Dr Lina Stankovic

Senior Lecturer

Electronic and Electrical Engineering

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.

Expertise

Has expertise in:

Intelligent monitoring and analytics, as applied to:

Energy and environment in smart buildings, e.g., disaggregation, activity recognition, appliace retrofit
Motion capture and person-centric kinematrics analysis using portable depth and infrared camera systems
Wireless sensor network solutions for civil infrastructure, such as predicting failure in earthworks (embankments and cuttings) and bridge/scour monitoring
Water consumption, treatment and infrastructure monitoring

Prizes and awards

Finalist of the World first 10K Best paper Award (Top 3%): Recipient; 12/7/2017
Paper awarded top 5% by reviewers in Eusipco-2010 conference and invited for journal publication.: Recipient; 8/2010

more prizes and awards

Publications

Network coding hard and soft decision behavior over the physical layer using PUMTC: Attar Hani, Alhihi Mohamad, Zhao Bochao, Stankovic Lina; 4th IEEE International Conference on Advances in Computing and Communication Engineering , (2018)
Optimal detection and error exponents for hidden semi-Markov models: Bajović Dragana, He Kanghang, Stanković Lina, Vukobratović Dejan, Stanković Vladimir; IEEE Journal on Selected Topics in Signal Processing, (2018)
Shift-enabled graphs : graphs where shift-invariant filters are representable as polynomials of shift operations: Chen Liyan, Cheng Samuel, Stankovic Vladimir, Stankovic Lina; IEEE Signal Processing Letters, pp. 1-5, (2018)
Non-intrusive load disaggregation using graph signal processing: He Kanghang, Stankovic Lina, Liao Jing, Stankovic Vladimir; IEEE Transactions on Smart Grid Vol 9, pp. 1739-1747, (2018); http://dx.doi.org/10.1109/TSG.2016.2598872
Appliance electrical consumption modelling at scale using smart meter data: Murray D.M., Stankovic L., Stankovic V., Espinoza-Orias N.D.; Journal of Cleaner Production, (2018); http://dx.doi.org/10.1016/j.jclepro.2018.03.163
Post-processing for event-based non-intrusive load monitoring: He Kanghang, Jakovetic Dusan, Stankovic Vladimir, Stankovic Lina; 4th International Workshop on Non-Intrusive Load Monitoring, pp. 1-4, (2018)

more publications

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); 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); 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); 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

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