Assessfy Pvt. Ltd Advanced 5 milestones 100 marks

Smart City Stormwater Management using ML-Based Flood Prediction

Target year: BE Sem 7-8 (Major Project Phase-I/II) AICTE: 6 credits · ~150 hrs Bloom: Create / Evaluate MU CBCS: CIV801 / CIDLO8021 BE Project

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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Milestones

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Core skills

About this project

Build a real-time flood-prediction + drainage-management system for a Mumbai ward. Combine BMC rainfall sensor data + IoT water-level sensors + ML model that predicts waterlogging hotspots 30 minutes in advance, integrated with a dashboard for BMC ops + a citizen-facing alert app.

Course Learning Outcomes (CLOs):
CLO1: Apply hydrologic + hydraulic principles to urban drainage.
CLO2: Design an IoT sensor network with cloud backbone.
CLO3: Train + evaluate ML model on time-series flood data.
CLO4: Build a cross-platform alerting system bridging ops + citizens.
CLO5: Engage with municipal stakeholders on disaster-management policy.

Industry/societal relevance: Mumbai floods 4-8 days/year, costing crores. BMC + Smart Cities Mission actively procures such systems; portfolio gold for civil-tech roles at L&T Smart World, Tata Consultancy, Hexaware.

Milestones

1. Catchment Survey + GIS

15 marks 21d

Pick a Mumbai ward, get BMC drainage map, build GIS layer in QGIS with elevation + drains. Identify 5 historic flood points.

2. IoT Sensor Deployment (simulated)

20 marks 21d

Spec ESP32 + ultrasonic sensors for 5 manholes. Simulate live data feed (since physical deployment may not be feasible). MQTT → cloud.

3. ML Model: Flood Prediction

25 marks 21d

Train on historical rainfall + waterlogging records. LSTM or gradient-boosted trees. Target: 30-min lead time, precision > 75%.

4. Dashboard + Citizen App

20 marks 21d

BMC ops dashboard (ThingsBoard) + simple citizen app (React Native) for ward-level alerts. Live demo.

5. Stakeholder Demo + Final Report

20 marks 21d

Present to a BMC official / faculty panel. 14-page report + recommendation memo to BMC. Oral defense.

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Skills you'll learn

Hydrology + HydraulicsGIS (QGIS / ArcGIS)IoT sensor networksMachine Learning (Pythonscikit-learn / TensorFlow)Cloud architecturePublic health + disaster mgmt

Tools used

QGIS 3.34Python 3.11 (pandas + scikit-learn + TensorFlow)ESP32 + ultrasonic water sensorsMQTT brokerThingsBoardAWS Lambda (free tier)React Native (mobile alert app)

Prerequisites

Hydraulics-II; Environmental Engineering; Python intermediate; basic ML

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