Browsing by Author "Yang, CY"

Now showing 1 - 8 of 8

item: Conference-Full-text
Human activity recognition using cnn & lstm
(Faculty of Information Technology, University of Moratuwa., 2020-12) Shiranthika, C; Premakumara, N; Chiu, HL; Samani, H; Shyalika, C; Yang, CY; Karunananda, AS; Karunananda, AS; Talagala, PD
In identifying objects, understanding the world, analyzing time series and predicting future sequences, the recent developments in Artificial Intelligence (AI) have made human beings more inclined towards novel research goals. There is a growing interest in Recurrent Neural Networks (RNN) by AI researchers today, which includes major applications in the fields of speech recognition, language modeling, video processing and time series analysis. Recognition of Human Behavior or the Human Activity Recognition (HAR) is one of the difficult issues in this wonderful AI field that seeks answers. As an assistive technology combined with innovations such as the Internet of Things (IoT), it can be primarily used for eldercare and childcare. HAR also covers a broad variety of real-life applications, ranging from healthcare to personal fitness, gaming, military applications, security fields, etc. HAR can be achieved with sensors, images, smartphones or videos where the advancement of Human Computer Interaction (HCI) technology has become more popular for capturing behaviors using sensors such as accelerometers and gyroscopes. This paper introduces an approach that uses CNN and Long Short-Term Memory (LSTM) to predict human behaviors on the basis of the WISDM dataset.
item: Conference-Full-text
iot driving assistant system for elderly
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Huang, KM; Hsieh, TL; Yi, CA; Samani, H; Yang, CY; Sudantha, BH
Nowadays in this modern globalizing world, elders are given a more prominent place in the society. Thus a lot of new technological innovations are being invented in order to facilitate their day to day activities. The elder driving assistive technology is one such big step which has introduced to cater the demands of elderly people. This technology is beneficial in increasing safety of the driver and passengers, and also has affect in reducing the public cost of society safety. This study proposes a driver assistive tool for elder drivers which respond immediately in case of potential accidents by giving appropriate warning or arrestments. This tool monitors the movement of the vehicle dynamically with the behavior of the driver, detects the irregularity between the driver and the vehicle. Sensory devices which have been installed in the vehicle include the imaging camera, inertial measurement unit, Lidar scanner, steering wheel angle sensor, depression sensors on accelerator pedal and brake pedal to form a sensory network for the purpose of collecting signals for irregularity identification. In order to detect the surrounding suspicious objects, an array of ultrasonic sensors was installed on the vehicle and to evaluate the irregularity level of the danger, a sensor harness was integrated. When the risk level reaches a significant level, a danger classification information will be delivered to the processing center and a corresponding ensemble of sensory feedback will be activated to remind to the driver. Driver will be notified via the signal interface automatically, which has been implemented to resist the operation or even stop the vehicle immediately when a dangerous situation related to inaccurate behavior is detected to prevent potential disasters.
item: Conference-Full-text
Iot empowered open sensor network for environmental air pollution monitoring system in smart cities
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2023-12-07) Sudantha, BH; Manchanayaka, MALSK; Yang, CY; Premachandra, C; Firdhous, MFM; Sumathipala, KASN; Piyatilake, ITS; Thalagala, PD; Ganegoda, GU; Thanuja, ALARR; Dharmarathna, P
Designing of an IoT-based air pollution monitoring system is a proactive and impactful approach to tackle the critical issue of air pollution and its adverse effects on the environment. Such a system is instrumental in offering real-time air quality data, empowering swift responses when pollution levels exceed acceptable thresholds. The system's design encompasses various hardware components, including carefully chosen air quality sensors, a microcontroller (Arduino Mega 2560), a communication module for the network connectivity, and a sustainable power supply. On the software front, the system involves data collection from sensors, data processing with calibration and conversion to air quality parameters, secure data transmission, storage, analysis, and an alerting mechanism. User interface development facilitates real-time and historical data visualization, while stringent security measures ensure data protection. Scalability, integration, and strategic deployment in key areas further enhance the system's effectiveness. Regular maintenance and updates are vital to ensuring accurate and reliable performance. Overall, implementing an IoT-based air pollution monitoring system is an essential step toward monitoring and addressing air quality concerns in a comprehensive and timely manner, ultimately fostering environmental awareness, and driving pollution mitigation efforts.
item: Conference-Full-text
Object detection with deep learning for underwater environment
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Wang, CC; Samani, H; Yang, CY; Sudantha, BH
In this research we have investigated the usage of deep learning algorithms for object detection in underwater environment and specifically we have employed YOLOv3 algorithm in our study. Details of the algorithm and experimental results are presented. We used available underwater database for training and investigated the method by experimenting to detect and identify the type of the fish in an aquarium in the lab. The results are also explained in this paper.
item: Conference-Full-text
Open, iot powered environmental air pollution monitoring framework for traffic management
(Faculty of Information Technology, University of Moratuwa., 2021-12) Manchanayaka, MALSK; Wijesekara, JPD; Yang, CY; Premachandra, C; Firdhous, MFM; Sudantha, BH; Ganegoda, GU; Mahadewa, KT
An IoT-enabled Environmental Ambient Air Pollution Monitoring System was developed using open technologies including open hardware, open software, and open standards. It can detect and measure the concentrations of four major air pollutant gases. The system measures concentrations of air pollutant gases such as NO 2 , CO, SO 2 , and O 3 using gas sensor modules. The system was developed to comply with IEEE 1451 standard, where the Smart Transducer Interface Module (STIM) was implemented using the Arduino Mega controller. Network Capable Application Processor (NCAP) was implemented using a NodeMCU and ATmega328P controller which is connected to the main board, STIM via the Transducer Independent Interface (TII). The system measures the concentrations of pollutant gases in every 10 seconds and collects all data upto 10 minutes. The measured concentration levels averaged to 10 min intervals and would be sent to the central server with the timestamp and data quality index. For the implementation of a fully open framework, the pollutant data made available free, and anyone can access data and they could be used for a relevant purpose considering the quality index.
item: Conference-Abstract
Polynomial regression real patient state estimate for clinical decision-making
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2022-12) Hung, CY; Wang, CY; Chen, KW; Yang, CY; Sumathipala, KASN; Ganegoda, GU; Piyathilake, ITS; Manawadu, IN
With the progress of the times, science and technology are changing with each passing day. Clinical decision has become more and more important in medicine nowadays. Clinical decision not only helps clinicians to get immediately crucial decisions; but also provides advices to inexperienced clinicians. In the early days, clinicians could only rely on their own experience and medical reports to make decisions. This process that clinicians analyze patients was very time-consuming. In order to solve these problems, we developed a scoring model. We can analyze patient conditions according to the value of each parameter by using the patient data collected by the hospital. Through computer analysis, evaluations, predictions and optimizations, the suitable model for clinicians and patients can be built. In this paper, we propose a nonlinear polynomial regression approach as a model for predicting patient health scores. The model that predicts patient health score fits multiple researches and clinical examinations through computer simulations. The predicted results are corresponded to the real results when we use the model. With the benefit of the model, it would be easier for clinicians to make clinical decision. In conclusion, our model can not only analyze patient’s conditions, but also predict patient health score via the support of appropriate parameters. This model has the potential to become a valuable tool for clinicians on clinical decision-making in the near future.
item: Conference-Full-text
Ros-based mobile robot pid and mpc control
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2023-12-07) Chiang, PL; Wu, YC; CHEN, SC; Yang, CY; Piyatilake, ITS; Thalagala, PD; Ganegoda, GU; Thanuja, ALARR; Dharmarathna, P
In this study, a Robot Operating System (ROS) based Mecanum-wheeled mobile robot is designed for two algorithms developed scheme, one is a Proportional-Integral- Derivative (PID) control algorithm directly implemented into the online controller firmware, and the other hand is a Model Predictive Control (MPC) algorithm implemented on an independent PC for a remote control. In the PID control algorithm, ultrasonic distance detection is used to keep the vehicle running parallelly along a wall. In the MPC algorithm, the vehicle is able to run according to planned paths and create the map by Lidar SLAM. In the paper, the real implementation of the system is detailed practical experiment validations.
item: Conference-Full-text
A short survey on adaptive algorithms in identifying wiener models
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2018) Yang, CY; Yang, JS; Yu, L; Wijesiriwardana, CP
Wiener model with its corresponding excellence were often adopted to identify varieties of nonlinear systems. The short paper is aimed to explore the rationale to establish the model from its very theoretical beginning. To uncover the success of the model, the key of the adaptive algorithms which are capable of adapting the changes of the dynamics is also covered.