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Building HydroPulse AI: Solving Urban Waterlogging with AWS Strands Agents SDK

An early-warning urban flood intelligence SaaS built for the WeMakeDevs Environmental Hacks hackathon, leveraging local agentic inference via AWS Strands Agents SDK to predict street-level risk.

# Building HydroPulse AI: Solving Urban Waterlogging with AWS Strands Agents SDK
Every monsoon across major Indian metros, urban underpasses and critical roadways face severe waterlogging. Standard weather apps provide macro-level rainfall alerts, but fail to provide street-level telemetry on which underpass is actively flooded.
To address this hyperlocal challenge, we built **HydroPulse AI** during the WeMakeDevs Environmental Hacks Hackathon (Track 02: Heat & Water).
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## 1. System Architecture & AWS Tech Stack Instead of relying on heavy cloud APIs that introduce network latency, we integrated an edge-telemetry pipeline utilizing the **AWS Strands Agents SDK**:
- **Telemetry Ingestion:** Real-time ultrasonic drainage depth and rainfall intensity streams. - **Agentic Engine (AWS Strands Agents SDK):** Processes high-frequency telemetry vectors locally to compute risk probability scores without incurring cloud API latency or billing overhead. - **Actuator Dispatcher:** Automatically flags critical thresholds (Risk Score > 75) to trigger municipal drainage pumps proactively.
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## 2. Engineering Challenges & Solutions Building an early warning system came with real-world hurdles: - **Telemetry Spikes:** Rainfall intensity varies rapidly during downpours. We configured the AWS Strands Agent logic to run moving-average evaluation matrices, filtering false positive spikes. - **State Synchronization:** Syncing real-time streaming state across multi-tab UI components without layout shifts.
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## 3. Impact & Next Steps By providing a 30-minute advance alert before severe flooding occurs, HydroPulse AI allows municipal authorities to deploy high-capacity pumps and reroute traffic proactively.
*Built for WeMakeDevs Bharat Builds Tour - Environmental Hacks.*
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