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Smart Buildings

A smart building is a building integrated with IoT devices to capture data about humans, the building heating, ventilation, air conditioning (HVAC), movement and vehicles. There are significant opportunities to create new approaches for the assessment of building health as well as supporting the health and wellness of the humans within the building. Our research thematic areas for smart buildings include:

Edge Computing and Big Data for Data Management in Smart Climatic Buildings

The ACE Facility located at Ontario Tech University is a university owned and operated 16,300 square metre research and development multi-chamber environmental testing facility. ACE provides large controlled climatic spaces that are distinctly unique to Canada and internationally. This research is creating a robust data management process to capture all the data generated within any environmental based testing simulations occurring within the ACE Facility climatic building, and allow seamless distribution to other processes for further analytics and machine learning modelling while preserving the privacy of data.

Privacy Preserving Big Data Management in Smart Buildings

The ability to effectively interpret the data flowing from a building can allow anticipation of user needs while increasing efficiency and potentially reduce costs. However, there is a risk that external companies could access this sensitive data about a community or place leading to infringements of people’s privacy.

This research is focused on the creation of data management approaches for smart buildings with an intense focus on privacy preservation before data is published for other external agents to consume.

Privacy Preserving Big Data Management for Smart Cities

Connecting city infrastructure such as multiple smart buildings, smart homes, as well as other environmental sensors and IoT devices brings the ideation of a smart city. Similarly to the need to preserve privacy in smart building analytics, concerns over privacy are a key impediment for community support for data collection within a smart city. In this work we have proposed a wholistic smart city framework that can effectively capture and manage the vast data from a city’s many infrastructures as well as its population, and seamlessly integrate and analyse that data to aid in making informed decisions on the provision of city services while maintaining security, health and privacy of the city as whole.









  • Refereed Conference Papers
    1. Inibhunu, C., McGregor, C., 2021, “Privacy Preserving Framework for Big Data Management in Smart Buildings”, IEEE PERCOM Workshop on Security, Privacy, and Trust in the Internet of Things (SPT-IoT), Kassal, Germany, in press
    2. Inibhunu, C., McGregor, C., 2020, “Edge Computing with Big Data Cloud Architecture: A Case Study in Smart Building”, 2020 IEEE International Conference on Big Data: Workshop on IoT based Big Data Architectures and Applications, virtual, in press
    3. Inibhunu, C., McGregor, C., 2020, “'A Privacy Preserving Framework for Smart Cities Utilising IoT, Smart Buildings and Big Data”, 18th IEEE International Conference on Smart City, Virtual, Dec, in press
    4. Jalali, R., El-Khatib, K., McGregor, C., (2015), “Smart City Architecture for Community Level Services Through the Internet of Things”, 18th International Conference on Intelligence in Next Generation Networks, Paris, pp 108-13