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StreetPulse, transforms urban blocks into AI-powered health corridors by leveraging DT technology and real-time biometric monitoring. Designed to address inequities in urban resilience, the system integrates edge AI cameras, wearable sensors, and air-quality beacons to predict and mitigate public health crises before they escalate. Data streams into an open-standard digital twin, generating a Health-Stress Index for each block, while AI triage alerts first responders via ATAK-compatible dashboards. Key features include:
• Predictive analytics: Detects health risks (e.g., heatstroke clusters) 5–10 minutes faster than traditional emergency systems.
• Privacy-centric design: Federated learning ensures biometric data stays encrypted and anonymized.
• Community co-creation: Residents shape sensor placement and alerts through VR workshops and inclusive UX (e.g., haptic feedback for visually impaired users).
• Scalability: Modular, open-source architecture allows cities to deploy the system at $1 per resident.
Concept shows Faster EMS response and fewer preventable ER visits, proving that equitable, AI-driven urban resilience is achievable.
Mohamed Fendi (Architect – Urbanist – Researcher)
Nagham El Natout (Architect & Urban Designer)
Rawad Aabed (Civil Engineer – Project Design & Delivery)
Abdulatif Almukhadhab (Civil Engineer – Transportation Engineer)
Ahmed Obied (Projects, programs & operations management expert)