• Manmeet Kaur
• Jasleen Kaur
• Manav Chauhan
• Jaspreet Kaur

The agricultural industry is essential for sustaining human civilization by providing food, fibre, and raw materials. Technological progressions have reshaped agriculture significantly, with Artificial Intelligence (AI) and Machine Learning (ML) playing pivotal roles. This article presents an overview of the agricultural sector, underlining the significance of technological advancements. It examines how AI and ML have revolutionized farming practices. The agricultural sector encompasses crop production, animal husbandry, aquaculture, forestry, and agribusiness. Technological advancements have become indispensable in tackling challenges such as resource constraints, climate change, and population growth. The importance of technology in agriculture is apparent in heightened productivity, precision farming, efficient resource allocation, disease and pest management, and optimization of supply chains. AI and ML technologies have emerged as formidable tools in agriculture, facilitating crop and soil monitoring, precision agriculture, agricultural robotics, predictive analytics, livestock management, and the utilization of agricultural drones. The integration of AI and ML holds tremendous potential for boosting productivity, minimizing resource depletion, fostering sustainability, and facilitating data-driven decision-making in the agricultural sector.

Keywords: Agricultural industry, artificial intelligence (AI), machine learning (ML), sustainability, technological advancements.

"Revolutionizing Agriculture through Artificial Intelligence and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.j83-j90, April-2024, Available :http://www.jetir.org/papers/JETIR2404909.pdf

"Revolutionizing Agriculture through Artificial Intelligence and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppj83-j90, April-2024, Available at : http://www.jetir.org/papers/JETIR2404909.pdf