Integrating Predictive Models and Remote Sensing for Sustainable Agriculture, Energy, and Environmental Management
This paper focuses on a critical analysis of the application of integrated works of predictive models and remote sensing in agriculture and renewable energy, and environmental conservation. This method involves the use of deep learning approaches, UAV data collection and hyperspectral imagery which gives the researchers an understanding on the real world effectiveness of the systems and technologies analyzed; on predictive models and resource utilization efficiency.
Authors
- Vishal Jain (ORCID: https://orcid.org/0000-0003-1126-7424)
- Ibrohimbek Yusupov (ORCID: https://orcid.org/0000-0002-2166-6683)
- Raj Kumar (ORCID: https://orcid.org/0000-0002-2382-1325)
- Danish Ather (ORCID: https://orcid.org/0000-0003-1596-5553)
- Sonia Duggal (ORCID: https://orcid.org/0000-0003-0713-5904)
- Pinki Sagar
Institutions
- Tashkent University of Information Technology (UZ)
- Manav Rachna International Institute of Research and Studies (IN)
- Sharda University (IN)
Publication Details
- Published
- 2024-11-13
- DOI
- https://doi.org/10.1109/ictacs62700.2024.10841299
- Citations
- 3
- Primary Topic
- Water-Energy-Food Nexus Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.60