Reference number : GC-2017-Q4-00608, amendment number : , agreement type : G, recipient legal name : Fraser, Andrew (Conestoga College Institute of Technology and Advanced Learning), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Engage Grants for colleges, program name french : Subventions d'engagement partenarial pour les collèges, program purpose english : Alkaline batteries in all shapes and sizes are used in many applications and comprise 78% of all batteries sold_x000D_
into the Canadian market every year. Alkaline (non-rechargeable) and Lithium-Ion (rechargeable) batteries_x000D_
contain Zinc and rare Earth metals such as Lithium, Cadmium, and Nickel. If these batteries are recycled_x000D_
responsibly, they will provide new sources for fertilizing agricultural fields, save energy and resources, protect_x000D_
the environment, and divert waste from landfills._x000D_
However, considering the volume and variety of waste batteries, automated systems require the ability to sort_x000D_
by chemistry in order to ensure proper recycling. Sorting results in better control over environmental outcomes_x000D_
as separated battery types can be processed by the best specialty recyclers using technology designed for_x000D_
recycling of specific battery chemistries._x000D_
In this feasibility study project, we will investigate different ways to employ new technologies for improving_x000D_
the efficiency and productivity of household batteries recycling. The core of our study will be to develop a_x000D_
reliable method for identifying different types of used button cell batteries using machine vision and Artificial_x000D_
Neural Networks (ANNs)., program purpose french : Alkaline batteries in all shapes and sizes are used in many applications and comprise 78% of all batteries sold_x000D_
into the Canadian market every year. Alkaline (non-rechargeable) and Lithium-Ion (rechargeable) batteries_x000D_
contain Zinc and rare Earth metals such as Lithium, Cadmium, and Nickel. If these batteries are recycled_x000D_
responsibly, they will provide new sources for fertilizing agricultural fields, save energy and resources, protect_x000D_
the environment, and divert waste from landfills._x000D_
However, considering the volume and variety of waste batteries, automated systems require the ability to sort_x000D_
by chemistry in order to ensure proper recycling. Sorting results in better control over environmental outcomes_x000D_
as separated battery types can be processed by the best specialty recyclers using technology designed for_x000D_
recycling of specific battery chemistries._x000D_
In this feasibility study project, we will investigate different ways to employ new technologies for improving_x000D_
the efficiency and productivity of household batteries recycling. The core of our study will be to develop a_x000D_
reliable method for identifying different types of used button cell batteries using machine vision and Artificial_x000D_
Neural Networks (ANNs)., agreement title english : Development of an artificial neural network for identification of used button cell batteries, agreement title french : Development of an artificial neural network for identification of used button cell batteries, agreement number : CARD1, agreement value : 25000.0, agreement start date : 2018-01-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada