Grant: Engage Grants Program
University of Ontario Institute of Technology
$25,000.00
A vehicular sensing platform for smart cities
EF 2016-17
Résumé
The data collected from the vehicle detection systems provides insight which is quite valuable in relievingtraffic congestion, detecting types of vehicles passing through an intersection and statistically demonstratingthe detailed traffic flow of vehicles in important intersections.The most common solutions today employ inductive detector loops, which are buried in the road pavement.Theses detectors can sense the presence of traffic at a traffic light, and adjust traffic light intervals accordinglyin order to optimize traffic flow. One drawback of existing sensor loops is the inability to identify a vehicle,which limits their application. By identifying a vehicle and using multiple sensor at intersections, the systemcan also be used to estimate traffic flow and pattern. In addition, detector loops are prone to damage by snowplow trucks. The use of a small sensor node the size of a hockey puck requires less installation hours. It alsolowers maintenance costs: a low power design allows for longer maintenance window intervals.Due to the low power nature of the design, the sensor motes require efficient routing algorithms tocommunicate with a central gateway. The classification algorithms and data storage occurs in a gateway whichacts as a broker between the sensor motes and the cloud.The main objective of this research project is to implement a vehicular detection platform and the underlyingrouting algorithms and software management platforms. The hardware for this project will be implementedwith the help of NorthLine Canada. The research work will include designing the embedded firmware for thesensor motes, implementing the routing algorithms to send data to a common hub and designing the softwaremanagement system on the gateway responsible for data analytics and presentation. Implementation of amobile app will be considered as well (time permitting). Thus, the main research avenues this project willinvestigate are the implementation of a vehicle detection algorithm using wireless motes together with thegateway routing algorithms.
Programme
Engage Grants Program
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
507544-2016
Name nom
Pazzi, Richard
Department département
Business and Information Technology, Faculty of
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2016
Competition year année de concours
2016
Award amount
25000
Program id
EGP
Program name en
Engage Grants Program
Program name fr
Programme de subventions d'engagement partenariat
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1553
Committee name en
Ontario Internal Decision Committee
Committee name fr
Comité de décision interne pour l'Ontario
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2718
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Communication and information theory
Research subject fr
Théorie des télécommunications et de l'information
Partie
1
Nb partie
1
Application title
A vehicular sensing platform for smart cities
Keyword
NSERC
Application summary
The data collected from the vehicle detection systems provides insight which is quite valuable in relievingtraffic congestion, detecting types of vehicles passing through an intersection and statistically demonstratingthe detailed traffic flow of vehicles in important intersections.The most common solutions today employ inductive detector loops, which are buried in the road pavement.Theses detectors can sense the presence of traffic at a traffic light, and adjust traffic light intervals accordinglyin order to optimize traffic flow. One drawback of existing sensor loops is the inability to identify a vehicle,which limits their application. By identifying a vehicle and using multiple sensor at intersections, the systemcan also be used to estimate traffic flow and pattern. In addition, detector loops are prone to damage by snowplow trucks. The use of a small sensor node the size of a hockey puck requires less installation hours. It alsolowers maintenance costs: a low power design allows for longer maintenance window intervals.Due to the low power nature of the design, the sensor motes require efficient routing algorithms tocommunicate with a central gateway. The classification algorithms and data storage occurs in a gateway whichacts as a broker between the sensor motes and the cloud.The main objective of this research project is to implement a vehicular detection platform and the underlyingrouting algorithms and software management platforms. The hardware for this project will be implementedwith the help of NorthLine Canada. The research work will include designing the embedded firmware for thesensor motes, implementing the routing algorithms to send data to a common hub and designing the softwaremanagement system on the gateway responsible for data analytics and presentation. Implementation of amobile app will be considered as well (time permitting). Thus, the main research avenues this project willinvestigate are the implementation of a vehicle detection algorithm using wireless motes together with thegateway routing algorithms.
