Research Publications
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Item Embargo Low-Cost, High-Precision Vibration Analysis: Enhancing SHM and Seismic Data Acquisition Systems(Institute of Electrical and Electronics Engineers Inc., 2025) Sashik, D; Iddamalgoda, A; Manchanayake, N; Prasanna, R; Abeygunawardhana, P.K.WThe development of a low-frequency vibration detection device is essential for testing vibrations in crucial applications such as structural integrity, seismic activity detection and industrial machinery maintenance. Current data acquisition systems suffer from lack of sensitivity and high cost. This paper presents the design and development of a low-cost vibration detection device that uses a 3-axis accelerometer and a geophone with a resonant frequency of 4.5 Hz, where the signals are filtered using a second order low-pass filter with a 250 Hz cutoff frequency. The device is integrated with a 24-bit analog to digital (ADC) converter for ensuring a precise data acquisition and the device ensures to monitor real-time vibrations of x, y and z axis using a accelerometer and the z axis with a geophone. The effectiveness of the device was validated via experimental simulations. This developed device is a solid and cost-effective solution for engineers and professionals, where reliable low-frequency vibration monitoring is required in critical applications.Publication Embargo i-Police-An Intelligent Policing System Through Public Area Surveillance(IEEE, 2021-10-27) Jayakody, A; Lokuliyana, S; Dasanayaka, K; Iddamalgoda, A; Ganepola, I; Dissanayake, ATechnology and law enforcement are now commonly used hand in hand to improve public safety. Most police departments only use CCTV cameras at a few major intersections for remote surveillance. The public is waiting too long for emergency response lines, therefore using new technologies to improve the current policing system has become one of the police's main goals. The paper presents a coordinated framework that could identify the subtleties of violations via an automated public area surveillance system, specifically the weapon-related crimes and vehicle accidents, which are then disassembled, analyzed, and stored for future inspections. The trained models are aimed to reduce the false positives of incident detection. The weapon detection system had the best average precision (93.8%) by using YOLOv5 while the vehicle accident detection system resulted in the best average precision (94.9%) by using YOLOv4. The system is tested against the collected set of CCTV footage and tested how long it takes to create a notification which is the main goal of this system. Notification is generated in less than 5 seconds after an incident is detected. The evidence collection engine developed with MATLAB delivered the expected with an accuracy of 97% making the extracted evidence reliable to both vehicle accidents and crime scenes. Additionally, the framework provides an effective and efficient communication channel through which the residents can report crimes to regular parties.