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Air pollution in cities remains a major challenge due to vehicle emissions, construction dust, and industrial activity. Current solutions—like masks or indoor purifiers—protect individuals but fail to address pollution at a community scale. My proposal is to design IoT & AI-integrated Smart Air-Purification Poles that combine air filtration, data analytics, and smart-city integration.
Each pole would run on solar panels with Li-ion battery storage for 24/7 uptime. The purification unit would include:
Cyclone separator + pre-filter for coarse dust,
HEPA H14 filter for PM2.5/PM10,
Activated carbon layer for SO₂, NOx, and VOCs,
Electrostatic precipitator for fine aerosols.
Pollution data is captured using sensors like SDS011 (PM2.5/PM10), MQ-135 (gases), CCS811 (VOC/CO₂), and DHT22 (temperature/humidity for calibration). These feed into a Raspberry Pi / ESP32-based microcontroller that preprocesses data before pushing it via LoRaWAN or 5G to a central cloud server (AWS IoT Core / Azure IoT Hub).
A real-time dashboard displays pollution heatmaps, while an AI model (LSTM or Prophet) predicts pollution spikes based on historical data + weather APIs. Citizens access this through a mobile/web app, which can issue alerts (e.g., “High PM2.5 tomorrow morning”).
Additional modules can be added: edge computing for local decision-making, public Wi-Fi hotspot, or CCTV integration.
Beneficiaries include residents (especially vulnerable groups), local authorities (better planning), and health agencies (data-driven policies). Unlike existing fragmented solutions, this system offers scalable, self-sustaining, and data-driven pollution control at the community level.
This matters to me because I’ve seen how poor air quality disrupts lives. By fusing IoT hardware, AI forecasting, and clean-tech engineering, we can build cities where clean air isn’t a luxury, but a standard.
Comments
I like how you combined IoT, AI forecasting, and renewable energy into a scalable solution.
The idea feels both practical and futuristic, something cities could genuinely adopt
The fundamental challenge, however, is the physics of scale. The impact of even hundreds of poles on a city's vast atmosphere would be negligible, making the purification itself highly inefficient. The prohibitive cost of manufacturing and maintaining these complex units, especially the frequent filter replacements, also makes city-wide deployment economically unfeasible. The system's true value lies in its hyper-local data collection, not the air purification.
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