Novel Deep Learning Approaches to Environmental Management with Sustainability

The application of Earth observation data to Deep Learning (DL) has increased dramatically over the last ten years, with ground-breaking initiatives made possible by the creation of foundational models. Environmental concerns have been addressed with the use of these technologies, which have been used to detect air quality, enhance precision agriculture, and provide alerts about deforestation in near real time. The objective of this research is to present cutting-edge studies and uses of these technologies in areas with limited data. The objective is to tackle the problems associated with environmental development while advancing cloud computing, data democracy, open data access, and capacity-building initiatives. This research concludes by analysing the most current breakthroughs and uses of DL and AI in order to encourage sustainability in a range of domains, such as, renewable energy, smart building energy management, environmental health and accomplishing the sustainable developments Goals(SDGs).