Browsing by Author "Chethana, E. J. K. S."

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IoT-enabled intelligent pedestrian crossing signal light system with violation tracking
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Rupasinghe, R. A. I. M.; Ranasinghe, R. A. J. B.; Moragoda, Y. G. D.; Navodya, W. D. I.; Premasiri, R. H. M. D.; Chethana, E. J. K. S.; Seneviratne, J. A.; Gunawardana, K. D. B. H.
The urban pedestrian crossing environment presents numerous challenges in ensuring the safety of pedestrians and maintaining smooth traffic flow. Traditional pedestrian signaling systems operate on fixed timings and have limited capabilities, making it difficult to manage the complexities of modern urban traffic effectively. This research introduces an innovative system for pedestrian crossing signal lights integrated with violation tracking and real-time data analytics to improve pedestrian safety and smooth traffic flow. This encompasses computer vision for pedestrian detection, machine learning (ML) for predictive analysis, adaptive signal light timers, sirens for violation deterrence, and IoT components for seamless real-time operation. The presented methodology combines real-time pedestrian detection, adaptive signal light timing, weather detection, and IoT integration so that all these subsystems work smoothly. The issues resolved include integrating image processing with hardware, selecting an efficient pedestrian detection model, optimizing camera angles for accurate detection, and transitioning from an Arduino to a Raspberry Pi 4 Model B. The Raspberry Pi offered better processing power, enabling faster and more complex data handling. A case study was done at a location proximate to the University of Kelaniya, and the average crossing time taken for the pedestrian crossing was recorded as 18.5 seconds, which can be factored using databases with larger data sets and simple ML models based on the day of the week. The issues that were resolved include integrating image processing with hardware, selecting an appropriate pedestrian detection model such as a Convolutional Neural Network (CNN) that works well within the outdoor environment, setting optimal camera angles for accurate pedestrian detection, and transitioning from an Arduino to a Raspberry Pi 4 Model B for enhanced processing capabilities. Integrating image processing with hardware posed challenges due to the need for real-time data transmission and processing, which required seamless communication between the software and hardware components. The pedestrian detection model was chosen based on its accuracy, speed, and ability to perform well in varying lighting and weather conditions. The transition to the Raspberry Pi 4 Model B, with its superior processing power and memory compared to the Arduino, allowed the system to handle more complex tasks, such as real-time data analysis and multiple input streams, significantly improving performance and efficiency. A custom dataset of overhead views of pedestrians was created, with images acquired from a similar environment within the university, manually labelling the images and achieving an 80% accuracy after training on Google Collab. The real-time data processing system is vital in making dynamic signal timing changes, tracking violations to encourage safe pedestrian behavior, and managing pedestrian and vehicle traffic flow. These findings endorse the broader adoption of intelligent systems, for innovative city projects toward safer and more efficient urban environments.
Taekwondo head guard and chest guard for training and scoring
(Faculty of Science, University of Kelaniya Sri Lanka, 2023) Chethana, E. J. K. S.; Loshan, T. J.; Jayasumana, M. A. I. D.; Sandanayake, S. P. D.; Randeniarachchi, R. A. N. D.; Nandasiri, D. D. D. S.; Senevirathna, J. A.; Gunawardhana, K. B. D. H.
Taekwondo is a highly popular martial art and Olympic sport that has been rapidly gaining worldwide recognition. With its dynamic kicks, precise strikes, and intricate footwork, Taekwondo requires a scoring system that accurately reflects the skill and technique of the participants. However, the traditional manual scoring system, which relies on a team of referees to keep track of points, has its limitations. It can be time-consuming, prone to human errors, and challenging to ensure consistency and fairness in scoring. To address these challenges, the use of electronic scoring systems has become a necessity in Taekwondo competitions. These integrate specialized gear like chest and head guards with advanced sensors. The Electronic Body Protector (EBP) system is crucial in modern Taekwondo, accurately capturing punches, kicks, and rotational kicks. Our solution involves specialized head and chest guards with advanced sensor technology. To detect forces, BMP 180 sensors are used in the chest guard. Positioned within airbags, these sensors detect even slight pressure variations from punches. These sensors, calibrated with precision, exhibit an exceptional capacity to detect even the most suitable pressure variations arising from punches. The calibration process fine-tuned the BMP 180 sensors, orchestrating a responsive mechanism where pressure changes triggered resistance alterations, thereby generating an accurate voltage output. As a result, player punches during matches are swiftly identified and meticulously recorded. Pressure changes trigger the BMP 180 sensor to alter resistance and generate an accurate voltage output. Thus, player punches during matches are swiftly identified and recorded. The chest guard also detects body kicks using BMP 180 sensors, and the head guard recognizes rotational kicks through a gyroscope sensor connected to an ESP 8266 microcontroller. The gyroscope detects angular changes, ensuring accurate rotational kick detection. The ESP 8266 microcontroller processes data from the gyroscope, transmitting it to the scoring system. ESP 8266 microcontrollers with Bluetooth modules facilitate data exchange between guards, ensuring real-time data transfer for reliable scoring. Our design offers a comprehensive scoring solution by combining BMP 180 sensors for punch and kick detection and a gyroscope for rotational kicks. The Scoring Board connects via Wi-Fi to the ESP8266 board, updating scores promptly upon sensor-detected hits. The ESP8266 board calculates hit scores and transmits the data to the Scoring Board, which updates the display in real-time, benefiting players and spectators. Wi-Fi connectivity ensures accurate and swift score updates during competitions. The Scoring Board is vital within the EBP system, enhancing accuracy and fairness. In conclusion, our proposed design offers an economical and accurate framework for punch and kick detection in Taekwondo. This innovation benefits athletes, coaches, and referees, driving the growth of Taekwondo as an exciting sport.