AIMday
Digital Agriculture

1 October 2020

Manitoba, Canada

University of Manitoba

Challenges

E

  • EMILI Canada

    • Challenge number 3092

      Can intelligent technologies help ensure value chains can continue to function uninterrupted in the face of a future pandemic? (eg. transportation, market access, AI and supply chain)

      Asper, supply chain management and transportation; marketing department; F of Ag; Ag economics; head of ag economics; science or engineering

    • Challenge number 3095

      Can intelligent technologies help determine crop rotation options that best meet the needs of export markets affected by a pandemic? (eg. fast growing, high yield, high protein crops)

      .

  • Enns Brothers

    • Challenge number 3083

      How can we cost-effectively collect and utilize soil data to automate variable rate applications of nutrients, pesticides, etc.

      Develop a nutrient management platform to efficiently record soil data analysis (ex. Agvise results). There is a lot of manual entry after the soil sampling results are sent back from the lab, and in many cases there is a separate program to geo-reference those points. Once a nutrient prescription has been written (many times manually), its then sent to the equipment for variable rate application. If the initial activity needs to be changed, we are then manually changing which takes time and can lead to input error. I believe Trimble has an expensive platform. Seamless data and process flow, but also ability to record historical tests, all georeferenced with ability to write nutrient mgmt. prescriptions.

    • Challenge number 3086

      How can we cost-effectively and precisely measure rainfall in agricultural settings on 5 km grid

      Affordable weather station coverage.. Many suggest the perfect weather station coverage to accurately measure rainfall on a per field basis is on a 5 KM grid.. Running through these scenarios with todays solution is to costly for adoption.. We need an affordable weather stations solution with sub soil moisture probes and connectivity to support realtime educated field level production decisions. Could be for nutrient management, yield prediction, marketing decisions, logistical in-season management and historical reference. Rainfall is one of the most important metrics to gather as its very sporadic.

M

  • MacDon Industries

    • Challenge number 3089

      What technologies could determine the relative position of 2 objects in the horizontal plane, with ~5cm2 accuracy up to a range of 10m, without the use of GPS?

      We’re interested in what sensors could be used to know where an object is located relative to another.

      For example, say you have a robotic forklift that is operating inside of a warehouse, without a GPS signal. If you wanted it to retrieve a specific pallet from a row of pallets, how could you tag the pallet with a locator sensor, so that once the forklift got close, it knew where the pallet was (relative to the forklift) with a high degree of accuracy.

U

  • University of Manitoba

    • Challenge number 2996

      Privacy concerns around data gathering and storage (Cybersecurity)

      No additional information available.