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-...
16,17. Considering that air quality data is a typical time series, auto regressive moving average model (ARMA) is widely used. Kumar et al.18used ARMA to predict\(\text {O}_{3}\), CO, NO and\(\text {NO}_{2}\)concentrations...
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 ...
Extensive experiments on a real-world dataset demonstrate that our model achieves the highest performance compared with state-of-the-art and baseline models for air quality prediction. This is a preview of subscription content, log in via an institution to check access. Similar content being ...
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
Exploiting the variability in the indicators retrieved in our dataset, we perform a cluster analysis (Everitt et al., 2011) that allows us to partition the countries under study into a limited number of internally homogeneous groups. The cluster analysis results are robust to different clustering ...
The aim of the study, was to utilize the CNN model on the air quality dataset to detect patterns for future prediction modelling. The proposed study, is implemented on two phases where the first phase focuses on preprocessing and data analysis, whereas the Second phase is used for the ...
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...
(PLI) values below 1, signifying low to negligible pollution and acceptable classroom environmental quality. A strong significant correlation atp < 0.05 was found between Mg-Mn (0.55), Mg-Fe (0.54), Mg-Ni (0.56), Mg-Co (0.48), Mg-Cu (0.63), Al-Cr (0.79), Al-Mn (0.79), Al-...
A water mask was applied to the dataset and the mean value over for the periods before and after the lockdown were calculated. Subsequently, we investigated the effect of the spatial resolution for this relatively small city; the complete time series of the pixel value over the ground station...