Sensors for Agriculture

Various sensors can be found in today’s agricultural operations. This microcredential provides a summary of the range of IoT sensors, the technology required to utilize the sensors, and collection and storage of data. The ideal learner will be looking to adopt sustainable farming practices using data and already be employed in the farming industry, either as an employee or owner.  It is expected that the learner will have at least basic digital skills. The learners will complete the modules at their own pace. Therefore, this microcredential has been developed fully online.

Prior Learning

• Recommended, but not necessary, to complete IOT Agriculture Essentials before enrolling

Learning Outcomes

• Summarize the range of IoT sensors utilized in agricultural operations
• Discuss technology required to utilize IoT sensors
• Examine data collection and storage to utilize for further analysis

Assessment

• The learner must achieve a minimum score of 80% on each of the 3 quizzes.

Precision farming practices using the latest techniques and technologies address various aspects of carbon footprint and clean technologies. An understanding of how smart equipment can assist with the reduction of greenhouse gases, not only regarding fertilizer application but also pesticide use and seeding practices, is vital to:

• Canada’s Climate Action Plan
• Responsible consumption and production- Ensure sustainable consumption and production patterns.
• Advancing innovation – Agriculture

Innovative solutions, including clean technologies, are required to reduce emissions from agriculture. Promising new technologies are being developed to reduce emissions from livestock and crop production, including from the use of precision farming and “smart” fertilizers, which time the release to match plant needs, and from feed innovations that reduce methane production in cattle. Actions pertaining to the agriculture sector will be developed collaboratively through Canada’s Next Agriculture Policy Framework.

• Drones in Agriculture
• Equipment Data and Analytics
• Farming Using Smart Technology
• IOT AgriTech Essentials
• IOT Data and Storage
• Machine Learning and Agriculture
• What-If Questions and Data