Research Collaborations | Department of Electrical and Electronic Engineering

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

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

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

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

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

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

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

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

⮚ 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 Paired and Unpaired Datasets for Enhancing Low Light Images," in proceedings of 2020 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, July, 2020.

⮚ Tharshini Gunendradasan, Chinthaka Dinesh, Roshan I. Godaliyadda, and Mervyn P. B. Ekanayake, “Expression Negation and Component Selection Algorithm for Face Recognition from Single Sample per Person”, ACTA Press Journal of Control and Intelligent Systems, Vol. 44, no. 3, pp. 103-110, 2016.

PROJECT: AI and Image Based Condition Assessment of Power System Components

DEEE Members: Prof. Manjula. Fernando, Dr. Janaka Wijayakulasooriya, Prof. Vijitha Herath, Prof. Roshan Godaliyadda, Prof. Parakrama Ekanayake Dr. Nalin Harichandra, Dr. Waranatha Abeygunasekara.

Overview

Project Summary

Development of AI based moisture estimation in power transformers by modelling FDS measurements collected from various laboratory and field aged pressboard samples under different moisture contents.

Development of AI based classification of faulty status of transformer windings by analysing FRA measurements collected from 132 kV level field aged transformers under different faulty and new conditions.

Development of statistical based classification of differently aged transformer oil based on multi spectral images taken from 132 kV field aged transformers.

Development of AI based classification of differently aged HV conductors based on IR and RGB images taken from new and aged conductor samples collected from 132 kV and 33 kV power system.

Development of statistical based classification of algal contaminated HV insulators based on multi spectral images taken from growth cultured on insulators.

COLLABORATORS

Ceylon Electricity Board, Sri Lanka - Dr. Kapila Bandara

NKT Cables, Sweden - Dr. Sarath Kumara

University of Queensland, Australia - Dr. Chandima Ekanayake

KEY PUBLICATIONS

⮚ Tharaka Wijethunge, Pawara Tharkana, Amila Wimalaweera, Janaka Wijayakulasooriya, Sarath Kumara, Kapila Bandara, and Manjula Fernando, “A Machine Learning Approach for FDS Based Power Transformer Moisture Estimation”, IEEE CEIDP 2021, Vancouver Canada.

⮚ Primash Morapitiya, Pamudu Ranasinghe, Janaka Wijayakulasooriy, Dilshan Muthukuda, Kapila Bandara and Manjula Fernando, “AI Approach for FRA Based Condition Assessment of Power Transformers” Submitted to 17th IEEE ICIIS2023.

⮚ R.M.L.S. Ramanayake, H.M.N.B. Senarath, J.M.V.D.B. Jayasundara, G.W.K. Prabhath, H.M.H.K. Weerasooriya, M.A.R.M. Fernando, S. Kumara, H.M.V.R.Herath, G.M..RI.Godaliyadda, M.P.B .Ekanayake, and S Athukorala, “Reflectance Multispectral Imaging for Identification of Algae Contamination in High Voltage Insulators”, Imaging Systems and Applications, paper ITh1B. 6, Sep 2021.

⮚ Shehan Seneviratne, Harith Udawatte, Manjula Fernando, Nalin Harischandra and Chandima Ekanayake, “Image-Based Condition Monitoring of Transmission Line Conductors Using Image Processing and Deep Neural Networks” Submitted to 17th IEEE ICIIS2023.

⮚M.A.A.P. Bandara, B.S.H.M.S.Y. Matharage, M.A.R.M. Fernando and G.A. Jayantha, “ANN Approach for Condition Assessment of Oil Filled High Voltage Current Transformers”, Trans. of Institution of Engineers (SL), 2013.

PROJECT: Lightning Hazards in Heritage Monuments in Sri Lanka and India

DEEE Members: Prof. Manjula Fernando, Dr. Sarath Kumara, Dr. Waranatha Abeygunasekara.
This project was funded by the Ministry of Science, Technology and Research, Sri Lanka under the Indo-Lanka research grants.

Overview

Project Summary

Analyse and summarizes possible lightning hazards and possible preventive measures of heritage Lord Buddha’s stupas in Sri Lanka and heritage Hindu temples and Catholic churches in India based on electro-geometrical and FEM based lightning models.

Investigates the effects of thermal and electrical shocks due to lightning on the materials used for heritage monuments and verifications by laboratory tests.

Analyse and propose the use of 2D cellular automata for leader propagation and lightning predictions in heritage monuments and mangrove forests in India.

COLLABORATORS

VIT India as PI from Indian Partners - Prof. S. Venkatesh and S. Thirumalini

Archeological Department, University of Peradeniya - Dr. D.K. Jayaratne

Department of Mathematics, University of Peradeniya - Prof. K.A.S. Susantha

University of Colombo - Prof. Mahendra Fernando

Uppsala University, Sweden - Prof. Vernon Cooray

Prof. M.P Ranaweera

KEY PUBLICATIONS

⮚ Venkatesh Srinivasan, Manjula Fernando, Sarath Kumara, Selvaraj Thirumalini, and Vernon Cooray “Modelling and Assessment of Lightning Hazards to Humans in Heritage Monuments in India and Sri Lanka“, IEEE ACCESS, Vol. 8, pp. 228032- 228048, 2020.

⮚ Selvaraj Thirumalini, Venkatesh Srinivasan, Simona Raneri, Manjula Fernando, Kunal Kakria, and Simon Jayasingh, “Response of organic lime mortars to thermal and electrical shocks due to lightning strikes“, MDPI Sustainability Journal, September 2020, Vol 12, Issue 17, 7182.

⮚ S. Venkatesh, Srisailam Sreedhar, S. Thirumalini, M.A.R.M. Fernando, and Sarath Kumara, “Lightning Protection of Ancient Chola Monument in South India Based on Three-Dimensional Geometric and Electro-Geometric Techniques”, International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-9 Issue-3, January 2020, pp 988-994.

⮚ A. Bandara, C. Ratnayake, D. Ambepitiya, S. Kumara, M.A.R.M. Fernando, S. Venkatesh, and D.K. Jayaratne, “Lightning Risk Analyses on Protected Sri Lankan Heritage Stupas”, 13th IEEE International Conference on Industrial and Information Systems ICIIS2018, IIT Ropar, Roparnagar, India, December 2018, pp. 291-296.

⮚ Venkatesh Srinivasan, Deepshikha Kumari, and M.A.R.M. Fernando, “Two Dimensional Cellular Automaton for Lightning Leader Propagation and Prediction in Giant South Indian Heritage Monument”, IEEE Innovations in Power and Advanced Computing Technologies (i-PACT) (2021), India.

PROJECT: Experience on Diagnosis of Power Transformers

DEEE Members: Prof. Manjula Fernando.

Overview

Project Summary

Review experiences related to use of diagnostic tools for power transformers based on frequency domain measurements at different geographical regions of the world including Australia, Malaysia, Sri Lanka and UK.

Report findings of transformer diagnostics on 577 power transformers ranging up to 1000MVA of power, 400kV of voltage and age of 65 years collected from the four counties.

COLLABORATORS

NKT cables Sweden - Dr. Sarath Kumara

University of Manchester, UK - Prof. Zhongdong Wang

University of Exeter, UK - Dr. Shanika Matharage

The University of Queensland, Australia - Dr. Chandima Ekanayake

Energy Queensland, Australia - Mr. Prasanna Wickramasuriya

Universiti Tun Hussein Onn, Malaysia - Dr. Fairouz Yousuf

Chalmers University of Technology, Sweden - Prof. Stanislaw Gubanski

CEB, Sri Lanka - Dr. Kapila Bandara

KEY PUBLICATIONS

⮚ Sarath Kumara, Shanika Matharage, Kapila Bandara, Prasanna Wickramasuriya, Fairouz Yousuf, Chandima Ekanayake, Manjula Fernando, Zhongdong Wang, Stanislaw Gubanski, “Frequency Domain Measurements for Diagnosis of Power Transformers: Experiences from Australia, Malaysia, Sri Lanka and UK”, Cigre Science and Engineering Journal, October 2021

PROJECT: Hyper Spectral Imaging for Remote Sensing

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

Overview

Project Summary

Development of Novel signal/image processing and Deep Learning based AI algorithms for unmixing of Hyper-Spectral Image data from Satellites to generate informative land cover maps.

Utilization of DL techniques for sharpening and resolution enhancement of HIS images using RGB data.

Lithological mapping of mineral deposits in Sri lanka: Mapping surface limestone in Jaffna peninsula and Ilmenite and Monmonorolite coverage in the North-East, Central and North-Central, using HSI data.

Remote sensing based Bathymetric survey of lagoons and vegetation zone mapping in Sri lanka using HSI data.

Mapping the spatio-temporal progression of algae in fresh water reservoirs of Sri Lanka.

COLLABORATORS

Department of Geology, University of Peradeniya – Prof. A. Senaratne

Department of Civil Engineering – Prof Shameen Jinadasa

National Aquatic Resources Research and Development Agency (NARA)

National Water Supply and Drainage Board (NWSDB)

KEY PUBLICATIONS

⮚ E. M. M. B. Ekanayake, H. M. H. K. Weerasooriya, D. Y. L. Ranasinghe, S. Herath, B. Rathnayake, G. M. R. I. Godaliyadda, M. P. B. Ekanayake, H. M. V. R. Herath, "Constrained Nonnegative Matrix Factorization for Blind Hyperspectral Unmixing Incorporating Endmember Independence", in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 14, pp. 11853-11869, November, 2021.

⮚B. Rathnayake, E. M. M. B. Ekanayake, K. Weerakoon, G. M. R. I. Godaliyadda, M. P. B. Ekanayake and H. M. V. R. Herath, "Graph-Based Blind Hyperspectral Unmixing via Nonnegative Matrix Factorization", in IEEE Transactions on Geoscience and Remote Sensing, vol.58, no. 9, pp. 6391 – 6808, September, 2020.

⮚ Mevan Ekanayake; Bhathiya Rathnayake; Hasantha Ekanayake; Anusha Rathnayake; Vijitha Herath; Roshan Godaliyadda; Parakrama Ekanayake; “Enhanced Hyperspectral Unmixing via Non-Negative Matrix Factorization Incorporating the End Member Independence”, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS-2019), Yokohama, Japan, August, 2019.

⮚ S.S.P. Vithana, E.M.M.B. Ekanayake, E.M.H.E.B. Ekanayake, A.R.M.A.N. Rathnayake, G.C. Jayatilaka, H.M.V.R. Herath, G.M.R.I. Godaliyadda and M.P.B. Ekanayake, “Adaptive hierarchical clustering for hyperspectral image classification: Umbrella Clustering”, Journal of Spectral Imaging, Vol. 8, Article ID aa1 (2019).

⮚ Mevan Ekanayake, Hasantha Ekanayake, Anusha Rathnayake, Sajani Vithana, Vijitha Herath, Roshan Godaliyadda and Parakrama Ekanayake, “A Semi-Supervised Algorithm to Map Major Vegetation Zones using Satellite Hyperspectral Data,” in 9th Workshop on Hyperspectral Image and Signal Processing (WHISPERS 2018), Amsterdam, The Netherlands, Sep. 2018.

PROJECT: Spectral Imaging for Food and Water Quality Estimation

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

Overview

Project Summary

Design and Development reflectance or transmittance based and dual mode Multi-Spectral (MSI) imaging system for Food Quality assessment and Water Quality estimation.

Determination of adulteration levels of turmeric power using multispectral imaging using functional mapping. As in the case of many widespread spices, turmeric powder is often adulterated using various additives and colorants.

Estimation of the adulteration and reheating status of coconut oil using novel data driven unsupervised clustering algorithms.

Meat Quality Estimation: The visual appearance, textural patterns, and color of fresh meat are the main criteria used by the customers when choosing high-quality meat products.

Design of automated fish grading systems using image processing this includes a Mobile App.

Estimation of sugar adulteration on Black tea using spectral imaging.

Automated water quality estimation (pH, Electric Conductivity, Turbidity and YSS) using multispectral imaging. This research proposes two methods to assess the pH of water using multispectral images.

COLLABORATORS

Department of Food Science and Technology – Prof Terence Madujith

Department of Civil Engineering – Prof Shameen Jinadasa

National Aquatic Resources Research and Development Agency (NARA)

Tea Research Institute (TRI)

National Water Supply and Drainage Board (NWSDB)

KEY PUBLICATIONS

⮚ D. Y. L. Ranasinghe; H. K. Weerasooriya; S. Herath; M. P. Bandara Ekanayake; H. M. V. R. Herath; G. M. R. I. Godaliyadda; Terrence Madhujith; "Transmittance Multispectral Imaging for Reheated Coconut Oil Differentiation" in IEEE Access, Vol. 10, pp. 12530-12547, January, 2022.

⮚ Wele Gedara Chaminda Bandara, Gode Withanage Kasun Prabhath, Dissanayake Walawwe Sahan Chinthana Bandara Dissanayake, Vijitha Rohana Herath, Gunawath Mudiyanselage Roshan Indika Godaliyadda, Mervyn Parakrama Bandara Ekanayake, Dhanushika Demini, Terrence Madhujith, “Validation of multispectral imaging for the detection of selected adulterants in turmeric samples”, Journal of Food Engineering, Volume 266, Article 109700, February, 2020.

⮚ H. M. H. K. Weerasooriya, H. M. S. Lakmal, D. Y. L. Ranasinghe, W. G. C. Bandara, H. M. V. R. Herath, G. M. R. I. Godaliyadda, M. P. B. Ekanayake, and T. Madujith, "Transmittance Multispectral Imaging for Edible Oil Quality Assessment" in Imaging and Applied Optics Congress, OSA Technical Digest (Optical Society of America, 2020), paper JW5C.8., Vancouver, Canada, June, 2020.

⮚ G. W. K. Prabhath, W. G. C. Bandara, D. W. S. C. B. Dissanayake, H. M. V. R. Hearath, G. M. R. I. Godaliyadda, M. P. B. Ekanayake, S. M. D. Demini, and T. Madhujith, "Multispectral Imaging for Detection of Adulterants in Turmeric Powder" in Optical Sensors and Sensing Congress (ES, FTS, HISE, Sensors), OSA Technical Digest (Optical Society of America, 2019), paper HTu3B.3., San Jose, California, USA, June, 2019.

⮚ A. Wijesinghe, D. Wickramsinghe, C. Wijedasa, Y. Ranasinghe, V. Herath, R. Godaliyadda, P. Ekanayake, S. Jinadasa, “Transmittance Multispectral Imaging System to Estimate Potable Water Quality Parameters”, 2021 OSA Imaging and Applied Optics Congress, OSA Virtual Meeting, July, 2021.

PROJECT: Electroencephalography based Brain-Computer-Interfacing (EEG based BCI) with Haptic Feedback

DEEE Members: Dr. Ruwan Ranaweera, Dr. Janaka Wijayakulasooriya, Dr. Nalin Harishchandra.

Overview

Project Summary

Implementation of an EEG based brain-computer-interfacing system for robot arm control.

Develop an inexpensive, simple BCI solution with low computational cost.

Develop novel classification algorithms to identify features in EEG that can be reliably used to control a device, such as a robotic arm, a keyboard, or a wheel chair.

Development of different strategies to control devices using EEG.

Use of haptic feedback to improve the subject perception about the control task.

Optimization of resources while maximizing accuracy of the detection of intention to control a device.

COLLABORATORS

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

Kent State University, Ohio, USA – Prof. Kwangtaek Kim

KEY PUBLICATIONS

⮚ S.P. Karunasena, D.C. Ariyarathna, R. Ranaweera, J. Wijayakulasooriya, K. Kim and T. Dassanayake, "Single-Channel EEG SSVEP-based BCI for Robot Arm Control," 2021 IEEE Sensors Applications Symposium (SAS), 2021, pp. 1-6