Admissions
Collaboration

National and International Research Collaborations

The Department of Electrical and Electronic Engineering has a strong research environment. Its own postgraduate program offers research based degrees/diplomas such as PGDip, MSc.Eng, MPhil and PhD. The department receives funds from various research grants through the university and government and also through collaborations that the department has with the industry and foreign universities and other institutes. Below, you will find a collection of ongoing and recent research collaborative projects of our members.

PROJECT: AI and Signal Processing for the Smart Grid and Renewable Energy Integration

DEEE Members: Prof. Janaka Ekanayake, Prof. G.M.R.I. Godaliyadda, Prof. M.P.B. Ekanayake.
This research project was funded by two consecutive grants from the National Science Foundation of Sri Lanka. Lanka Transformers and LTL holdings also supported this work with resources and support. There was a PhD student that graduated from a subproject in this thrust area.

Overview

 

SmartGrid

 

Project Summary

Development of Novel Signal Processing algorithms for Non-Intrusive Load monitoring under voltage fluctuations, solar power influx while incorporating usage patterns to improve performance. (Usage modes can also be identified)
Demonstratable End-to-end hardware solution for NILM for developed – Tested with real household data.
Sky image-based forecasting system was developed for micro-level solar irradiance prediction.
Impact of Solar PV integration on LV networks was analyzed and state estimation algorithms for LV networks with high PV penetration was developed
Development of a coordinated PV rephasing algorithm based on swarm optimization for maximization of renewable energy integration capability
Sensitivity matrix-based solution coupled with a search space reduction mechanism was proposed to reduce run-time significantly compared to load flow simulations to enable near real-time PQ control to mitigate voltage violations due to PV integration.

 

KEY PUBLICATIONS

⮚ W. G. Chaminda Bandara, G. M. R. I. Godaliyadda, M. P. B. Ekanayake, J. B. Ekanayake, “Coordinated photovoltaic re-phasing: A novel method to maximize the renewable energy integration in low voltage networks by mitigating network unbalances”, Applied Energy, Vol. 280, 15 December 2020, 116022. (SCIE Indexed Journal with Impact Factor 9.8)

⮚ Shirantha Welikala, Neelanga Thelasingha, Muhammed Akram, Parakrama B. Ekanayake, Roshan I. Godaliyadda and Janaka B. Ekanayake, “Implementation of a robust real-time non-intrusive load monitoring solution”, Applied Energy, Vol. 238, pp. 1519-1529, March 2019. (SCIE Indexed Journal with Impact Factor 9.8)

⮚ Chinthaka Dinesh, Shirantha Welikala, Yasitha Liyanage, Mervyn Parakrama B. Ekanayake, Roshan Indika Godaliyadda and Janaka Ekanayake, “Non-intrusive load monitoring under residential solar power influx”, Applied Energy, Vol. 205, pp. 1068-1080, November 2017. (SCIE Indexed Journal with Impact Factor 9.8)

⮚ Shirantha Welikala, Chinthaka Dinesh, Mervyn Parakrama B. Ekanayake, Roshan Indika Godaliyadda and Janaka Ekanayake, “Incorporating Appliance Usage Patterns for Non-Intrusive Load Monitoring and Load Forecasting”, IEEE Transactions on Smart Grid, Vol. 10, No. 1, pp. 448-461, January 2019. (SCIE Indexed Journal with Impact Factor 8.9)

⮚ H. G. C. P. Dinesh, D. B. W. Nettasinghe, G. M. R. I. Godaliyadda, M. P. B. Ekanayake, J. V. Wijayakulasooriya, J.B.Ekanayake, “ Residential Appliance Identification based on Spectral Information of Low Frequency Smart Meter Measurements”, IEEE Trans. Smart Grid, vol. 7, no. 6, pp. 2781-2792, Nov. 2016. (SCIE Indexed Journal with Impact Factor 8.9)
 

 
 

PROJECT: AI for COVID

DEEE Members: Prof. Janaka Ekanayake, Prof. Vijitha Herath, Prof. G.M.R.I. Godaliyadda, Prof. M.P.B. Ekanayake.
This research is primarily funded by International Development Research Centre (IDRC), Canada.

Overview

 

AI4COVID

 

Project Summary

Development of AI based forecasting models for COVID-19 and similar pandemics (Dengue included).
Machine vision based contagious decease propagation risk assessment in urban areas using remote sensing.
Analysis of the influence of population dynamics (pop pyramid) on the severity level of the pandemic.
Design and Development of a human behavior emulator for COVID and other pandemic threat assessment to enable optimal spread control while mitigating socioeconomic impact of containment measures and the pandemic.
Utilization of AI and Data analytics to analyze and interpret online and household data collected which studies the educational, economical, occupational, sociopolitical, mobility and psychological impact of the pandemic.

 

COLLABORATORS

Department of Community Medicine – Prof. Samath Dharmaratne

Department of Sociology – Prof. Mallika Pinnawala

Department of Education – Prof. Sakunthala Yatigammana

Institute of Policy Studies, Sri Lanka

Ministry of Health, Sri Lanka

University Tenaga Nasional, Malaysia (Manipal and Multimedia University Collaborators)

McGill University, Canada

 

KEY PUBLICATIONS

⮚ Gihan Jayatilaka, Jameel Hassan, Suren Sritharan, Janith Bandara Senanayaka, Harshana Weligampola, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath, Janaka Ekanayake, and Samath Dharmaratne. 2022. "Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations" Applied Sciences Vol. 12, no. 17: 8428, August 2022.

⮚ G.A. Ilangarathna, Y. Ranasinghe, H. Weligampola, E. Attygalla, J. Ekanayake, S. Yatigammana, M. Pinnawala, R. Godaliyadda, V. Herath, P. Ekanayake, G. Thilakaratne, S. Dharmarathne “A Comprehensive Overview of Education During Three COVID-19 Pandemic Periods: Impact on Engineering Students in Sri Lanka,” in Education Sciences, Vol. 12, no. 3: 197, March, 2022. 

 
 

PROJECT: Application of Deep Learning to Estimate Ground-level Air Pollution in Sri Lanka using Micro-satellite Imagery and Low-cost Sensors

DEEE Members: Dr. Nalin Harischandra
This research is supported by the main project "Building capacity to improve air quality in South Asia: Reducing PM2.5 through low-cost sensor network driven policy decisions" which is funded by the U.S. State Department - Grant to Dr. Gayan Bowatte, AHS, University of Peradeniya.

Overview

 

Spatial Temporal PM25

 

Project Summary

Setting up low cost sensor network- BlueSky to measure PM2.5 in Colombo, Kandy and around the Island.
Calibration of sensors against reference monitors and assess the spatial variability of PM2.5 within Colombo and Kandy regions.
Download micro-satellite images (ortho visual) from Planetscope for each and every sensor and preprocess- remove outliers and cloudy images and then crop- them to associate with PM2.5 data.
Development of the database associating PM2.5 and other meteorological data to micro-satellite images.
Design and implementation of the Deep learning based spatial-temporal model for predicting PM2.5 using satellite imagery.

 

COLLABORATORS

Department of Basic Science, Faculty of Allied Health Sciences, University of Peradeniya – Dr. Gayan Bowatte (PI)

University of Sri Jayawardenapura, Sri Lanka – Prof. Meththika Vithanage

Duke University, USA – Prof. Mike Bergin (Project Director)

North Carolina State University, USA - Dr. Prakash Bhave

Eng Gimhan Aththanayake

Mr. Mahesh Senarathna

Project Consortium - India, Nepal, Pakistan, Bangladesh, Maldives, Bhutan

 

 

PROJECT: Elephant-Train Collision Prevention System

DEEE Members: Prof. Lilantha Samaranayake, Prof. Kithsiri M. Liyanage, Dr. Nalin Harischandra, Dr. Tharindu Weerakoon, Dr. Parakrama Ekanayake.
This research was primarily funded by IEEE Robotics and Automation Society Special Interest Group on Humanitarian Technology (RAS-SIGHT).

Overview

 

Elephant_Train CP

 

Project Summary

Development of Machine Learning based Elephant detection system using Infra-Red camera images.
Implementation of YOLO3 based detection algorithm on NVIDIA Jetson Xavier AGX development board within ROS environment.
Analysis of contrast and other image enhancements of night time images for improving elephant detection.
Design and development of a Hot spot system which consists of a Camera unit, solar panel, 12V dc battery, solar battery charger, router, Jetson Xavier AGX, Arduino board with SIM800L and inverter.
Development of Mobile Application for the end user - Train driver or Railway station masters- to locate the Elephants and to remotely access the status of the Hot Spot System.

 

COLLABORATORS

University of Technology, Sydney (UTS) – Prof. Gamini Dissanayake, Dr. Ravindra Ranasinghe, Mr. Maleen Jayasuriya 

Eng. Shanaka Ramesh Gunasekara

Sri Lanka Railway Department

 

KEY PUBLICATIONS

⮚ Gunasekara S, Jayasuriya M, Harischandra N, Samaranayake L, Dissanayake G (2021) "A convolutional neural network based early warning system to prevent elephant-train collisions", In 2021 IEEE 16th International Conference on Industrial and Information Systems (ICIIS), pp 271-276, 09-11 December 2021

⮚ Gunasekara S, Jayasuriya M, Harischandra N, Samaranayake L, Dissanayake G (2021) "A vision-based early warning system to prevent elephant-train collisions", In International Conference on Wildlife Technologies and Wildlife Conservation (ICWTWC 2021), August 2021, London, UK; Open Science Index, Biological and Ecological Engineering Vol:15, No:08 

⮚ Samaranayake L. et al. (2020) "Elephant train collision prevention system", In workshop on Humanitarian Robotics, IEEE International Conference on Robots and Systems (IROS), Las Vegas, USA, 09 November 2020 (ONLINE) 

 
 

PROJECT: Elephant-Train Collision Prevention- On Train System

DEEE Members: Prof. Lilantha Samaranayake, Dr. Nalin Harischandra, Dr. Tharindu Weerakoon.
This research project was primarily funded (hardware and financialiy) by the NVIDIA Inc., USA through its Academic Hardware Grants Program.

Overview

 

Elephant_Train CP Ontrain module

 

Project Summary

Improvement of Deep Learning based Elephant detection system using Infra-Red camera images.
Implementation of YOLO3 based detection algorithm on NVIDIA Jetson Xavier AGX development board within ROS environment.
Implementation of a sementic segmentation algorithm for detection of rail track specialy in night time images.
Design and development of an algorithm to infere the elephants direction of movement when detected nearby to the train track. Essentially, the threat events are generated only when the elephant moving towards the track.
IMprovements to communication Application for the end user - Train driver or Railway station masters- to locate the Elephants and to remotely access the status of the Hot Spot System.

 

COLLABORATORS

University of Technology, Sydney (UTS) – Prof. Gamini Dissanayake, Dr. Maleen Jayasuriya 

Eng. Tuan Azzam

Sri Lanka Railway Department

 

 

PROJECT: Biomedical Signal & Image Processing and AI for Pregnant Mother and Fetus Condition Monitoring, Human Action Recognition and Gait Analysis via Wearable Devices

DEEE Members: Prof. M.P.B. Ekanayake, Prof. G.M.R.I. Godaliyadda, Dr. Janaka Wijayakulasooriya, Prof. H.M.V.R. Herath.
This research was primarily funded by IEEE Robotics and Automation Society Special Interest Group on Humanitarian Technology (RAS-SIGHT).

Overview

 

BioMed Wearables

 

Project Summary

Design and Development of a IMU based Wearable, low cost, Non-Invasive, Non-Transmitting Fetal Condition Monitoring Device for pregnant mothers.
Mobile application was developed to be used with the sensor for pregnant mothers.
AI and Signal Processing based algorithms were developed for accurate detection of movements from artifacts.
Interference cancellation techniques were used to remove artifacts to isolate breathing pattern parameters at different energy levels. Breathing pattern analysis at different stages of pregnancy.
Multi-sensory IMU based Wearable detection system was designed and developed with a modular architecture to detect limb movements for biometric analysis of human movement patterns.

 

COLLABORATORS

Department of Department of Obstetrics and Gynecology, University of Peradeniya – Prof. Chathura Ratnayake

Department of Medicine, University of Peradeniya – Dr. Duminda Yasaratne

Department of Physiology, University of Peradeniya – Prof.Tharaka Dassanayake

Department of Physiology, University of Peradeniya – Dr. Indu Nanayakkara

 

KEY PUBLICATIONS

⮚ Eranda Somathilake, Upekha Hansanie Delay, Janith Bandara Senanayaka, Samitha Lakmal Gunarathne, Roshan Indika Godaliyadda, Mervyn Parakrama Ekanayake, Janaka Wijayakulasooriya, Chathura Rathnayake, "Assessment of Fetal and Maternal Well-Being During Pregnancy Using Passive Wearable Inertial Sensor," in IEEE Transactions on Instrumentation and Measurement, Vol. 71, pp. 1- 11, Art no. 4005111, May 2022. (SCIE Indexed Journal with Impact Factor 5.3)

⮚ Upekha Delay, Thoshara Nawarathne, Sajan Dissanayake, Samitha Gunarathne, Thanushi Withanage, Roshan Godaliyadda, Chathura Rathnayake, Parakrama Ekanayake, Wijayakulasooriya, “Novel non-invasive in-house fabricated wearable system with a hybrid algorithm for fetal movement recognition”, PLoSONE 16(7): e0254560. (SCIE Indexed Journal with Impact Factor 3.3 - Ranked in Top 30 of all publications with h5index of 185) 

⮚ B. M. T. M. Nawarathne, W.T.Ruwanga, M. S. L. Gunarathne, U. H. Delay, E. Somathilake, J. B. Senanayaka, G.M.R.I Godaliyadda, M.P.B. Ekanayake, R. M. C. J. Rathnayake, J. V. Wijayakulasooriya. “Comprehensive Study on Denoising of Medical Images Utilizing Neural Network Based Auto-encoder” Third International Conference on Advanced Computational and Communication Paradigm (ICACCP - 2021), Sikkim, India, March, 2021. 

 
 

PROJECT: Computer Vision and Smart Surveillance

DEEE Members: Prof. G.M.R.I. Godaliyadda, Prof. M.P.B. Ekanayake, Prof. H.M.V.R. Herath, Prof. Janaka Ekanayake.

Overview

 

Smart Surveillance

 

Project Summary

Human Behavior modeling, group activity detection through video feeds. Utilization of Deep Learning based Video Transformer Networks, Graph Attention Networks, Auto Encoder Architectures to enable action spotting and video inferencing.
Utilization of unsupervised clustering techniques for human motion pattern analysis. Human motion tracking under dynamic background scenes. Foreground estimation under rapidly fluctuating dynamic backgrounds.
Development of AI based Computer Vision solution for vehicle identification and tracking for traffic surveillance and planning. Estimation of traffic parameters such as junction statistics, vehicle headway, speed, dimension and events detection.
Image enhancement and illumination/augmentation under low light conditions. Enhancement via decomposing images into its intrinsic properties so that it is possible to improve the illumination property of the image separately.
We propose a neural network architecture capable of this decomposition using physics-based parameters derived from the image.
Smart segmentation of images based on information spread for forgery detection and Image processing for human affect and emotion detection
Computer vison-based algorithms for crowd counting and crowd forecasting. Visual surveillance for social distance monitoring and COVID19 spread threat assessment.

 

COLLABORATORS

Department of Civil Engineering, University of Peradeniya – Dr I. M. S. Sathyaprasad

Department of Computer Engineering, University of Peradeniya   – Prof Roshan Ragel

Department of Community Medicine, University of Peradeniya - Prof Samath Dharmaratne 

Ministry of Defense, Sri Lanka

Simon Fraser University, Canada – Dr. Chinthaka Dinesh

Johns Hopkins University, USA – Mr Chaminda Bandara

University of Surrey, UK – Mr Umar Marikkar

 

KEY PUBLICATIONS

⮚ Gihan Jayatilaka, Jameel Hassan, Suren Sritharan, Janith Bandara Senanayaka, Harshana Weligampola, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath, Janaka Ekanayake, and Samath Dharmaratne. 2022. "Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations" Applied Sciences Vol. 12, no. 17: 8428, August 2022.

⮚ Harshana Weligampola, Gihan Jayatilaka, Suren Sritharan, Parakrama Ekanayake, Roshan Ragel, Vijitha Herath, Roshan Godaliyadda, “An Optical physics inspired CNN approach for intrinsic image decomposition”, 2021 IEEE International Conference on Image Processing (IEEE ICIP 2021), Anchorage, Alaska, USA, September, 2021.

⮚ H. Weligampola, G. Jayatilaka, S. Sritharan, R. Godaliyadda, P. Ekanayake, R. Ragel and V. Herath, "A Retinex based GAN Pipeline to Utilize Paach ftOL– Prof. Mike Bergin (Project Dirn4a, Harshana Welig,unity Medici Ap, and Samath mproveG. J 6, L is perence," s and Systems ugh locnceG. v> Mor:buwat train colliin"> ⮚ (MERd ritMor:buwa

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PROJECT: Computer Vision and Smart Surveillance

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Overview

 

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COLLABORATORS

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PROJECT: Computer Vision and Smart Surveillance

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Overview

 

Smart Surveillance

 

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COLLABORATORS

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PROJECT: Computer Vision and Smart Surveillance

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Overview

 

Smart Surveillance

 

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COLLABORATORS

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PROJECT: Computer Vision and Smart Surveillance

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Overview

 

Smart Surveillance

 

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Project Summary

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COLLABORATORS

Department of Civil Engineering, University of Peradeniya – Dr I. M. S. Sathyaprasad

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PROJECT: Computer Vision and Smart Surveillance

DEEE Members: Prof. G.M.R.I. GodaliyaddSpmert GrWeliuter visFooidGue.WokgriQua>Downion and evR. Herath, Prof. Janaka Ekanayake.d="edu_main">

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Overview

 

Smart Surveillance

 

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COLLABORATORS

Department of Civil Engineering, University of Peradeniya – Dr I. M. S. Sathyaprasad

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PROJECT: Computer Vision and Smart Surveillance

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Overview

 

Smart Surveillance

 

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Project Summary

Human Behavior modeling, group activity detection through video feeds. Utilization of Deep LI pltor human affeanheEGrable abtatu-cpplied -iembefre the elephants direction of movement when deteMoniteanh Welp1- uv Psi plteBCIimation of uh at icpplie 2021
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COLLABORATORS

Department of Civil Engineering, University of Peradeniya – Dr I. M. S. Sathyaprasad

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