Research Publications

Now showing 1 - 3 of 3

Embargo
Timely_Tech: IoT based Motion, Health, and Fitness Monitoring System for Laborers in Indoor and Outdoor Environments
(IEEE, 2022-07-18) Yatagama, H.C; Anuruddika, W.G.S.J; Ranasinghe, P. T. K; Jayasekara, P.D.G.T; De Silva, D; Wijendra, D
Smart wearables collect and securitize data, and in some cases, make intelligent decisions and respond to the user. "IOT based motion, health and fitness monitoring system for laborers in indoor and outdoor environments" is a concept that has been developed in order to ensure the safety of employees in their working environments. The key objective is to provide the employees with a SMART device that can monitor many of their vital bodily functionalities such as the pulse rate, oxygen in blood concentration and body temperature and thereby rectifying any potential risk or danger to any significant employee. Monitoring the motion of the limbs of each individual employee and analyzing the postural changes, degree of motion and thereby constantly keeping in track about the movements of employees is another major functionality that is proposed to be discussed under the research paper. Gaseous concentration around the working area has been another major aspect that have been taken into consideration through this study, toxic gas content levels according to the age limits that will affect each individual has been taken into note when developing the afore mentioned wearable device. Monitoring the location of the employees both online and offline will be much more convenient to track the working areas of each individual and also it will also be a great support if a certain employee faces any kind of accidental situation. Similarly, locating the working areas of a certain individual when they are offline is a novel concept has been developed in order to obtain the step count utilizing the aid of the motion detection algorithm.
Embargo
Image Enhancement Algorithm for Remote Surveillance Using Low Cost Cameras in Unevenly Illuminated Environments
(IEEE, 2021-12-07) Dharmasena, T; Abeygunawardhana, P. K. W
The surveillance domain is becoming increasingly popular due to the demand for security and safety. In terms of the data being used, the cameras linked to them play an essential role. However, in poorly lit environments, the acquired image may appear to be underexposed when the camera adjusts itself to the light available in the scene, resulting in a loss of visual information in poorly lit regions. This could result in poor functionality in image based processing, as well as a negative impact on remote surveillance monitoring activities. This study offers a novel algorithm for improving the illumination of scenes that are unevenly lit using a selective pixels processing method to enhance the illumination of the environment. Rather than processing grayscale versions of red,green and blue channels to enhance the image, this approach uses value (v) channel of an HSV image.
Embargo
Moving Robots in Unknown Environments Using Potential Field Graphs
(IEEE, 2022-02-23) Panagoda, M; Lokuliyanage, M; Senarath, A; Nethmini Nisansala, N. K. V. M; Rajapakshe, R. W. A. D. U; Rajapaksha, S; Jayawardena, C
The purpose of this research paper is to introduce a new navigation algorithm for Robot Operating System (ROS) based robots which will allow complete autonomous traversal in any given indoor environment. Turtle bot3 burger bot is the sample robot chosen for this project. This will be equipped with a Light Detection and Ranging (LIDAR) scanner with the default settings, ultrasound, Intel Real Sense camera, etc. Environment information gathered via these sensors will be sent into a remote computer for processing since the raspberry pie micro-controller with the turtle bot burger is not enough to carry out a high computation-intensive task. Once the information is received series of tasks will be carried out by the remote personal computer before executing the newly developed navigation algorithm. The data from the LIDAR scanner help to generate a 2-dimensional(2D) potential field graph. Then it will later be used for path planning by navigation algorithm. Furthermore, the Real sense camera is used for object boundary detection to produce more accurate data for the navigation algorithm. Once all the data proceed, data will return to the robot, where the navigation algorithm will start execution in parallel with a recovery behavior algorithm and scan algorithm. The recovery behavior algorithm is responsible for guiding the robot to face away from an obstacle in an event where the predetermined path is obstructed. Furthermore, it is responsible for maintaining accurate data in the cost map. Subsequently, the scanning algorithm will be used to generate maps.

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