.
- Showcase one problem from each sector.
- Explain AI architecture and deployment steps.
- Highlight feasibility, impact, and scalability.
- Close with ethics, governance, and rollout plan.
- Strong problem depth across multiple industries
- Clear AI implementation path instead of generic ideas
- Real deployment context for India
- Structured content that maps well to judging rubrics: innovation, technical depth, impact, and scalability
- Add a web dashboard to filter problems by sector and risk level
- Export one-click pitch summary (2-minute and 5-minute versions)
- Add cost-benefit scoring and implementation timeline per use case
- Integrate citations and benchmark references automatically
- Keep the generated report as the source of truth for submission content.
- If you customize problem statements, regenerate and review consistency before final submission.
- Track any judge feedback and map it to specific sections for iterative improvements.