Sustainable Precision Agriculture in the Era of IoT and Artificial Intelligence
July 18-20, 2023
BARD
Bard Workshop
A three-day workshop with podium presentations delivered mainly by keynote and invited speakers who are leading experts in the relevant fields of Artificial Intelligence (AI) in Precision Agriculture (PA), with additional selected voluntary presentations . Roundtable discussion sessions will follow on the topic of AI in PA.
The workshop will be held for three days from July 18-20, 2023, which will include two days of scientific lectures and discussions at Ben Gurion University in the Negev (BGU), located in Beer Sheva, and one day for a professional tour at the Model Farm at Newe Ya'ar, run by the Agricultural Research Organization (ARO), located in the northern part of Israel. It will focus on PA development in Israel and different states in the USA with similar agriculture enterprises and agriculture-driven economies. The desired outcomes of the proposed workshop are:
- Exchange of information and expertise among the workshop participants.
- Inclusion of advanced graduate students and postdocs as part of their training and career development.
- Establishment of a network of USA and Israel-based PA experts that will encourage research collaborations that will accelerate PA development through coordination and exchange of information through follow-up activities (e.g., satellite meetings, targeted workshops, group websites, social media, etc.)
- Publication of a synthesis/review paper or joint research proposal based on workshop discussions and activity outcomes.
Location: All Sessions will take place at the Ben Gurion University Campus in the W.A. Minkoff Senate Building (71A).
Registration is free but you must sign-up in advance.
Schedule
AG-AI Workshop Tentative Program
Developing and adopting IoT/AI/ML techniques and applications in agriculture is challenging but highly important. The significant variability and complexity of agricultural systems are key challenges. The workshop will focus on big data acquisition and AI/ML-based analytics in PA. The emphasis will be on the application of data science approaches in PA. In the workshop, we will present state-of-the-art IoT/AI/ML methods, tools, and applications and consider how these can be applied to enable more sustainable agricultural practices. The workshop sessions will occur on the first two days, July 18 & 19, followed by a professional tour on July 20.
| Day 1 – July 18, 2023 | |
| Opening session- GREETINGS | 8:30-9:30 |
| Session A | 9:30-11:30 |
| Coffee Break | 11:30-12:00 |
| Session B (Part 1) | 12:00-14:00 |
| Lunch Break | 14:00-15:00 |
| Session B (Part 2) | 15:00-16:40 |
| Coffee Break | 16:40-17:00 |
| Session C (Part 1) | 17:00-18:40 |
| Opening Dinner | 20:00-22:00 |
| Day 2 – July 19, 2023 | |
| Session C (Part 2) | 9:00-11:00 |
| Coffee Break | 11:00-11:20 |
| Session D | 11:20-13:20 |
| Lunch Break | 13:20-14:20 |
| Session E | 14:20-16:20 |
| Coffee Break | 16:20-16:40 |
| Session F - Panel Discussion | 16:40-17:30 |
| Driving from Beer-Sheva to Nazareth | 18:00-20:00 |
| Dinner | 20:00-22:00 |
| Day 3 – July 20, 2023 | |
| Breakfast | 6:30-7:30 |
| Driving from Nazareth to Newe Ya'ar, The Model Farm | 7:30-8:00 |
| Neve Ya'ar- Local tour of infrastructure in the Model Farm | 8:00-10:00 |
| Coffee Break | 10:00-10:30 |
| Studies in the Field Crop Platforms of the Model Farm | 10:30-11:10 |
| Presentation from Agrilight Ltd | 11:10-11:30 |
| Opening of the first discussion session | 11:30-12:30 |
| Lunch Break | 12:30-13:30 |
| Roundtable 1: Group Discusions | 13:30-15:00 |
| Roundtable 2: Joint Discussion | 15:00-16:30 |
Workshop summary and closure | 16:30-17:30 |
Driving from Model Farm to Tel Aviv | 17:30-19:30 |
Sessions
Session A: Understanding the role, advantages, limitations, and gaps in sensor development, networking, integration, fusion, and applications in PA
- Dr. Jason Hallstrom, National Science Foundation, USA, NSF Investments in the Future of Precision Agriculture
- Prof. Steven Mirsky, US Department of Agriculture, USA, Operationalizing Precision Sustainable Agriculture
- Dr. Victor Alchanatis, Agricultural Research Organization (ARO), Israel, Integration of Artificial Intelligence and Sensing for Precision Farming
- Prof. Avital Bechar, ARO, Israel, Agricultural Robots and AI for Precision Agriculture
- Dr. Yafit Cohen, ARO, Israel, Big Data in Area-Wide and In-Field Scales
- Dr. Iftach Klapp, ARO, Israel, Enhancement of Low-Cost Sensing Devices for Precision Agriculture
Session B (Part 1): Defining the benefits of using big data and AI/ML to maximize the impact and applicability of PA and to support decisions for sustainable agriculture
- Prof. James Krogmeier, Purdue University, USA, Networking and Computing Infrastructure for Large Scale Agricultural Testbeds Supporting the IoT4Ag Engineering Research Center
- Dr. Brian Needelman, University of Maryland, USA, Integrating Topographic and Soil Survey Analyses into Predictions of Cover Crop Performance in Precision Sustainable Agriculture Models
- Dr. Yael Salzer, Agricultural Research Organization (ARO), Israel, Towards Informed Postharvest Logistic Management Systems to Reduce Food Loss, and Other Challenges
- Dr. Ariel Shabtay, ARO, Israel, Integrating Biomarkers into the Electronic-Sensors based PLF Tool Box
- Dr. Shai Sela, Agmatix, Israel, Harnessing Data Standards to Accelerate Collaborative Agronomic Big Data Research
Session B (Part 2): Defining the benefits of using big data and AI/ML to maximize the impact and applicability of PA and to support decisions for sustainable agriculture
- Prof. Dorivar A. Ruiz Diaz, Kansas State University, USA, Decision Support Tools for Farmers: Field Data Collection Challenges and Opportunities through Multidisciplinary Collaboration
- Prof. Taejoon Kim, University of Kansas, USA, Predicting In-Season Soil Mineral Nitrogen in Corn Production Using Generative Deep Learning Model
- Dr. Offer Rozenstein, Agricultural Research Organization, Israel, Data-Driven Estimation of Actual Evapotranspiration to Support Irrigation Management: Testing Two Novel Methods based on an Unoccupied Aerial Vehicle and an Artificial Neural Network
- Prof Yeal Edan, Ben Gurion University of the Negev (BGU), Israel, AgRobotics in the Era of IoT & AI for Sustainable PA
- Prof. Tal Svoray, BGU, Israel, A Machine Learning and Geoinformatics Water Erosion Approach in Agricultural Catchments
Session C (Part 1): Understanding big data advantages and limitations in key agricultural contexts: livestock farming, fertilization, irrigation, orchard management, site-specific weed management, pest management, and disease detection
- Dr. X. Carol Song Purdue University, USA, GeoEDF: A Framework for Designing and Executing Reproducible Geospatial Research Workflows in Science Gateways
- Prof. Raj Khosla, Kansas State University, USA, Artificial Intelligence for Agricultural Sustainability
- Prof. Uri Yermiyahu, Agricultural Research Organization (ARO), Israel, Reforming Crops’ Mineral Diagnostics by Chemometrics to Sustenance the Empirical Requirements of Decision Support Tools in Farming
- Dr. Yael Laor, ARO, Israel, Introduction to the Model Farm for Sustainable Agriculture, Newe Ya'ar, Volcani Institute
- Dr. Ehud Strobach, ARO, Israel, Seasonal Predictions of Crop Yield under Changing Climate Conditions: The Coupled Crop-Climate Modeling Approach
Session C (Part 2): Understanding big data advantages and limitations in key agricultural contexts: livestock farming, fertilization, irrigation, orchard management, site-specific weed management, pest management, and disease detection
- Prof. Won Suk (Daniel) Lee, University of Florida, USA, Specialty Crop Production in using Artificial Intelligence in Florida, USA
- Prof. Dharmendra Saraswat, Purdue University, USA, Unmanned Aerial Systems for Plant-Stress Identification and Monitoring
- Dr. Tarin Paz-Kagan, Ben Gurion University, Israel, Advances in Agricultural Unmanned Aerial Vehicles - Focus on Sensing Applications
- Dr. Ran Lati, Agricultural Research Organization (ARO), Israel, Early Sub-Soil Detection of Broomrape Infestation Using Spectral Data
- Dr. Or Sperling, ARO, Israel, Modeling The Cost of Deficit Irrigation
- Dr. Shahar Baram, ARO, Israel, Using Remote Sensing to Close the Yield Gap in Almond Orchards
Session D: Developing an AI system for early detection of yield problems in agriculture: Innovative research at the confluence of AI /ML, big data, and PA
- Prof. George Vellidis, University of Georgia, USA, Big Data, IoT, and AI Applications to Solve Agricultural Problems in the Southeastern USA: Three Case Studies
- Dr. Lizhi Wang, Iowa State University, USA, A Digital Twin Framework for Precision Agriculture
- Prof. Naftali Lazarovitch, Ben Gurion University of the Negev (BGU), Israel, Improving Fertigation Scheduling by Combining Continuous Monitoring and Numerical Modeling of the Root Zone
- Dr. Assaf Chen, MIGAL, Israel, Early Detection of White Mold Disease in Field Crops via Remote Sensing and Machine Learning
- Dr. Anna Brook, University of Haifa Israel, Multisource Remote Sensing Sensors/Platforms Integration and Synergy in Smart and Sustainable Agriculture
- Prof. Charlie Messina, University of Florida, USA, Emergence Agriculture: Concept for Managing Complexity in Maize Production
Session E: Investigation and evaluation of the influence of AI/ML in current and future PA contexts
- Prof. Ioannis (Yiannis) Ampatzidis, University of Florida, USA, AI-Enhanced Technologies for Precision Management of Specialty Crops
- Prof. Glen Rains, University of Georgia, USA, AI, Data Analytics and Precision Tools for Intelligent and Climate-Resilient Agriculture Systems
- Dr. Fadi Kizel, Technion- Israel Institute of Technology (Technion), Israel, AI-Based Muti-Sensor Data Fusion for Spatially Enhanced Spectral Mapping Products
- Prof. Eyal Ben-Dor, Tel Aviv University, Israel, Precision Agriculture: The Pedosphere under a Spectral Binocular
- Prof. Gilad Ravid, Ben Gurion University, Israel, Exploring Date Collection Methods and Investigating the Emergence of Macrophomina Phaseolina in Cotton Fields: A Comprehensive Study in Agricultural Decision Support Systems
- Prof. Raphael Linker, Technion, Israel, Predicting Nitrogen Content in Citrus Orchards Canopy using UAV and Satellites Data
Session F: Summarizing existing gaps in PA surrounding IoT/AI/ML and brainstorming ways to overcome them
A Panel Discussion
professional Tour
The Model Farm is a pioneering project in Israel and unique on an international scale. It spans over 40 hectares and incorporates four major platforms: an almond orchard, a field-crop plot, a precision-based feedlot, and a waste recycling site. The Model Farm will test, demonstrate, and assimilate sustainable agricultural practices and agricultural conservation principles, aiming to bridge the gap between the research world and the farmer.
The tour will take place on July 20, the last day of the workshop.
More Information Regarding the Farm
Organizing Committee
Dr. Tarin Paz-Kagan, Ben Gurion University of the Negev (BGU), Jacob Blaustein Institutes for Desert Research, Israel
Senior Lecturer & Organizing Committee
Dr. Paz-Kagan is a remote-sensing scientist who is using computing and information technology dedicated to soil and plant interaction for agricultural and environmental studies. Her research focuses on identifying and quantifying spatial and temporal patterns in soil and plant distribution and their interactions in response to biotic and abiotic stress.
Dr. Victor Alchanatis, Agricultural Research Organization (ARO), Volcani, Israel
Senior Research Scientist
Dr. Alchanatis is a senior research scientist at the Institute of Agricultural Engineering at ARO. His research focuses on sensing technologies and their application to agricultural and environmental systems: optical sensing in the visible, near-infrared and thermal infrared spectrum, hyper-spectral and multi-spectral image processing, computer vision and classification systems.
Dr. Yael Laor, ARO, Volcani, Israel
Scientific Director, The Model Farm for Sustainable Agriculture
Dr. Laor researches the management and recycling of agricultural and municipal wastes and the environmental impacts associated with these processes. Composting is in the core of her research work, including aspects of process control, emissions of gases and odors, pathogen survival and compost quality for agronomic use.
Dr. Jason O. Hallstrom, National Science Foundation (NSF), USA
Program Director, NSF
Dr. Hallstrom serves within the Computer and Information Science and Engineering Directorate. His areas of program responsibility include Computer Systems Research, Future of Semiconductors, Formal Methods in the Field, Expeditions in Computing, CISE Community Research Infrastructure, and Mid-scale Research Infrastructure-1.
Book of Abstracts and Presentations
Book of Abstracts
See the attached Book of Abstracts for the lectures that were presented at the Workshop. Thank you to all that participated.
Learn MorePresentations
A selection of the lectures that were presented at the workshop are available for viewing
Learn MoreVenue and Accomodations
