Developing context-aware green architecture for IoT-enabled embedded systems in smart public transportation

The proposed project will bring solutions for the efficient design of road-units that consist of multiple sensors deployed in remote stations detecting contextual data regarding traffic patterns, road conditions, weather, etc. As the major concern in establishing an outdoor sustainable embedded system is providing a reliable energy source, we aim at exploiting solar energy that offers a clean, and renewable source of power with a high rate of availability. The self-greening approach as a run-time solution would activate context-aware operation (channel conditions, applications, Quality of Service, data-rate requirements, and process variation) in such communication systems to optimize the energy consumption dynamically at each instance of time based upon the battery status feedback. Such smart IoT devices are aware of its operating conditions while adapting itself in real-time for optimal energy-efficiency and performance.

Intern: 
Ahmad Shahnejat Bushehri
Superviseur universitaire: 
Samira Keivanpour;Gabriela Nicolescu
Province: 
Quebec
Partner University: 
Discipline: