Integrated Aqua with Paddy Analysis for Pisciculture Using Reinforcement Learning
To maximize and improve the effectiveness of pisciculture methods, this project focuses on developing an integrated system that balances aquaculture and paddy farming. The objective is to use reinforcement learning techniques to make intelligent decisions by identifying and analyzing critical characteristics that are crucial for the growth of fish as well as rice crops. The aquaculture component's factors include pH, temperature, dissolved oxygen levels, humidity, ammonia, and water quality. These elements have a critical role in influencing the general well-being and growth of fish in aquatic environments and as well as Important factors for rice cultivation include soil moisture content, nutritional levels, ambient temperature, and solar exposure. These factors work together to affect the growth and output of paddy crops.
Authors
- Shaik Sikindar (ORCID: https://orcid.org/0009-0001-4720-3978)
- Mohammad Azhar
- Vipin Kumar (ORCID: https://orcid.org/0000-0002-8054-7262)
- SK Bhadar Saheb
- Tejaswi Maddineni
Institutions
- Vignan's Foundation for Science, Technology & Research (IN)
- Indian Institute of Technology Tirupati (IN)
- Film Independent (US)
Publication Details
- Published
- 2024-12-17
- DOI
- https://doi.org/10.1109/icicnis64247.2024.10823325
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00