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Objectives
- DFT based Computational analysis of pure and doped material.
- Transient charging and discharging analysis of developed material.
- Lab synthesis and characterization for possible biosensor applications.
- To test and validate the AI integrated model and the device for Agriculture applications.
Issues Involved
Despite the benefits, several challenges hinder widespread adoption:
- High Initial Costs: The implementation of AI and renewable technologies requires significant investment, which may be a barrier for small-scale and medium scale users.
- Scalability Issues: Energy systems must adapt to varying geographical conditions, energy demands, and resource availability. Designing scalable AI models that generalize across regions remains complex.
- Integration Complexities: Combining AI-driven renewable systems with existing agricultural practices can be challenging, especially in regions with limited infrastructure or technical knowledge. Overcoming these obstacles requires supportive government policies, financial incentives, and capacity-building programs for farmers and stakeholders.
Team Lead
Dr. Divya Gautam
divya.gautam@nmims.edu
Collaborator
Dr. Pankaj Mishra
D.Sc(R),Ph. D, M.Sc( Electronics & Physics) (Gold medalist), (Co-Principal Investigator),
Professor & Head, ASET,
Amity University Madhya Pradesh, Gwaliorrajgurav.mishra@nmims.edu
