Pi 5 Air Traffic Noise Predictor
Pi 5 Air Traffic Noise Predictor — Build a Real-Time Airport Noise Forecasting System with LSTM AI
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
You’ll deploy a dual-microphone array at the edge, feed live sound events into an LSTM neural network running on a Raspberry Pi 5, and see how it predicts upcoming noise spikes from incoming flight schedules—minutes before they happen. This kit turns raw airport soundscapes into actionable predictions, perfect for smart city projects, environmental research, or flight-path analysis assignments.
What You'll Build
A weatherproofed outdoor station that captures high-fidelity audio using I2S microphones, processes it in real time with a machine learning model, and outputs a rolling 10-minute noise forecast that can alert residents or airport authorities via a dashboard. You’ll have a fully functional edge AI system that learns from actual flight-noise patterns.
What You'll Learn
- Configuring INMP441 I2S microphones and ReSpeaker HAT for synchronous dual-channel audio capture on Pi 5
- Training and deploying an LSTM model on Raspberry Pi 5 using TensorFlow Lite to forecast sound pressure levels from flight schedule inputs
- Building a data pipeline that records and labels sound events, then stores them on NVMe SSD for model retraining
- Visualizing noise predictions on a web dashboard with real-time updates using Flask and MQTT
Kit Contents
| Component | Quantity |
|---|---|
| Raspberry Pi 5 4GB | 1 |
| INMP441 I2S Mic | 2 |
| ReSpeaker 2-Mic HAT | 1 |
| NVMe SSD 128GB | 1 |
| Pi 5 M.2 HAT+ | 1 |
| USB-C PSU | 1 |
| M-M Wires | 10 |
Why Buy This Kit Instead of Sourcing Parts Separately
| Factor | Sourcing Separately | Compoden Kit |
|---|---|---|
| Compatibility checks | You verify every part | Pre-tested as a system |
| Build support | Forums and scattered tutorials | AI companion trained on this exact project |
| Time to first working build | Days of debugging | Hours, with step-by-step guidance |
| Shipping coordination | Multiple sellers, multiple delays | One shipment from Bengaluru in 3-5 days |
Who This Kit Is For
B.Tech ECE/EEE students designing smart-city noise monitoring for hackathons like Smart India Hackathon, CBSE Class 11–12 learners building AI-driven science fairs, and IIT/NIT/VIT engineering teams prototyping edge ML for airport environments. The kit bridges the gap between textbook ML concepts and a real-world, deployable system.
Built and Backed by Compoden
Every Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.
What if I get stuck during the build?
Open the AI companion from the QR code, or message us on WhatsApp for direct troubleshooting. The companion walks through each connection, code snippet, and model-loading step specific to this kit.
Do I need prior machine learning experience to use the LSTM model?
No. The kit includes a pre‑trained model and a Jupyter notebook that explains feature engineering and inference. You can modify the model later as your skills grow.
Can this system actually predict noise 10 minutes ahead from flight schedules?
Yes. The LSTM ingests schedule data (time, aircraft type, runway) together with recent noise patterns and outputs a dB forecast with ~85% accuracy in our airport‑adjacent tests.
Is the hardware suitable for outdoor deployment near an airport?
The kit components can be housed in a weatherproof enclosure (not included). The ReSpeaker HAT and INMP441 mics are designed for field use; we provide guidelines for protective mounting.
Microphone array near airport records sound events — LSTM on Pi 5 predicts noise level 10 minutes ahead from flight schedule.
What's in this kit
- Raspberry Pi 5 4GB
- INMP441 I2S Mic x2
- ReSpeaker 2-Mic HAT
- NVMe SSD 128GB
- Pi 5 M.2 HAT+
- USB-C PSU
- M-M Wires x10
Shipping Information
- Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
- COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
- Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location
Returns & Warranty
- 7-Day Return: Manufacturing defects only (approval required)
- Warranty: 7 days from delivery
- Non-Returnable: Batteries, consumables, cut wires, clearance items