Transforming food production and distribution with intelligent technology
Smart Food Systems: AI for a Sustainable Agri-Food Sector
Presented by
Sponsored by
Open Innovation Partner
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This challenge is tied to the united nations’ sustainable development goals:
Background
Canada’s agri-food sector is a cornerstone of the national economy and cultural heritage, yet it faces pressing challenges. Food loss and waste costs billions annually, supply chains often lack transparency and resilience, and communities may struggle to access affordable, nutritious, and locally sourced foods.
Key Issues:
- Inefficiencies in matching supply with demand, leading to waste, spoilage, and lost revenue.
- Limited transparency and traceability in supply chains, reducing consumer trust and producer competitiveness.
- Uneven access to high-quality, local, and culturally relevant foods, affecting nutrition and community wellbeing.
Challenge as part of Cooperathon 2025
How can we leverage AI, data analytics, and innovative value chain models to optimize Canada’s food supply chains—reducing waste, strengthening local sourcing, and ensuring equitable access to nutritious foods?
Goals
Desired outcomes:
- Demand Forecasting & Inventory Management: AI-driven tools to anticipate consumer demand, reduce surplus, and minimize waste.
- Traceability & Transparency: Data platforms (potentially leveraging blockchain or IoT) that allow consumers to trace products from farm to fork, building trust and supporting local producers.
- Nutritional & Cultural Relevance: Recommendations and solutions that help consumers identify nutritious, locally sourced, and culturally appropriate foods, enhancing community health and satisfaction.
Stakeholders & Target Audiences
- Producers (Farmers, Co-ops) & Distributors: Seeking tools to forecast demand, reduce waste, and increase market access.
- Retailers, Restaurants, & Food Programs: Interested in inventory optimization, sustainable sourcing, and improved supply chain visibility.
- Agri-Tech Startups, Researchers, & Innovators: Looking to develop AI-driven solutions that reshape the Canadian agri-food landscape.
Scope & Constraints
- Geographic Focus: Canadian agricultural regions, distribution networks, and urban/rural markets.
- Solution Stage: Early-stage concepts through proof-of-concept prototypes demonstrating feasibility and readiness for pilot testing.
- Considerations:
- Seasonal and regional variations in production.
- Compliance with food safety, labeling, and regulatory standards.
- Ethical data use and sensitivity to diverse dietary/cultural needs.
Prize(s)
- 1st Prize: $5,000 (minimum)
Solution scope
- Waste Reduction: Measurable decrease in food loss and waste within a given supply chain segment.
- Improved Local Sourcing: Increased availability and visibility of local and sustainable products in retail channels.
- Stakeholder Validation: Interest from producers, distributors, or community food organizations, and a pilot-ready plan for deployment.
Confidentiality
All details relating to technologies, innovations or methods submitted to Cooperathon will remain strictly confidential, unless otherwise indicated.