Healthcare Systems Design of Intelligent Testing Centers: Latest Technologies to Battle Pandemics such as Covid-19 highlights the importance of designing intelligent testing centers requiring no human intervention during sample collection and testing of the Covid-19 virus and all similar viruses. This book introduces the background, medical requirements, and new research on medical robotics applications, including general Covid-19 testing techniques, development considerations for intelligent testing booths, kinematic and dynamic modeling, design specifications and optimization, numerical verifications, actuators, and sensors in medical applications of artificial intelligence and robotics systems.
Tawanda Mushiri is a senior lecturer in the Department of Biomedical Informatics and Biomedical Engineering under the Faculty of Engineering and the Built Environment at the University of Zimbabwe. His research interests are in artificial intelligence, robotics, biomedical engineering, medical physics, and healthcare systems design. He has published 2 books, 11 chapters, 23 journals in highly accredited publishers, and 87 conferences in peer reviewed publishers. He has also supervised more than 200 student undergraduate projects, 20 masters students to completion, and 2 PhD students in progress. Tawanda is a member of the Zimbabwe Institute of Engineers and the Engineering Council of Zimbabwe, and is in the process of finalizing his patent for robotic first aid in passenger vehicles, which aims to reduce deaths in global society where accidents occur. Before becoming an academic, Tawanda Mushiri worked as a Professional Engineer for the National Oil Company of Zimbabwe (NOCZIM) (Pvt.) Ltd (Supervising and delegating preventive maintenance report forms of machines, working both as an engineer and an operator with RSVIEW 32 runtime (to maintain and control fuel plant processes) and Entis 5.17x and Entis Pro (to monitor and control fuel tank inventory). After NOCZIM, Tawanda did a lot of consultancy in the following companies: * Coal Beneficiation for the Metallurgical Industry US$30,000 and Bots P550,000. * Improving access to healthcare services and pregnancy outcomes using Mobile health technology in the COVID-19 pandemic in Zimbabwe (Under review by NIH) * RISK ASSESSMENT OF THE FERUKA PETROLEUM HANDLING DEPOT IN RELATION TO THE ADJOINING FERUKA REFINERY STRUCTURE AND THE OXYGEN AND ACETYLENE PRODUCTION PLANT - (December 2019). * US$10,000, Preliminary hazard analysis for the NOIC Ruwa Plant * Design of an automated Steel Ball Making Machine SHENZHU STEEL BALL MANUFACTURERS PVT LTD * 2016; Design of a small-scale weeding machine for a developing nation, sponsored by the University of Zimbabwe, US$3 430,00 (1 August 2015 - 31 July 2016). Gadget manufactured and completed, nice piece of knowledge. 3D printing was done to the prototype machine * 2016; Design of an economic solar panel cleaner for multipurpose use, sponsored by the University of Zimbabwe, US$2 940,00 (1 August 2015 - 31 July 2016). * 2015; INDUSTRIAL DEVELOPMENT ZONES ANALYSIS IN INDUSTRIAL PARKS IDENTIFIED FOR GREEN INDUSTRIES AND WASTE MANAGEMENT SECTOR ON BEHALF OF THE CLEANER PRODUCTION CENTRE OF SOUTH AFRICA: Wadeville and Alrode Industrial Parks - Gauteng Province; sponsored Marvellous Moyo is an undergraduate student in the department of Mechatronics and Industrial Engineering, class of 2021, under the Faculty of Engineering and the Built Environment at the University of Zimbabwe. He has advanced skills in engineering design, 3D modelling and simulation, and intends to specialize in the field of robotics, artificial intelligence, health 4.0, aerodynamics, renewable energy, and has his first journal article under review with a highly credited publisher. Marvel is a technology enthusiast and dedicates most of his time researching on artificial intelligence, robotics, biomedical engineering, aerodynamics and healthcare systems design.
Title: Healthcare Systems Design of Intelligent Testing Centers: Latest Technologies to Battle Pandemics such as Covid-19
Author: Mushiri,Moyo
ISBN: 9780323994439
Binding:
Publisher: Elsevier Science & Technology
Publication Date: 2023-01-25
Number of Pages: 250
Weight: 0.3701 kg
