Inspiration
AquaSense AI was inspired by the environmental risks caused by poorly monitored industrial wastewater discharge and the lack of realtime compliance systems.
What it does
AquaSense AI monitors realtime wastewater metrics such as pH, COD, BOD, TSS, and temperature while using AI to detect compliance risks and predict environmental breaches.
How we built it
We built AquaSense AI using Flask, SQLAlchemy, MQTT, Socket.IO, Chart.js, and Python AI logic. We simulated IoT wastewater sensors and created a realtime environmental monitoring dashboard with automated PDF reporting.
Challenges we ran into
We faced challenges integrating MQTT with Flask, managing realtime database updates, synchronising live graphs, and designing a professional dashboard UI without making it visually overwhelming.
Accomplishments that we're proud of
We successfully built a fully functional realtime wastewater intelligence platform with AI-powered compliance analysis, live telemetry visualisation, and professional environmental reporting.
What we learned
We learned how to build realtime IoT architectures, manage websocket communication, create scalable dashboards, and apply AI concepts to environmental monitoring systems.
What's next for AquaSense AI
We plan to integrate real IoT hardware, machine learning anomaly detection, cloud deployment, SMS/email alerts, GIS environmental mapping, and advanced predictive analytics.
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