KEYWORD |
Particulate Matter monitoring station with Raspberry Pi Pico
Reference persons FILIPPO GANDINO
External reference persons Pietro Chiavassa
Edoardo Giusto
Gustavo Adolfo Ramirez Espinosa
Research Groups DAUIN - GR-05 - ELECTRONIC CAD & RELIABILITY GROUP - CAD
Description A high concentration of particulate matter (PM) in the air we breathe can cause a series of health problems such as strokes, heart diseases, and lung cancer.
The monitoring of PM concentration levels is often performed by environmental agencies using a network of fixed stations that are spread over the territory. However, due to the high cost of the instrumentation, it is not possible to achieve high spatial granularity, especially in urban environments.
In the past few years, low-cost light-scattering sensors have been introduced in the market and can provide more insights on PM levels at a finer temporal and spatial granularity.
The thesis work involves the development and improvement of a monitoring station for particulate matter, in more detail:
- porting of the existing MicroPython code to the Raspberry Pi Pico microcontroller
- code optimization for memory constraints (if necessary using low-level languages such as C, C++, or Rust)
- implementation of LORA and Bluetooth connectivity using extension modules
- driver implementation/adaptation to multiple PM sensors models (only one model is currently supported)
Required skills Good programming skills
Knowledge of C, C++, or Rust
Python (preferred)
Some experience with embedded systems (preferred)
Deadline 17/01/2024
PROPONI LA TUA CANDIDATURA