Personal statement
My ongoing research efforts focus on tuning analytical expertise for intelligent sensor data acquisition and analytics of smart buildings energy usage, understanding appliance behaviour through energy disaggregation, understanding energy demand through activities, motion analysis for tele-rehabilitation via depth and infrared sensors, through the use of sensor network data acquisition, communications and various modelling and inference tools.
Better understanding of appliances in a building, when they are used, and how much electricity they use, would help to overcome some of the challenges in managing households energy demand. Using smart meter data obtained through real household trials, via disaggregation, we focus our research efforts on enhanced appliance retrofit/upgrade decisions, demand prediction from appliances within households, opportunities for load shifting and improved understanding of households' daily routines.
With increasing importance given to telerehabilitation where the focus is clinical assessment of a patient’s functional abilities in his or her own environment, there is a growing need for accurate, low-cost, and portable motion capture systems that do not require specialist assessment venues. Current state-of-the-art optical clinical assessment equipment for rehabilitation requires multiple cameras for 3D image capture. Research efforts focus on motion capture using only a single camera sensor, with infrared and depth data, which is portable and cost effective compared to most industry-standard optical systems, without compromising on accuracy. Motion patterns of interest are determined from infrared and depth data, obtained in clinical trials, through depth recovery methods that map object coordinates into camera space.
Research interests
- Graphical-based inference
- Graphical modelling of variables with probabilistic relationships
- Model-fitting/system characterisation
- Predicting energy demand at appliance level
- Sensor deployment and data acquisition
Professional activities
- Carnegie Trust for the Universities of Scotland (External organisation)
- Advisor
- 2/2018
- IEEE Transactions on Signal and Information Processing over Networks (Journal)
- Editorial board member
- 2018
- 4th International Workshop on Non-Intrusive Load Monitoring (Event)
- Advisor
- 1/2018
- IEEE 2017 Workshop on Multimedia Signal Processing
- Member of programme committee
- 16/10/2017
- 21st century standards and labelling programmes
- Invited speaker
- 16/12/2015
- Domestic Energy Feedback Research focusing on Functionality and Uses of Smart Metering
- Contributor
- 3/2/2015
more professional activities
Projects
- EPSRC Global Challenges Research Fund Institutional Sponsorship Award 2017 (GCRF) / R171051-102
- Stankovic, Vladimir (Principal Investigator) Stankovic, Lina (Co-investigator)
- Period 01-Jul-2017 - 31-Mar-2018
- Impact Acceleration Account - University Of Strathclyde 2012 / R120526-212
- Stankovic, Lina (Principal Investigator)
- Period 01-Oct-2012 - 31-Mar-2017
- Eco-Bot: Personalised ICT-tools for the Active Engagement of Consumers Towards Sustainable Energy
- Stankovic, Lina (Principal Investigator) Stankovic, Vladimir (Co-investigator)
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- Period 01-Oct-2017 - 31-Dec-2020
- SENSors and Intelligence in BuiLt Environment (SENSIBLE) MSCA RISE
- Stankovic, Lina (Principal Investigator) Glesk, Ivan (Co-investigator) Gleskova, Helena (Co-investigator) Stankovic, Vladimir (Co-investigator)
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- Period 01-Jan-2017 - 31-Dec-2020
- EPSRC DOCTORAL TRAINING GRANT | Elafoudi, Georgia
- Stankovic, Lina (Principal Investigator) Galloway, Stuart (Co-investigator) Elafoudi, Georgia (Research Co-investigator)
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- Period 01-Nov-2011 - 01-Sep-2015
- Smart Building Energy Management System (BEMS)
- Stankovic, Lina (Principal Investigator)
- Market study and prototyping of data analytical tools that could be beneficial to utilities for improving their customer experience
- Period 01-Jun-2013 - 30-Sep-2015
more projects
Address
Electronic and Electrical Engineering
Royal College Building
Royal College Building
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