Sensing, Perception, and Robotics for Smart Agriculture Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 121
Editors
Interests: applied robotics; automation; deep learning; digital tools; integrated pest management
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; artificial intelligence; machine learning; agriculture
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The integration of sensing technologies, automation, and robotics is rapidly transforming agricultural systems toward more efficient, data-driven, and sustainable production systems. Global challenges, not limited to labor shortages, rising production costs, climate variability, and the need for resource-efficient farming, have accelerated the adoption of smart and precision agricultural technologies. Advances in IoT-enabled sensors, computer vision, autonomous machinery, and edge computing now enable real-time monitoring, precise input application, and intelligent decision-making across crop, livestock, and controlled environment systems. These technologies are reshaping traditional agricultural practices into intelligent, adaptive, scalable, and resilient systems capable of meeting the future food, fiber, and energy demands of a continuously growing human population.
This Special Issue aims to present recent advances and emerging developments in sensing, automation, and robotics applied to smart agricultural systems. We invite contributions that focus on the design, development, integration, and deployment of intelligent systems for food production agriculture applications. Submissions addressing methodological innovations, simulation and/or proof-of-concept scale studies, and real-world implementations are encouraged, particularly those demonstrating practical relevance, scalability, and field validation. Topics of interest include, but are not limited to:
- Sensor technologies and IoT systems for agricultural monitoring.
- Computer vision and machine learning for crop and livestock applications.
- Advanced machine learning and AI systems in agriculture.
- Autonomous agricultural machinery and robotic systems.
- Precision agriculture and site-specific management technologies.
- Edge computing and real-time data analytics in agriculture.
- Sensor fusion and multi-modal data integration.
- Robotics for weed control, harvesting, and field operations.
- Applications in controlled environment agriculture (CEA).
- Smart livestock monitoring and behavior analytics.
- Decision support tools for pest or resource management or optimization.
- Internet of Things (IoT) device or cyber-physical systems in agriculture.
- Sustainable and resource-efficient agricultural technology.
Dr. Chetan Badgujar
Dr. Sathishkumar Samiappan
Guest Editors
Manuscript Submission Information
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Keywords
- smart agriculture
- precision agriculture
- agricultural sensing
- internet of things (IoT)
- computer vision
- machine learning
- agricultural robotics
- autonomous systems
- edge computing
- digital agriculture
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