Development of an ANN Integrated Streamlit Web App for Estimating Soil Compaction Beneath Agricultural Tyre

The soil compaction with the operation of a powered bias-ply tyre in different soil conditions, i.e. soft, medium and hard soils, was estimated using a developed ANN model. Inputs to the model were pull, inflation pressure, wheel load, soil condition, and cone index before operating the tyre, whereas cone index after operating the tyre was the output parameter. The tyre was tested at varying normal load (1000 and 1400 kg) and inflation pressure (82.74–137.90 kPa). The ANN model was trained and tested on a data set of 303 data points for the 13.6-28 bias-ply tyre, with a split ratio of 80:20, respectively. The best results were obtained with trained model having 5-8-6-1 architecture. The correlation heatmap revealed that among all other parameters, pull had the strongest correlation with cone index after operation with 13.6-28 powered wheel. The maximum soil compaction was observed at normal load of 1400 kg and 137.90 kPa inflation pressure in all soil conditions. Soil compaction was increased with the increase in pull, inflation pressure, and wheel load in all soil conditions. The developed model was also deployed in Streamlit web application interface, in which user can enter the input parameters and application will show the predicted value of cone index after operation of the tyre and amount of soil compaction incurred due to it.