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This chapter details initially acquiring an open-source UAV dataset and creating a Google Earth dataset of vehicles, and creating the metadata for these images. Then training a deep learning object detection model, YOLOv4, to generate the best training weight files, having a very high mean average precision (mAP). It is the measure of how precisely the model is detecting the objects specified in the metadata of the validation dataset. The higher this value, the more accurate the model is, with the specific data it has been trained upon. Then deploying the model on various satellite data of certain areas like parking lots, toll booths, and roads, over a certain period of time, to count the number of vehicles in RGB images and from those images calculate factors like maximum capacity of parking lots, average vehicle density of roads, congestion rate in toll booths, length of congestion in toll booths, etc. The model trained on the UAV Dataset at various conditions of weather, daytime, and different resolutions are tested over other UAV Datasets and the trained weights are uploaded to GitHub for future use.

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The insects most prominently colonized in a nutrient-rich fresh dung habitat are mainly beetles and flies and the group is termed collectively, the dung community. Coprophagous insects play an important role in tropical ecosystems by providing essential functions including mechanically breaking down excrement into smaller-sized particles, mixing of organic matter in the soil, soil aeration, nutrient cycling and to remove unhealthy materials from their surroundings. Against this backdrop, present study is an attempt to assess the insect diversity and abundance inhabiting dairy farm dung community in North & South 24 Parganas, West Bengal along with the study on the life cycle pattern of frequently encountered dung beetle taxa, Oniticellus cinctus (Fabricius) and to observe their role in the decomposition. Altogether 2 dung beetles, 4 dung loving beetles, 8 dung loving flies, 17 dung associated insects of different groups, one mesostigmatic mite species are recorded from cow and buffalo dung community during the study period. December is the period of maximum dung beetle abundance. Beetle activity gets greatly diminished with the rise of temperature above 30 °C. The brood ball made by the functional group 'Dwellers' is for oviposition. The brood balls provide the immatures with an assured food supply. Egg to adult developmental period ranges between 43-51 days. The teneral adult period observed under laboratory conditions is 2-3 days. Our findings show that extensive management practices result in more pats with higher insect abundances. Data proves that the members of these two orders, Coleoptera and Diptera are almost perfectly separated seasonally. Flies are most abundant in the premonsoon while beetles during monsoon and postmonsoon. Season is therefore the main temporal axis separating ecologically similar species of dung-inhabiting insects in tropical habitats, while succession aggregates species that may have similar environmental tolerances. This separation between ecologically similar taxa of beetles and flies may be attributable to either competition-based niche segregation or to temperature tolerance-based habitat filtering.