AgriAqua intelligence: Advancing smart farming with ecosystem-based water management solutions

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Qazi Umar Farooq
Addepalli Lavanya
Waqas Ali
Syed Muqthadar Ali
Maloth Bhavsingh


This paper focuses on developing the AgriAqua Intelligence Framework, an innovative integration of artificial intelligence (AI) and Internet of Things (IoT) technologies aimed at revolutionizing water management in smart farming. The research sought to address the challenge of optimizing water usage in agriculture while preserving aquatic ecosystems, thereby promoting sustainable agricultural practices. We employed a combination of experimental and simulation methods to design and test the framework. Advanced IoT sensors were deployed to monitor real-time environmental and agricultural data, while AI-driven analytics were used to process this information and make informed water management decisions. The implementation of the AgriAqua Intelligence Framework resulted in a 30% reduction in water usage and a 20% increase in crop yields across various farming environments. Our predictive models demonstrated a precision rate exceeding 90% in forecasting water demands, significantly enhancing irrigation efficiency. These findings illustrate the effectiveness of integrating AI and IoT in farming to achieve more sustainable water management. The AgriAqua Framework not only supports agricultural productivity but also contributes to the preservation of aquatic ecosystems, showcasing a balanced approach to resource management. The significance of this research lies in its potential to transform agricultural water management practices globally. By demonstrating substantial improvements in resource efficiency and environmental sustainability, the framework offers valuable insights and tools for policymakers, agricultural developers, and environmental scientists aiming to foster a more sustainable agricultural future.

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How to Cite
Qazi Umar Farooq, Addepalli Lavanya, Waqas Ali, Syed Muqthadar Ali, and Maloth Bhavsingh, “ AgriAqua intelligence: Advancing smart farming with ecosystem-based water management solutions”, Int. J. Comput. Eng. Res. Trends, vol. 11, no. 1, pp. 51–60, Jan. 2024.
Research Articles


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