Events2nd International Online Conference on Agriculture
Published
with-doi10.3390/IOCAG2023-16877 (registering DOI)
This submission belongs to the session S6. Artificial Intelligence for Advanced Analyses in Agriculture; of the event 2nd International Online Conference on Agriculture
Published date
11 Mar, 2024
Academic Editor
author-avatarFrancesco Marinello
Citation
Aamir Raza, Muhammad Adnan Shahid, Muhammad Safdar, Muhammad Zaman, Rehan Mehmood Sabir, The Role of Artificial Intelligence in Climate-Smart Agriculture: A Review of Recent Advances and Future Directions, in Proceedings of 2nd International Online Conference on Agriculture, 1 November–15 November 2023, MDPI: Basel, Switzerland, doi: 10.3390/IOCAG2023-16877
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The Role of Artificial Intelligence in Climate-Smart Agriculture: A Review of Recent Advances and Future Directions

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1. Department of Irrigation & Drainage, University of Agriculture, Faisalabad, 38000, Punjab, Pakistan, Pakistan
2. Department of Irrigation & Drainage, University of Agriculture, Faisalabad, 38000, Punjab, Pakistan
3. Agricultural Remote Sensing Lab of National Center of GIS and Space Applications (NCGSA-ARSL), University of Agriculture, Faisalabad, 38000, Punjab, Pakistan
Abstract

Artificial intelligence (AI) has the potential to revolutionize agricultural analysis and improve climate-smart farming practices. This paper explores the transformative role of AI in climate-smart agriculture, focusing on recent advances and future directions. Climate change poses significant challenges for agriculture, including weather variability, water scarcity, and the emergence of new pests and diseases. Leveraging AI technology, this research delves into how agricultural analysis can be revolutionized, leading to improved climate-smart farming practices. Recent advances in AI, such as machine learning and deep learning, have enabled the development of powerful predictive models that can be used to forecast climate events, optimize irrigation schedules, and detect early indicators of crop stress or disease outbreaks. This information can be used to proactively alter farming operations and resource allocation tactics, resulting in increased productivity and less environmental impact. AI-powered precision agriculture technology, such as autonomous drones and sensor networks, also enables real-time monitoring and data collection. This allows farmers to collect precise data on crop health, soil moisture levels, and fertilizer requirements. AI algorithms can then deliver practical crop management advice, such as optimal planting schedules, fertilizer application rates, and pest control techniques. The integration of AI in climate-smart farming also holds potential for long-term agricultural practices. Predictive analytics and AI-based supply chain optimization can improve post-harvest management, storage, and distribution processes, reducing food loss and increasing overall efficiency. The research emphasizes how AI can enable farmers to make data-driven decisions, optimize resource consumption, and enhance resilience in the face of climate challenges. By integrating AI into agriculture, this paper presents a pathway toward sustainable food production, environmental stewardship, and improved farmer livelihoods.

Keywords
Artificial Intelligence
Agricultural Analyses
Machine Learning
Predictive Models
Precision Agriculture
Resource Efficiency
Manuscript
A DISEASED THREE-SPECIES HARVESTING FOOD-WEB
MODEL WITH VARIOUS RESPONSE FUNCTIONS
Artificial Intelligence-Enabled Precision Agriculture: A Review of Applications and Challenges