Next-Generation Smart Farming: The Role of Agricultural Large Models and Intelligent Machinery
A Special Issue of AgriEngineering (ISSN 2624-7402) belonging to the section "Computer Applications and Artificial Intelligence in Agriculture".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 1029
Editor
Special Issue Information
Dear Colleagues,
The global agricultural sector is on the brink of a profound transformation, driven by the convergence of artificial intelligence, big data, and advanced robotics. This Special Issue is dedicated to exploring this pivotal shift from data-driven farming toward a new era of cognitive and autonomous agriculture. Central to this revolution is the synergistic integration of two disruptive technologies: Agricultural Large Models (AgLMs) and next-generation intelligent machinery.
Agricultural Large Models (AgLMs), trained on vast multimodal datasets, including satellite imagery, weather history, soil science, plant physiology, and real-time sensor data, are emerging as the “digital brain” of the farm. These foundational models can perform complex tasks such as predictive yield modeling, precise disease and pest identification, hyper-localized resource recommendation, and generation of optimal management strategies under climate uncertainty. They move beyond simple analytics to offer generative, prescriptive insights, effectively understanding the intricate language of agronomy.
These digital insights must be physically actuated, which is the role of intelligent machinery. The field is evolving from automation to full autonomy, with smart tractors, robotic harvesters, drones, and swarms of mini-robots that can perceive their environment, make real-time decisions, and perform delicate operations with minimal human intervention. Empowered by edge computing and advanced sensors, these machines become the “hands and feet” of AgLMs, closing the loop between data-driven decision-making and physical action. This enables tasks like millimeter-accurate weeding, plant-by-plant treatment, and selective harvesting at scale, fundamentally redefining precision agriculture.
This Special Issue will serve as a platform for cutting-edge research that bridges this digital–physical divide. We invite contributions on the development and application of AgLMs, advanced perception and control algorithms for intelligent machinery, human–robot interaction in agricultural settings, and scalable cloud–edge architectures for farm-wide intelligence. Furthermore, we welcome discussions on critical socio-economic dimensions, including technology adoption barriers, data ownership, and the ethical implications of autonomous systems. By fostering interdisciplinary dialogue, this collection aims to chart the course toward a more resilient, productive, and sustainable agricultural future, powered by cognitive machines.
Dr. Gang Yuan
Guest Editor
Manuscript Submission Information
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Keywords
- agricultural large models
- multimodal embodied perception
- generative AI decision-making
- digital twin virtual simulation
- embodied intelligence of robots
- electric intelligent power equipment
- immersive virtual reality
- agricultural carbon intelligence
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