The global population is rapidly growing, placing unprecedented pressure on agricultural systems to increase productivity, efficiency, and sustainability. The integration of the Internet of Things (IoT), coupled with advancements in Artificial Intelligence (AI), Machine Learning (ML), and sensor technologies, is revolutionizing the agricultural sector. This Smart Agriculture paradigm allows for real-time monitoring, data-driven decision-making, and automated operations, leading to Precision Farming techniques that optimize resource use, minimize environmental impact, and enhance yields. Smart Agriculture can support efforts for achieving a number of Sustainable Development Goals set by the United Nations, including Zero hunger, Sustainable cities and communities, Responsible consumption and production and Climate action.

This topical collection aims to gather high-quality research and innovative applications focusing on the design, development, deployment, and evaluation of IoT-enabled solutions across the entire scope of agriculture, including traditional crop cultivation and modern animal husbandry (livestock farming).

Topics of Interest

The topics of interest for this collection include, but are not limited to, the following themes:

I. General IoT Infrastructure and Data Analytics

• Novel IoT Architectures: Development of efficient and scalable network topologies (e.g., LoRaWAN, 5G, satellite) for large-scale agricultural environments.
• Edge and Fog Computing: Solutions for real-time data processing and decision-making at the farm edge.
• Sensor Technology: New designs and applications of low-cost, low-power, and robust sensors for environmental monitoring (soil, weather) and biometrics.
• Big Data and AI: Machine Learning and Deep Learning algorithms for agricultural data analysis, predictive modeling, and prescriptive actions.
• Data Security and Privacy: Addressing challenges related to data integrity, security, and ownership in connected agricultural systems.

II. Smart Crop Farming and Horticulture

• Precision Irrigation: IoT systems for real-time soil moisture monitoring and automated water delivery optimization.
• Pest and Disease Detection: Early warning systems using visual, spectral, and olfactory sensors combined with AI.
• Yield Prediction and Optimization: Predictive models based on multi-source data (satellite imagery, drones, ground sensors).
• Automated and Robotic Systems: Integration of IoT with agricultural robotics for planting, harvesting, and localized treatment.
• Vertical/Indoor Farming: IoT control and optimization of climate, lighting, and nutrient delivery systems.
• Early Disease Detection and outbreak prediction: AI-driven analysis of data for timely disease detection and outbreak prediction, as well as proposal of relevant mitigation measures.

III. Smart Animal Husbandry (Livestock and Aquaculture)

• Animal Health and Welfare Monitoring: Wearable and non-wearable IoT sensors for tracking vital signs, activity, and behavioral patterns.
• Precision Feeding Systems: Automated and individualized feed and water management based on animal-specific data.
• Location and Tracking: Real-time localization and geo-fencing for herd management and anti-theft measures.
• Environmental Control: IoT solutions for optimizing barn/coop climate (temperature, humidity, air quality) to reduce stress and disease.
• Animal welfare: leveraging IoT sensors and actuators, together with AI-based analysis to promote and sustain animal health, proper nutrition, expression of normal behaviors and reduction of fear and distress.
• Early Disease Detection: AI-driven analysis of behavioral and physiological data for proactive health management.

Keywords: Internet of Things; Smart Farming; Precision Livestock Management; AI-Based Analysis; Agricultural Big Data; Agricultural IoT

Editors

• Costas Vassilakis, Professor, University of the Peloponnese, Greece
• Spiros Skiadopoulos, Professor, University of the Peloponnese, Greece
• Christos Tryfonopoulos, Professor, University of the Peloponnese, Greece
• Paraskevi Raftopoulou, Research and Teaching Faculty Member, University of the Peloponnese, Greece
• Anastasios Darras, Professor, University of the Peloponnese, Greece