EVENT POSTPONED to MAY 10-14 2021

With the COVID-19 virus being declared a pandemic by the World Health Organization, the Canada and Quebec governments have put in place several temporary mesures to limit the propagation including the interdiction to held events and Canada's border closing.  

As the situation is evolving very quickly and unpredictably, the Local Organizing Committee has decided to POSTPONE the event to MAY 10-14 2021.

Registration is closed until August 31, 2020. Abstract submission is re-open until February 1st, 2021.

IMPORTANT NOTICE:

Authors and registered participants, please see our Continuity Plan.

Workshops

Instructor: Keld Sørensen
Danish Exergy Technology A/S, Skorping, Nordjylland, Denmark

Date: Monday May 10 2021, 1 p.m. to 5 p.m.
Location: TBD
Language: This workshop will be in english
Cost: see Registration
 

StaldVent 5.0 is a decision support PC-program for the design and troubleshooting of ventilation and heating systems for livestock buildings.  It may also be used to model and analyze energy consumption when used with local climate data.  Users can input customized component data files for equipment specification and parts lists using market-available ventilation equipment.

The main focus of this workshop is to understand the capabilities of the StaldVent software, to be able to set up a livestock housing project and work through the ventilation and heating design, and to learn how to create weather files and component files that maximize the versatility of the software.  

StaldVent can be used for ventilation design for dairy, swine, and poultry houses, with options for different types of production and flooring systems.

Course Overview

This introductory half day workshop covers key topics in setting up livestock building ventilation projects in StaldVent:

  1. Overview of StaldVent
  2. Installation and Basic Settings:
    • assigning directories,
    • CSV-format compatibility
    • heat production model selection
  3. Navigation for Design:
    • menus for data entry
    • design values for ventilation and heating
    • summer and winter design process
    • case study example: broilers
    • case study example: hogs
  4. Ventilation Troubleshooting:
    • ventilation setting adjustment options
  5. Creating Custom Files:
    • weather files
    • component files
  6. Energy Use Simulation
    • referencing weather file
    • case study example: broilers
  7. Additional Modules Overview
    • ammonia/air-cleaning
    • cooling/humidifying
    • tunnel ventilation

Following completion of this course, the trainee should

  • have an understanding of the ventilation design and troubleshooting capabilities of StaldVent, including how to work through a new project design
  • have basic knowledge of how to prepare component files for equipment specification
  • have a working knowledge of how to prepare weather files for energy use simulations

Who can attend?

Anyone who has an interest in livestock facility ventilation design can attend.  No previous experience with StaldVent is required (the trial version will be provided to participants in advance of the workshop).  This training workshop may be particularly useful for consulting professionals, biosystems/agricultural engineering students and ventilation/heating equipment suppliers.

Please note that the participants should bring their own PC laptops if they want hands-on experience in working through the lecture topics.

Technical requirements:

Participants should bring their own laptop to the session with StaldVent software trial version installed in advance of the workshop.

About the instructor

Bonakdari

Keld Sørensen, M.Sc., Mechanical Engineer, was educated at the Department of Energy Technology, Aalborg University, Denmark. He has been working in the agriculture industry since 1995.  Keld developed the StaldVent software together with the Danish Agriculture Research Centre, Bygholm, now managed by Aarhus University. As the owner of Danish Exergy Technology A/S, Keld is now responsible for maintenance and development of the StaldVent software working in close cooperation with Danish Universities and leading ventilation companies.

During his career, Keld has been working with the design and troubleshooting of barn systems, and models for the prediction of gas emission from animal houses including air cleaning systems.

Mr. Sørensen is currently involved in several research projects in collaboration with Universities, Research Institutes and ventilation companies. Recently a model for wind effects on natural and mechanical ventilation systems has been developed.

Besides his work within the agriculture industry, Keld also has been involved in the design of numerous biomass and solar boilers.

For more information, please contact Keld at:  This email address is being protected from spambots. You need JavaScript enabled to view it.

Instructor: Hossein Bonakdari, PhD, P.Eng.
Department of Soil and Agri-Food Engineering, Laval University, Quebec, Canada

Date: Monday May 10 2021, 9 a.m. to 4 p.m.
Location: TBD
Language: This workshop will be in english
Cost: see Registration
 

Workshop description:

Artificial intelligence (AI) techniques and machine learning approaches will revolutionize many aspects of future agriculture engineering field. AI can be used as a promising tool to tackle different problems but related aspects of agricultural practical cases as great concern all over the world. The main focus of this course is to understand and discuss the recent developments in AI applications relating to practical engineering application. This course introduces a variety of different topics in AI approaches and learning methods in modeling and prediction of complex datasets. All codes are user friendly and trainees after this course will be able to use them for their cases. 

Course Overview

This introductory one day workshop covers key topics in Artificial Intelligence application in Agricultural Engineering:

  1. Data acquisition/Preprocessing:
    • outliers detection,
    • transferring raw information into usable data,
    • splitting the data into training & testing sets
  2. Classification:
    • decision tree,
    • support vector machine.
  3. Modeling tools:
    • Multilinear Regression (MLR)
    • Multi-layer perceptrons (MLP)
    • Adaptive Network-based Fuzzy Inference System (ANFIS),
    • Extreme Learning Machines (ELM),
  4. Post processing:
    • analysis of statistical indices,
    • scatter plot

Following completion of this course, trainee should

  • have an understanding of major AI techniques,
  • have a working knowledge of how to apply AI technologies to real-world datasets,
  • have gained experience designing and applying AI techniques in Agricultural Engineering practical problems

Who can attend?

Anyone who wants to learn about practical application of machine learning techniques can attend the workshop. No knowledge about programming is required.

Please note that the participants should bring their own laptops with minimum specifications as described in following section.

Technical requirements:

Participants are requested to bring their own laptops with MATLAB software.

About the instructor

BonakdariHossein Bonakdari, Ph.D, P.Eng., earned his Ph.D in Civil Engineering at the University of Caen-France. He has worked for several organizations like most recently as faculty member of department of Soils and Agri-Food Engineering at Laval University, Quebec. He has supervised several PhD and MSc students with teaching experience of more than 12 years in field of Artificial Intelligence application in practical Engineering applications. His fields of specialization and interest include: practical application of soft computing techniques in engineering problems. Results obtained from his researches have been published in more than 180 papers in international journals (h-index=26). He has also more than 150 presentations in national and international conference. He published two books. Dr. Bonakdari is currently leading several research projects in collaboration with industrials partners.

For more information, please contact This email address is being protected from spambots. You need JavaScript enabled to view it.

Instructor: Dr. Prasad Daggupati
School of Engineering, University of Guelph, Canada

Date: Monday May 10 2021, 9 a.m. to 4 p.m.
Location: TBD
Language: This workshop will be in english
Cost: see Registration

Workshop description:

The Soil & Water Assessment Tool (SWAT) is a basin scale hydrological model developed to quantify the impacts of different land management practices in large, complex watersheds. SWAT is a public domain model and is actively supported by USDA Agricultural Research Service, and Texas A& M University, USA. The model accounts multiple hydrological and water quality components such as: weather, surface runoff, return flow, percolation, evapo-transpiration, transmission losses, pond and reservoir storage, crop growth and irrigation, groundwater flow, reach routing, nutrient and pesticide loading, and water transfer. The various application of SWAT has been noted throughout the globe, as is evident by the number of peer-reviewed articles till 2019 (>3500).

The workshop is expected to provide an overview (approx. 20%) and a hands-on session (approx. 80%) of state-of-the-art SWAT (SWAT2012) model to academicians and practitioners in hydrology, watershed management, water resources engineering and agricultural water quality management. In this workshop, we will be demonstrating QSWAT which is a QGIS (open source, publicly accessible) plugin that enables us to run SWAT through a GIS desktop/ interface

What will be delivered?

  • An overview of hydrological models (Theory)
  • An overview on the various applications of SWAT (Theory)
  • Introduction to QSWAT interface (Hands-On/Theory)
  • Watershed delineation using Q-SWAT (Hands-On)
  • Landuse, soil overlay and delineate Hydrological Response Units (HRUs) (Hands-On)
  • Weather/weather generator and remaining inputs (including point sources) to develop SWAT model (Hands-On)
  • SWAT simulations and saving results (Hands-On)
  • Visualization and interpretation of SWAT outputs (Hands-On)

Who can attend?

Anyone who wants to learn about SWAT model can attend the workshop. However, the prospective participants are expected to have a working knowledge (loading vector and raster maps, panning, zooming, selecting features) of QGIS. We will not have time to review basic concepts of QGIS. Please note that the participants should bring their own laptops with minimum specifications as described in following section.

Technical requirements:

Participants are requested to bring their own laptops (Windows 10 OS, Microsoft .Net Framework 3.5, at least 4GB RAM, 20GB free hard disk space, Adobe Reader, Microsoft Office with MS ACCESS. Please go the SWAT model website (https://swat.tamu.edu/software/qswat/) and install the following software before training:

  • QGIS (QGIS Brighton 2.6)
  • QSWAT 1.9
  • SWAT Editor 2012.10.18
  • SWAT-CUP 5.1.6.2

About the instructor

headshot daggupatiDr. Daggupati is an Assistant Professor (Water Resource Engineering) in the School of Engineering at the University of Guelph, Canada. He received his BS degree (2012) from the College of Agricultural Engineering in India, Masters (2007) and Ph.D. (2012) degrees from Kansas State University in USA. He worked as a Post-Doctoral Research Associate and Assistant Research Scientist at Texas A&M University, USA before joining the University of Guelph. Dr. Daggupati’s major contributions to research and practical applications are towards solving emerging water quality and quantity issues using GIS, hydrological modeling, machine learning, and field experimentation at various scales (e.g. field scale, watershed scale) across multiple countries around the world. 

For further questions/information, please reach to us via This email address is being protected from spambots. You need JavaScript enabled to view it..