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http://www.concordia.ca/content/shared/en/news/stories/2019/04/09/Concordia-phd-candidate-milad-ashouri-is-building-an-app-to-monitor-and-improve-home-energy-use.html

PhD candidate Milad Ashouri is building an app to monitor and improve home energy use

The Concordian's research tracks problem areas to help occupants find greener solutions
April 9, 2019
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Milad Ashouri: “Not everyone is aware of how much energy is wasted by home appliances.”

Environment and Climate Change Canada announced April 1 that the country is warming at twice the global rate, warning that human behaviour must change to slow the trend.

Milad Ashouri, a PhD student in Concordia’s Department of Building, Civil and Environmental Engineering, is working on a way to enhance our energy-conscious behaviour.

Together with his research team, the Energy and Environment Group, Ashouri is using data-mining frameworks that track building occupants’ energy consumption in order to identify problem areas and recommend improvements.

Employing data belonging to a set of Japanese buildings, he is developing an app that will generate a residential energy use profile as well as potential areas for savings, from heating to lighting to plug loads.

These cutting-edge technologies are going to change the future of buildings

How does this specific image (top right) relate to your research at Concordia?

Milad Ashouri: The image depicts the main idea of our research team at Concordia. Nowadays enormous amounts of data are monitored and collected by building energy management systems (BEMS), but useful/straightforward information is not readily provided to occupants or energy managers through analysis of that collected data.

As such, our research team focuses on developing data-mining frameworks with these goals:

  • To give customized feedback and recommendations on improving the energy consumption profile of the occupants (as shown in the figure)
  • To explore the correlations between occupancy and building energy use
  • To find the instances of energy wastage and subsequent potential for energy savings
  • To detect and diagnose faults in building heating and cooling systems

What is the hoped-for result of your project? And what impact could you see it having on people’s lives?

MA: Since the building sector is a major consumer of primary energy, the main focus of this project is to appreciably reduce the total energy consumption in buildings by exploring unseen energy savings and giving occupants useful feedback in the form of a mobile application.

The outcome of our research is to make the occupants aware of their best energy consumption profile through an analysis of their energy usage, which will motivate them to achieve the targeted energy consumption or even improve their behaviour to achieve better results.

Doing so will benefit both energy consumers and suppliers. This will also make buildings more efficient as well as cost effective.

The findings of my research have to be first integrated with the existing BEMS, which we are currently working on. Once this is done, the app that gives useful and straightforward feedback to the occupants about their energy performance will be developed and integrated with the BEMS.

What are some of the major challenges you face in your research?

MA: One major challenge in this field of research is developing a general methodology — irrespective of the building type, location, etc. — that provides useful insights to the occupants about their energy consumption patterns and suggests viable recommendations from the massive data collected from BEMS.

We have developed a methodology that can be applied to most buildings irrespective of their geographical location.

Sometimes the identified recommendations may save a lot of energy. However, they might interfere with occupants’ comfort, and the occupants may therefore be reluctant to apply them.

Suggesting recommendations that balance both occupants’ comfort and energy savings is a challenge.

The other issue comes from the quantity and quality of the data available. If we had more detailed data — for example, questionnaires about the preferences of occupants — it would be possible to provide more specific and customized feedback.

What are some of the key areas where your work could be applied?

MA: In general, the developed framework can be applied to both commercial and residential buildings. Specifically, this research work can be incorporated into BEMS — building automation and control systems to extract, analyze the patterns of building energy use and provide useful recommendations to building occupants and energy managers.

The data mined in this study was the outcome of a collaborative research project between Concordia and Tohoku University, with the sponsorship of the International Energy Agency.

Detailed data was collected through sub-monitoring of every type of energy use from 80 residential buildings.

What person, experience or moment in time first inspired you to study this subject and get involved in the field?

MA: The first ever study on using end-use load data to analyze the impact of occupant behaviour on building energy consumption was conducted by our research group. This kind of research is new and has many opportunities in the building sector.

This fact motivated me to pursue my research in the application of data mining in exploring energy savings opportunities in buildings.

In addition, not everyone is aware of how much energy is wasted by not being cautious about the use of home appliances. Quantifying the energy wastage and savings will demonstrate the real impact of occupant behaviour in building energy use.

That’s when I came up with the idea to find the correlations between home appliances and energy use to actually use these to monitor the occupants’ behaviour.

How can interested STEM students get involved in this line of research? What advice would you give them?

MA: Implementation of BEMS in modern buildings is a fast-growing field these days with lots of research opportunities, such as improving occupant behaviour, load forecasting, increasing the share of renewables in buildings, etc.

I would suggest interested students get involved in applying novel data-mining methods along with artificial intelligence to improve building operation systems such as HVAC and occupant behaviour.

I am sure these are the cutting-edge technologies that are going to change the future of buildings.

What do you like best about being at Concordia?

MA: Concordia provides a friendly and supportive environment for researchers to work independently. I was part of a research team and whenever I faced a problem in my work, I was able to ask my colleagues and get help.

In addition, easy access to relevant courses in my field helped me to gain the required knowledge needed to do my research.

Are there any partners, agencies or other funding/support attached to your research?

MA: I would like to thank my supervisor, Fariborz Haghighat (professor of building, civil, and environmental engineering) for providing financial support through his Concordia Research Chair – Energy and Environment, and extend my thanks to him and Benjamin Fung (Canada Research Chair in Data Mining for Cybersecurity at McGill University) for their valuable advice.


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