A spatiotemporal causal convolutional network for predicting air pollution.
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Updated
Jul 25, 2022 - Python
A spatiotemporal causal convolutional network for predicting air pollution.
Python scripts to download and preprocess air pollution concentration level data aquired from the Sentinel-5P mission
Python package to get and transform PurpleAir data
A spatiotemporal causal convolutional network for predicting PM2.5 concentrations.
A minimal python interface for PMS7003 PM sensor
Emissions Spatial and Temporal Allocator model
Exploring the effect of COVID-19 in air pollution by using satellite data, with the sentinelsat and cartopy libraries.
☁Air pollution visualization and forecasting platform based on Flask and TensorFlow
Detects PM2.5 levels based on daily atmospheric conditions
A Python module to import data from the UK Automatic Urban Rural Network (air pollution monitoring network)
Low cost air quality monitoring
Home Assistant integration for air quality measurements in Austria (data source: Umweltbundesamt / Federal Environment Agency Austria).
Using NYC Taxi Data as a Predictor of Urban Air Quality
Historical data of the Air Pollution Index in Malaysia from 2005. (With script)
Python wrapper for the honeywell-hpma115s0 particulate matter sensor
Gridded Aircraft Trajectory Emissions model
Crowdsourced real-time air quality monitoring platform with hyper-local sensor networks
Framework to collect, aggregate and process air pollution data from different sources (Italy regions)
Python Wrapper for the sensirion SPS030 Particulate Matter (PM) sensor
Air Pollution Detection model using Raspberry pi 3 Model B.
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