Browsing by Author "Salehin, Sultanus"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Performance Analysis of Human Tissue-Embedded Antennas for Enhanced Wireless Power Transfer in Medical Implants
    (IEEE, 2024-05-23) Islam, Akib Jayed; Pranta, Swapnil; Salehin, Sultanus; Das, Nobel; Shawon, Md. Raihan Ahmed; Alam, Sadman Shahriar
    By developing a novel rectenna system, this study advances wireless power transmission technology for medical implants, including neurostimulators and pacemakers. With a patch antenna tuned for the 433 MHz ISM band frequency, the study painstakingly designs a biocompatible rectenna that is compatible with human flesh. The research refines the antenna design and incorporates an impedance-matching network to improve power transfer efficiency using CST Microwave Studio and ADS software. The inclusion of a nonlinear diode model, which precisely models the diode's behavior inside the rectifying circuit and optimizes the rectenna's RF-to-DC conversion process, is a novel component of this work. The antenna is positioned between the layers of skin and muscle using extensive simulations to reduce return loss and comply with specific absorption rate (SAR) safety requirements. The result of their efforts is a very effective rectenna that exhibits an approximate 84.816% RF-to-DC conversion efficiency, which represents a substantial advancement in the safe and smooth integration of wireless power technology into medical devices.
  • Thumbnail Image
    Item
    Real-Time Lane Detection and Motion Planning for Autonomous Vehicle
    (Department of Electrical and Electronic Engineering, Islamic University of Technology,Board Bazar, Gazipur, Bangladesh, 2019-11-15) Ahmed, Nadim; Salehin, Sultanus; Choudhury, Tashfique Hasnine; Rossi, Alfa
    Our dissertation describes in-depth the algorithm intended to identify lane lines on streets and highways in different conditions. Lane detection enhances the protection of the independent system to some extent. The autonomous or self-sufficient vehicle is an independent device that senses conditions and determines accordingly without any human intervention. Our emphasis was on the use of a vehicle prototype to recognize lanes that could be used later on a standard vehicle. To capture real-time video, PiCamera is embedded with a RaspberryPi 3.0 Model B for processing purposes. RaspberryPi along with battery, motors are mounted in a prototype constructed using CNC machine with sheer perfection. The real-time video captured by Picamera is sufficient enough to evaluate the performance of the algorithms used. The algorithms that have been used are the concepts of OpenCV, Hough transformation, canny edge detection algorithm and elementary algebra to compute and draw the lines. Python 2.7 was used to write the code for the relevant algorithm. The accuracy level of the algorithm used is quite astonishing. Our research works significantly in the field of autonomous vehicles. The comprehensive approach shown here offers a fairly precise and efficient solution for tracking lines. This can make a big difference in the driving experience in every way possible if used properly.