Contribution: Industrial Research Assistance Program – Contributions to Firms
Ansik Inc.
$75,000.00
Prediction of automotive system health from time series data using neural network models
FY 2020-21 · 2020-07-06
Summary
Pitstop’s mission is to obtain predictive maintenance insights from vehicle data and service data. Some drawbacks with machine learning approaches have been that data sets are not always complete. The simulation approach taken in this project will improve this situation and increase the benefit of a machine learning approach. In this project the plan is to train algorithms where there are common cases of service records that correlate to time-series sensor streams across different kinds of components (ex. engine and battery) and let the machine learning take care of small variations. This is an important step in our plan to apply neural network approaches to build proprietary predictions models on vehicle wear and failures.
Department
Program
Industrial Research Assistance Program – Contributions to FirmsIndustrial Research Assistance Program-Contributions to Firms (linked with high confidence)
Recipient
Location
Toronto|Toronto, Ontario, Canada
Recipient Type
For-profit organization
Business Number
844437632
Type
Contribution
Source
Proactive Disclosure - Grants and Contributions
Amendments
Each version of the agreement as published, oldest first, with its total as of that version. The amount above is the latest.
| Amendment | Date | Fiscal Year | Total |
|---|---|---|---|
| 0 | 2020-07-06 | 2020-21 | $75,000.00 |
| 1 | 2020-07-06 | 2020-21 | $75,000.00 |
As published
Additional Information
This agreement has been amended 1 time(s). The end date of this agreements has been modified by 84 days.
Additional Information (French)
Cet accord a été modifié 1 fois La date de fin du présent accord a été changé de 84 jours.
Agreement End Date
2021-04-02
Agreement Number
952153
Agreement Start Date
2020-07-06
Agreement Title
Prediction of automotive system health from time series data using neural network models
Agreement Title (French)
Prévision de la vigueur du système automobile à partir de données de séries chronologiques à l'aide de modèles de réseaux de neurones
Agreement Type
Contribution
Agreement Value
$75,000.00
Amendment Date
2021-02-10
Amendment Number
1
Coverage
IRAP Contributions to Firms projects stimulate wealth creation for Canada through technological innovation. | Les projets des Contributions aux entreprises stimulent la création de richesse au Canada grâce à l’innovation technologique.
Description
Pitstop’s mission is to obtain predictive maintenance insights from vehicle data and service data. Some drawbacks with machine learning approaches have been that data sets are not always complete. The simulation approach taken in this project will improve this situation and increase the benefit of a machine learning approach. In this project the plan is to train algorithms where there are common cases of service records that correlate to time-series sensor streams across different kinds of components (ex. engine and battery) and let the machine learning take care of small variations. This is an important step in our plan to apply neural network approaches to build proprietary predictions models on vehicle wear and failures.
Description (French)
La mission de Pitstop est d'obtenir des informations sur la maintenance prédictive à partir de données de véhicules et de données de service. Certains inconvénients des approches d'apprentissage machine sont que les ensembles de données ne sont pas toujours complets. L'approche de simulation adoptée dans ce projet permettra d'améliorer cette situation et d'accroître les avantages d'une approche basée sur l'apprentissage machine. Dans ce projet, il est prévu de former des algorithmes, dans lesquels il existe des cas courants d'enregistrements de services qui sont en corrélation avec des flux de capteurs de séries chronologiques sur différents types de composantes (par exemple, le moteur et la batterie), et de laisser l'apprentissage machine s'occuper des petites variations. C'est une étape importante de notre plan visant à appliquer des approches de réseaux de neurones pour construire des modèles de prévisions propriétaires sur l'usure et les pannes de véhicules.
Expected Results
The purpose of IRAP Contributions to Firms is to support research, development, adoption and/or adaptation of innovative or technology-driven new or improved products, services or processes in Canada up to their commercialization
Expected Results (French)
Le PARI, par le biais des Contributions aux entreprises, vise à appuyer la recherche, le développement, l’adaptation et/ou l’adoption au Canada de produits, de services ou de processus novateurs ou axés sur des technologies nouvelles ou améliorées, et ce jusqu’à leur commercialisation
Federal Riding
Spadina--Fort York
Federal Riding (French)
Spadina--Fort York
Federal Riding Number
35101
NAICS Code
541514
Organization Code
nrc-cnrc
Organization
National Research Council Canada | Conseil national de recherches Canada
Program Name
Industrial Research Assistance Program – Contributions to Firms
Program Name (French)
Programme d’aide à la recherche industrielle – Contributions aux entreprises
Program Purpose
The purpose of IRAP Contributions to Firms is to support research, development, adoption and/or adaptation of innovative or technology-driven new or improved products, services or processes in Canada up to their commercialization
Program Purpose (French)
Le PARI, par le biais des Contributions aux entreprises, vise à appuyer la recherche, le développement, l’adaptation et/ou l’adoption au Canada de produits, de services ou de processus novateurs ou axés sur des technologies nouvelles ou améliorées, et ce jusqu’à leur commercialisation
Recipient Business Number
844437632
Recipient City
Toronto|Toronto
Recipient Country
CA
Recipient Legal Name
Ansik Inc.
Recipient Operating Name
Pitstop
Recipient Postal Code
M5V 1S8
Recipient Province or Territory
ON
Recipient Type
F
Reference Number
172-2020-2021-Q1-952153
