The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Transforming Food Systems: Harnessing the Power of AIOps and MLOps in AgriTech
Abstract
The rapid evolution of artificial intelligence (AI) technologies is revolutionizing food production, enhancing efficiency, sustainability, and scalability. This chapter explores the transformative impact of AIOps (Artificial Intelligence for IT Operations) and MLOps (Machine Learning Operations) in AgriTech. By leveraging predictive analytics, real-time monitoring, and automated decision-making, AIOps optimizes agricultural processes, from soil analysis to crop health monitoring. MLOps facilitates the seamless deployment and maintenance of machine learning models, ensuring continuous learning and adaptation to dynamic farming environments. The integration of these technologies accelerates data-driven decision-making, reduces resource consumption, and enhances food security. Key use cases, such as precision farming, smart irrigation, and supply chain optimization, are examined to illustrate the potential of AI-driven innovations in reshaping food systems.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|