Earth Precision Agriculture

August 10-14, Calgary, Alberta, Canada

Controlled Environment Agriculture Conference Track

Build the autonomous, intelligent, and resource-efficient indoor farms of the future, from sensor to harvest

About the Controlled Environment Agriculture Conference Track

This specialized controlled environment agriculture conference session welcomes abstracts that demonstrate how automation, artificial intelligence (AI), and robotics are advancing sustainable controlled environment agriculture (CEA), such as hoophouses, greenhouses, and indoor vertical farms.

We seek research and case studies that translate sensing and data into actionable insights to enhance energy, water, nutrient, and labor efficiency while maintaining yield, quality, and biosecurity. The track emphasizes how complementary, multidisciplinary approaches can generate richer, more actionable insights into CEA.

Dedicated to indoor farming, the controlled environment agriculture conference goes beyond commercial trade shows to focus on rigorous, peer-reviewed science. Presentations and workshops will examine critical issues such as digital twin development, predictive modeling for climate resilience, precision environmental control, and the integration of autonomous robotic systems for harvesting and crop monitoring. Attendees of the controlled environment agriculture conference will also benefit from the broader Earth Precision Agriculture ecosystem, gaining access to 20 complementary tracks. This cross-pollination of ideas creates unparalleled opportunities for interdisciplinary collaboration that extends well beyond the five days in Calgary.

The research areas of interest include, but are not limited to:

Digital Twins and Predictive Modeling

AI/ML for Prediction: Use of artificial intelligence and machine learning (including physics-informed or hybrid methods) for predicting yield, quality, stress, and resource use.
Digital Twin Development and Calibration: Research on developing and calibrating digital twins for real-time forecasting and optimization of CEA operations.
Hydrological and Environmental Modeling: Studies on modeling and forecasting the impacts of climate change on water availability, quality, and demand at various scales (farm, watershed, basin).

Sensing, Data, and Analytics

Advanced Sensor Networks: Research on developing and deploying sensors for monitoring substrate moisture, nutrient solution properties (e.g., EC, pH), air quality (e.g., CO2, VOCs), and plant physiological status within indoor farms.
Data Analytics: Use of data from in-facility imaging systems and sensor networks for analytics on edge or cloud platforms to improve operational decisions and workflow automation.
Data Quality, Interoperability, and Cybersecurity: Addressing challenges related to interoperability, data quality, cybersecurity, and biosecurity in commercial CEA.

Robotics and Autonomous Systems

Precision Environmental Control and Automation

Automated Irrigation and Fertigation: Development and application of advanced technologies (e.g., AI, IoT) for real-time monitoring and optimization of irrigation and fertigation scheduling.
AI for Environmental Control: AI-powered decision support for precision control of heating, cooling, ventilation, dehumidification, and lighting.
Climate Adaptation and Mitigation: Research on designing resilient irrigation, water reuse, and drainage systems for controlled-environment agriculture to ensure reliable operation under climate-driven water scarcity and extreme weather events.