What is CAAIN?
Canada urgently needs to bridge the gap between today’s (and tomorrow’s) emerging technologies and traditional resource-oriented industries. Perhaps nowhere is this so essential as in the agri-food sector, which faces one of our world’s most critical problems: as our global population continues to grow, the amount of food, land and water available becomes more constrained. Never has it been more essential to find new ways to produce “more with less.”
The only way forward is to increase the productivity and efficiency of agri-food companies by applying new technological solutions, including artificial intelligence, automation, blockchain and others. However, it has been difficult for agri-food producers to work directly with the researchers and technology companies to shape emerging technologies into real tools that can be applied to farming and food production, limiting the adoption of new techniques and technologies.
How We’re Solving it
The Canadian Agri-Food Automation and Intelligence Network (CAAIN) is a group of technology and agri-food companies, universities, colleges, and research institutions working together to create new technological solutions for Canada’s agricultural and food producers.
CAAIN brings together technology and agri-food companies focused on creating and integrating automated and digitized solutions in Canada’s agri-food sector. Our projects focus on using techniques in artificial intelligence, advanced sensor technologies, hyperspectral imaging, and blockchain applications to increase the productivity of Canadian agri-food producers. By working together, agri-food producers can help technology companies understand their unique needs and develop technological solutions to challenges within the agri-food sector. This will allow tech firms to create, validate, commercialize and scale new products for the global agri-market.
CAAIN projects will drive increased precision, productivity and premium for Canada’s agri-food market, enable technology companies to reach an important sector with significant growth opportunities around the world, create jobs in both sectors and drive economic growth in Canada.
Vineland Research & Innovation Centre
Cool Farm Alliance
Point Forward Solutions
Telus Trimble Ag
Weather Innovations Consulting
… and 38 others
CAAIN Project Areas
Smart farming is the latest farm management concept, using GPS, soil monitoring, data analysis and other technological tools to help farmers make the best possible decisions based on real conditions in the field. This data is often used to make decisions about crop and animal management, such as where to deploy pesticides. The data gathered through smart farming has other applications. Smart Farms are integral to the adoption of new technologies, enabling both companies and farmers to identify which processes would most benefit from a new approach, selecting the most promising solutions, and determining how successful those products are.
CAAIN is working to establish a network of Canadian smart farms that will help drive the development of new agri-food technologies.
Automation & Robotics
Labour shortages are a common problem in Canada’s agricultural sector, one that is exacerbated by the lack of automated production systems. There are currently few robotic solutions for labour-intensive farming sectors such as field crops, horticulture, livestock, and poultry and eggs. CAAIN members are developing robotic platforms suited to agricultural environments, research that will establish Canada as a global leader in agricultural automation an.
Data Integration & Analysis
The agri-food sector has yet to fully realize the transformative power of artificial intelligence. In the agricultural context, AI could assist farmers by finding problems and suggesting solutions For instance, predictive crop and pest models could help agricultural producers prevent outbreaks and reduce pesticide usage. However, researchers developing AI-enabled data analysis platforms generally don’t understand the agri-food sector well enough to develop solutions for it, while those in the agri-food sector don’t understand AI well enough to take advantage of its benefits. One of the major impediments to developing effective algorithms for deployment in data integration and analysis is the lack of easily accessible, high-quality data.
CAAIN members are undertaking several projects to create shareable data sets as well as the frameworks and digital architecture that enable the creation of new artifical intelligence and machine learning tools.