This repository features a project blending Quantum Computing and Machine Learning to enhance sensor calibration for air quality monitoring. It contrasts classical models like FFNN and LSTM with quantum versions VQR and QLSTM, focusing on improving measurement precision. The repo includes all relevant code, datasets, and findings.

C# Client for Sensirion SPS30 particulate matter sensor

C driver to work with Sensirion's SEN66 environmental sensor modules via I2C

An Analysis of Delhi NCR Air Pollution Data Using Remote Sensing

ThunderFly TF-ATMON Particulate Matter Sensor Payload

ELV-LW-SPM

Tool to Create PM2.5 Dataset with Climate Vars

Particulate Matter Sensor for ThunderFly TF-ATMON system

System for logging, storing and visualisating values from various sensors