WATER MANAGEMENT DONE SMARTLY

Founded by the winners of the 2016 Aquahacking Challenge in Montreal,  CANN Forecast ’s mission is to help prevent water-related crises by leveraging municipalities’ existing data . Nicolas St. Gelais, Co-founder and Scientific Director, has always had an interest in understanding water issues and exploring how technology can help us better manage it.

“Back in 2005, and even more importantly today, communities were asking to get back access to the rivers and water bodies neighbouring Montreal. Not knowing whether water bodies were safe or healthy for recreational activities created a challenge. During the 5-month hackathon, our team created a machine learning model that accurately predicts water quality in real time,” says Nicolas.

CANN Forecast

Their model, fueled by artificial intelligence (AI), proved that their technology was giving clearer results compared to traditional water quality measurement methods. Not only was it clearer, but the information was available in real time — a crucial factor in understanding the state of our waters. In October 2016, their InteliSwim technology won first place in the Aquahacking Challenge, and shortly after, CANN Forecast signed their first consulting contract with the Wastewater Treatment Division of the City of Montreal.

The team is also one of the winners of the Generation Water Tech Challenge, WWF-Canada’s first-ever tech challenge looking for bold solutions that address Canada’s freshwater health. A total of $75,000 was granted to the Generation Water Tech Challenge award recipient, in addition to a spot in CSI’s Climate Ventures’ Earth Tech accelerator.

Protecting swimmers in real time

One of the ways that CANN Forecast is addressing water quality is through their InteliSwim technology. It’s summertime and people are dying to cool off at nearby beaches, but there’s always that concern about how clean or healthy the water is — and that’s where InteliSwim can help.

“Our model uses municipalities’ historical data to learn the complex relationships between the different variables affecting water quality in urban environments. Once the model is adapted to nearby city beaches,   can determine in real time if the concentration of  E. coli  in the water is higher than the acceptable standard for swimming,” says Nicolas.

The great thing about this model is that it is 90% more accurate than traditional methods. “Our present tool enables the safe use of water in real time. With traditional methods, contamination would be discovered after peaks, putting people at a higher risk.”

Urban water bodies are used for many activities including kayaking and surfing, so InteliSwim can address other issues in addition to protecting swimmers. The long-term objective for CANN Forecast is to provide real-time water quality information for multiple zones across water bodies, so that users can make a more informed decision, as we routinely do for weather forecasts.

Self-training tools for pipe vulnerability

CANN Forecast has also created a system that can identify vulnerable pipes, reduce water loss, and provide potential cost savings when it comes to pipe rehabilitation. InteliPipes is an AI-based algorithm that helps municipalities identify risky pipes before they break, by “self-training” with historical network data.

“Every day, approximately 850 water mains break in North America, costing over $3 billion per year to repair. If we can identify pipes before they fail, we can increase water health and save money. Each unexpected pipe failure comes with a high economic and environmental impact.”

Protecting ecosystems for future generations

Poor water quality and infrastructure management have a direct impact on people’s health and the environment. That’s why Nicolas and the CANN Forecast team are committed to addressing these challenges with innovative technology to support municipalities in their strategic decision-making. “The long-term goal is to protect ecosystems for communities and future generations. Technology is a powerful tool and it can really help us understand how our actions are affecting ecosystems, and bring viable solutions,” says Nicolas.

So far, CANN Forecast has done pilot projects with more than 10 innovative municipalities of all sizes across eastern Canada. CANN Forecast also won prestigious innovation awards like the Fast Forward Challenge from Canada Economic Development.

Beyond scaling, CANN Forecast is hoping to facilitate the smart management of water across Canada. They’re continuing to develop tools that can enable decisions to be based on the best available science and information.  To achieve this, their secret ingredient is a team with diverse backgrounds: from physics to statistics.

Alex Del CastelloSeptember 15, 2020

SOURCE WWF

Taxonomy

• Data & Analysis
• AI