Abstract
This work provides environmental protection and sustainable development to manage network of reservoirs and canals for identifying inner water link under river. Continuous monitoring of the river width, speed, flow, and longitude images of the river are analyzed by time series and AIoT technique to predict the path and trace the direction of inner and outer flow of river. At the same time, get prediction of data and images on soil alleviation and erosion. Extract the significance of rivers / drainage images from high-resolution multispectral satellite by framework is developed to identify river drainage characteristics such as inner water link, prediction of river path by its width and longitude and compare the images after natural calamities. Analyzed the multi spectral images to develop digital elevation maps of river drainage features and provide guidance for disaster preparedness.
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Ganesan, V., Talluru, T., Challapalli, M., Seelam, C. (2023). Identifying River Drainage Characteristics by Deep Neural Network. In: Ogudo, K.A., Saha, S.K., Bhattacharyya, D. (eds) Smart Technologies in Data Science and Communication. Lecture Notes in Networks and Systems, vol 558. Springer, Singapore. https://doi.org/10.1007/978-981-19-6880-8_7
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DOI: https://doi.org/10.1007/978-981-19-6880-8_7
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