To train and validate the proposed model, an image dataset labeled with ground-truth AQI values is collected from Delhi, India, termed 'AirSetDelhi'. It consists of 21,620 single-scene daytime and nighttime images, unevenly distributed in six AQI categories. Experimental results show that En3C-...
Experimental work has been carried out using existing machine learning techniques and proposed method on the air quality dataset of Delhi. It has been observed that the proposed method extracts wind speed, carbon monoxide and nitrogen dioxide as the key parameters and further accuracy of this method...
Thank you soo much for this post. It really gave me direction on how scaping can be done for air quality data. On following you post, I am trying to collect data only for Delhi but I am getting below error for setup_pull.py setup_pull.py”, line 60, in encoded_data = base64.b6...
Delhi’s Air Quality Index (AQI) registered at 243, falling under the ‘Poor’ category, as reported by the Central Pollution Control Board (CPCB). In response to this, the Sub-Committee under the Commission for Air Quality Management in NCR & Adjoining Areas (CAQM) convened to assess ...
Your task is to build a machine learning model that can predict air quality index in Indian cities. Dataset Description This dataset was adapted from the Air quality dataset byRohan Rao Context Air is what keeps humans alive. Monitoring it and understanding its quality is of immense importance ...
Salé city (North-Western Morocco)18. Barcelona city was assessed19for air quality using a remote sensing dataset provided by ESA's Tropospheric monitoring instrument (TROPOMI) along with local air quality monitoring data to assess differences in air quality during the lockdown and one month before...
To train the Autoencoder, a custom root mean squared error (RMSE) loss function is defined. This loss function quantifies the disparity between predicted and actual PM2.5concentrations, guiding the model toward more accurate predictions. The training process iterates through the dataset multiple time...
Classification carried out on the testing dataset based on the developed model on the training set. Finally, the air quality levels are predicted Table 3: Factors of input feature: Wind Power Wind Power Factors <3 level 3-4 level 4-5level 5-6 level 6-7 level 0 1 2 3 4 Table 4: ...
CPCB National Air Quality Index (AQI) Bulletin Central Pollution Control Board, New Delhi, India (2023) https://cpcb.nic.in/AQI_Bulletin.php, Accessed 28th Feb 2023 accessed on Google Scholar CREA, 2023 CREA Tracing the Hazy Air 2023. Progress Report on National Clean Air Programme (NCAP) ...
This dataset has high spatial (15 Km) and temporal (1 h) resolutions, and the qualities of which have been assessed by the cross-validation method and independent datasets, suggesting a high accuracy. The above air quality reanalysis data were interpolated to each subject of current study ...