OpenAgSense at the i3A Innovation Showcase: Trusted AI & Open Data Infrastructure for Canadian Agriculture

On March 4, 2026, the Innovation, Automation, and AI Acceleration (i3A) program—an initiative of Agriculture and Agri-Food Canada (AAFC) under its Information Systems Branch and Transformation and Modernization Services—held an Innovation Showcase highlighting research that applies AI, sensing technologies, and data-driven approaches to agriculture. The event demonstrated how digital technologies can support more efficient, sustainable, and resilient farming systems across Canada.

Our lab participated through the OpenAgSense project, presenting a vision for a trusted, cloud-native, and interoperable agricultural data infrastructure.

The i3A Showcase in Brief

The showcase featured work from multiple institutions. Patrick Hennessy (Dalhousie University) presented AI-based selective herbicide spraying in wild blueberry fields using computer vision to reduce chemical use. Shangpeng Sun discussed AI and robotics for smart agriculture and data-driven decision-making. Hayda Almeida (WELL-E Team, UQAM) introduced an AI-powered Digital Living Lab for monitoring animal welfare in dairy farms via cameras, movement tracking, and behavioral indicators. Lewis Lukens (University of Guelph) and Caleb Niemeyer (Woodrow Limited) presented machine learning for matching crop genetics to farm environments using soil, elevation, and management data. Vinicius Camargo (University of Calgary) shared work on AI and wearable sensors for precision monitoring of beef cattle health.

Across these projects, a common theme emerged: AI, IoT sensing, robotics, and open data platforms are shaping the future of digital agriculture and supporting more climate-informed farming.

Our Contribution: OpenAgSense

Our contribution, OpenAgSense, was presented as a single project with two research components:

1. AI-based integration of multi-source environmental data for drought prediction in Alberta, combining satellite observations, weather stations, and IoT sensors into regionally tuned models.

2. A multi-agent crowdsourcing platform for smart agriculture, enabling farmer-controlled data sharing and integration of sensor data, satellite information, and farmer observations using open standards and FAIR data principles.

The core idea is that Canada needs trusted agricultural AI infrastructure—not fragmented tools: a shared, open data ecosystem that integrates sensors, satellites, and farmer knowledge into AI-ready intelligence for drought monitoring, emission tracking, and climate-resilient decision-making.

For technical details, architecture, and how OpenAgSense is designed around farmer trust, open standards, and multi-agent systems, see our OpenAgSense: Trusted AI & Open Data Infrastructure for Canadian Agriculture project page.