Lina Stankovic

Senior Lecturer

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 & Capabilities

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

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

Academic / Professional qualifications

  • Senior Member of the IEEE
  • EPSRC Peer Review college Member
  • Editor for the Elsevier International Journal of Electronics and Communications
  • Proposal reviewer for EPSRC, EU European Research Council, Belgian Research Foundation Flanders
Lina Stankovic

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