Technical Approach

• Modular architecture for flexibility and scalability
• Edge computing for IoT integration & offline support
• Local caching + delayed sync without internet
• Continuous AI/CV model training for accuracy
• Strong encryption + secure data handling
• Microservices for scalability

Feasibility & Viability

Challenges: Complexity of integrating blockchain, AI, IoT; delayed real-time updates in disasters; limited internet access; accuracy issues (CV, anomaly detection, NLP); privacy & regulatory concerns.

Solutions: Modular + edge computing; caching & delayed sync; continuous model validation; encryption & secure practices; scalable microservices.

Verdict: Technically feasible & highly viable with existing tech.