Inspiration# Inspiration
Women in India face persistent safety risks—especially in public spaces, transit, and isolated environments. Existing safety apps often rely on manual triggers and lack intelligent automation, contextual awareness, and real-time coordination. We wanted to build a proactive, AI-powered system that could detect distress, activate emergency protocols, and connect users to verified support networks—even in low-connectivity or high-risk scenarios.
What it does
Women’s Safety Guard is a multi-agent AI platform that delivers real-time emergency response, safety guidance, and community support. It uses IBM’s Granite NLP models and Agent Development Kit (ADK) to automate detection, alerting, routing, and reporting. The system is multilingual, scalable, and designed for both urban and rural contexts.
How we built it
Frontend: HTML5, CSS3, JavaScript, Bootstrap
Backend: IBM ADK, Node.js, Express.js, Google Sheets
Security: Firebase Auth / OAuth, encrypted data, role-based access
External APIs: Twilio (alerts), Google Maps (routing), NGO databases
Dev Tools: IBM Granite NLP, IBM Data Preprocessing Toolkit, Canva, GitHub, VS Code
Challenges we ran into
- Integrating multi-agent workflows with real-time triggers
- Handling multilingual NLP inputs for regional dialects
- Ensuring secure, consent-based data sharing
- Designing a UI that’s intuitive under stress and accessible across devices
What we learned
We deepened our understanding of agentic AI design, NLP model tuning, and emergency response workflows. We also learned how to balance technical complexity with user-centric design—especially for vulnerable populations.
What's next
We plan to integrate voice-based triggers, expand regional language support, and partner with NGOs for verified support networks. We’re also exploring offline SMS fallback and community-driven safety mapping.
$$ \text{Emergency Trigger} \rightarrow \text{Context Detection} \rightarrow \text{Alert Dispatch} \rightarrow \text{Safe Routing} \rightarrow \text{Support Connection} \rightarrow \text{Incident Logging} $$
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