This project focuses on adding new functionalities to the InfoBaignade and InfoBris tools in order to generalize water quality prediction for several uses and to evaluate drinking water consumption wi...
Cannforecast Software Inc.
9 enregistrements totalisant 571,800.00 $ CAN, selon les données ouvertes officielles du gouvernement du Canada.
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Par ministère
| Conseil national de recherches Canada | $571,800 | 9 enregistrements |
Enregistrements
The project aims to extend the capabilities of a predictive modeling tool, for optimized management of municipal infrastructures: drinking water, wastewater, roads, bridges and culverts. The main outc...
The project involves automating the InfoBris and InfoBaignade data pipeline to significantly reduce the amount of time spent on manual labour, which will increase CANN Forecast's margins and allow the...
A model based on machine learning, able to predict the breakage of aqueducts more reliably has been developed. The project is transforming this model into a turnkey solution, by integrating data from...
The objective of this pilot project is to adapt the InfoBaignade tool to provide a water quality forecast for drinking water treatment. This tool allows the identification of events where water qualit...
Modeling the impact of flooding on buildings in urban areas under various climate change scenarios.
The objective is to use AI to predict in real time the quality of water to identify and anticipate the events when it is degraded to optimize the treatment of drinking water.
Development of a software architecture that will allow for real time implementation of artificial intelligence algorithms: InfoBaignade and InfoBris; two decision making models that are currently bein...
Given the success of a first exploratory engagement with the City of Montreal for the prediction of aqueduct breakage, this project aims to adapt the most recent machine learning algorithms in order t...