Smart Ag Research

Smart agriculture research is the primary way Olds College tests and validates budding technology to enhance the way producers do agriculture. We take new and developing products and test them according to producer needs, comparing them to proven or established standards and technologies. Smart agriculture research works closely with Olds College Smart Farm to enhance agricultural operations at the College through innovation and the integration of technology on campus, providing unique education opportunities for the next generation of farmers.

Smart Agriculture Research Goals

To support producers by providing them with an accurate in-depth analysis of developing technology so they can make informed integration decisions.
To evaluate, demonstrate, and validate developing technologies in comparison to pre-established agricultural standards.
To improve production efficiency through technology by increasing crop yield and livestock production while decreasing waste and used resources.

Telus Ag - Farm at Hand Posted January 26, 2021

Farm at Hand is a software that provides systems for field and inventory management, activity tracking and equipment information management which can support producers by simplifying decision-making and increasing profits. In partnership with TELUS Ag, Olds College evaluated the Farm at Hand platform's overall cost, ease of use, interoperability, performance, security, support, features, and functionality.
Funder: TELUS
Telus Ag - Arable Microclimate Sensor Posted January 26, 2021

Having a microclimate sensor in the field means knowing the levels of precipitation, temperature, wind, and weather patterns for your farm, accessible from your mobile device. Olds College is working with TELUS Ag to evaluate Arable Labs Microclimate Sensor’s connectivity, accuracy, dependability, interoperability, user interface, and customer service.
Funder: TELUS
Telus Ag - Hummingbird Posted January 26, 2021

Hummingbird is an Artificial Intelligence business that gathers satellite imagery to define variable rate prescription maps. In partnership with TELUS Ag, Olds College is evaluating the process of creating these prescription maps and the functionality of the platform. Olds College also looked at the realized savings in chemical use as a result of using the prescription for fungicide application.
Funder: TELUS
In-Bin Drying Monitors Posted October 26, 2020

The In-Bin Drying Monitor is a technology developed by Top Grade Agriculture that uses a proprietary algorithm with pressure, temperature and humidity sensors to optimize grain drying procedures. This technology, which is being evaluated by Olds College, could improve the cost efficiency of drying grain using in bin drying strategies as an alternative to specialized grain drying equipment requiring a high initial capital investment.
Partner: Top Grade Agriculture
Funder: NSERC WED and CFI/RCP, Top Grade Ag and Olds College
Project Type: Evaluation
CropScan 3300H Grain Analyzer Posted October 26, 2020

The Crop Scan 3300H Grain Analyzer is an agricultural digital technology that is installed on the college’s combine, and is capable of measuring protein and moisture content of harvested grain, oil seeds, and pulse crops in near-real time. Olds College is working closely with Farmers Edge to evaluate the technology, which could lead to producers being able to map geospatial crop information and improve field management.
Partner: Farmers Edge
Funder: Vantage Canada, Western Economic Diversification, Canada Foundation for Innovation, and NSERC, Olds College, Farmers Edge
Project Type: Evaluation
Grazing Management Project Posted August 18, 2020

The grazing management project was established to evaluate and demonstrate the use of various remote grazing management technologies. Olds College is working evaluating the functionality and value of several technologies to help producers understand how these technologies can help increase the efficiency of their intensive grazing systems. The project is also comparing intensive and conventional grazing systems, side-by-side, to quantify the differences on animal, forage, and soil health.
Partner: Allflex
Funder: Alberta Innovates, Western Economic Diversification, with in-kind contribution from Union Forage
Growsafe Posted August 17, 2020

Growsafe is currently developing an in-pasture weighing system prototype that will provide producers with the ability to monitor their cattle’s weight on a daily basis without the need to handle animals. Olds College is working with Growsafe to validate the technology and measure its effectiveness at weighing cattle, monitoring cattle growth, and taking daily inventory of herds.
Partner and Funder: Growsafe
Heifer Development Program Posted August 17, 2020

In Partnership with Neilson Signature Beef, Olds College is seeking to optimize the best practices used in heifer development programs. The project includes measuring the stress levels of heifers acclimated to different levels of human interaction prior to breeding in order to assess the impact on conception rates.
Partners: Nielson Signature Beef
Funders: NSERC
Animal Identification using Artificial Intelligence Posted August 17, 2020

Using artificial intelligence for individual animal identification is a novel concept that Olds College is exploring with an industrial client. If successful, producers will be able to identify animals within their herds using images or videos collected from the ground or air, which could have applications to automated illness detection or animal traceability.
Funder: Industry.
Hyperlayer Data Concept Posted August 17, 2020

The hyperlayer data concept is a process that allows the Olds College Smart Farm to compile, analyse, and use virtually every type of agricultural data. It centers around compiling topographical data, hyperspectral imagery, moisture mapping, yield data, and other information to assist in machine learning for easy analysis and data extraction.
Funder: Internally Funded

Smart Ag Research

Smart Agriculture Research Goals

Smart Agriculture Projects

Olds College Smart Farm