Fellow IEEE, Professor,
University of Waterloo, Canada
Abstract: This presentation will offer an overview of microgrids in isolated and impoverished communities around the world that provide local access to electrical energy, as well as Prof. Canizares’ group’s research on planning the integration of renewable energy sources (RES) in diesel-based remote microgrids in Canada. The results of a survey of Canadian remote microgrids will be presented, followed by a detailed description of the microgrid in Kasabonika Lake First Nation (KLFN), an Ojibwa native community in Northern Ontario, and the results of an exhaustive measuring campaign and associated main observations. A comprehensive planning framework for the integration of RES in these microgrids will then be described in some detail, and the results of applying it to KLFN and selected communities in Nunavut and the North West Canadian Territories will be presented and discussed, considering the use of variable speed diesel generators.
IEEE Life Fellow, IEEE TA Hall of Honor
Chair, IEEE Roadmaps
Chair, IEEE Data Based Strategy AdHoc
President, Technology Connexions, Inc.
Abstract: Technology innovations over the years are being used to create engineering solutions at a very rapid pace. This session will provide select examples of some exciting solutions using Wireless and Compute technologies, IoT, AI/ML and similar capabilities to create solutions in spaces such as Agriculture, Healthcare, Smart Lighting and Power Generation and Distribution, and many others. While these solutions are enhancing personal experience they are also creating challenges. As IEEE Technology Roadmaps bring together a bevy of international experts to chart out a mapping of continued evolution of the underlying basic technologies, they provide the groundwork for making these humanitarian solutions possible. Some examples of this connectivity between Technology Roadmaps and the humanitarian solutions will also be enumerated
Galgotia University, Noida
Abstract: Learning was considered as one of the best modes of teaching learning. After the pandemic, it became the need of an hour. Blended learning changed the traditional aspect of teaching learning innovations. New innovations and pedagogical initiatives have been defined under new normal and now shall be adopted as permanent modes of teaching learning. It has crossed all boundaries and old definitions and parameters, platforms. This special session proposal shall attract all the case studies which were experienced during or after the pandemic under blended learning.
Associate Professor & Head of Department (Computer Science), Usman Institute of Technology (UIT) Karachi, Sindh
Abstract: Professional development for any professionals, maybe for young professionals or mid-career professionals or retire or near retiring age helps develop new skills, stay-to-date on current trends, and advance in their careers.
Unfortunately, many professionals are not investing in their career development and do nothing to upgrade or improve their current skill set. They often lag with those who have been continuously learning new skills and improving themselves with different sets of skills and technologies. IEEE has been striving to provide such opportunities for its members and volunteers to learn and apply the new knowledge and skills that can help them in their job and further their careers. Any professional development skill is not only for just your upbringing, this also helps for your employer and society at large. IEEE is the largest professional organization of engineers and technologists and sets its mission and vision as “Advancing Technology for Humanity”. To improve the quality of life of marginalized communities worldwide through the design and development of technology-based solutions combined with the building of local capacity. IEEE has a unique role and acknowledges its responsibility towards addressing and lessening the challenges that face humanity through technological innovation and with the help and support of their dedicated volunteers.
Professor, Nordakademie University of Applied Sciences, Germany Chair, Germany Section
Abstract: Remote teaching in engineering study courses has become more and more necessary since the start of the COVID- 19 pandemic. Many classes have to be given online, and while more theoretical subjects can more or less easily be adapted to a pure online version, especially engineering courses are hardto replace by virtual classrooms. As most engineering students will at some time be employed in industry, only teaching virtual courses lacks building up a gut feeling for the technical devices and thus leads to required additional training and diminished value of the education. This paper gives an overview on protocols and systems for remote laboratories as well as a presentation of an example experimental setup, namely a hardware model of a sophisticated elevator having two cabins in one shaft.
University of Bologna (Italy), IEEE Director 2022-2023, IEEE Computer Society President 2019
Abstract: Highly Autonomous Intelligent Systems are increasingly adopted in alarge variety of application fields, and the trend is towards trying to makethem more and more autonomous. They are complex systems, that operate in closecollaboration with human beings and/or the health of human beings may depend onthem. Consequently, their safety, reliability and security must be guaranteed,despite the possible occurrence of hazardous conditions affecting theelectronics implementing them during their in-field operation. Possible risksfor safety, reliability and security of highly autonomous intelligent systemswill be discussed, as well as possible solutions to enable increasing theirautonomy level for the benefit of humanity.
LSM IEEE, Chair,LMAG, Hyderabad Section
Abstract: Coronavirus 2019 (COVID-19) emerged in early December 2019, caused severe respiratory syndrome. While WHO declared the outbreak as a global pandemic on March 11, 2020. Number of people were hospitalized and several deaths occurred. This led to a massive strain on the healthcare systems worldwide. Due to this pandemic, the need for accelerating the digital transformation has been highlighted to provide the healthcare needs to people. Coronavirus 2019 (COVID-19) emerged in early December 2019, caused severe respiratory syndrome. While WHO declared the outbreak as a global pandemic on March 11, 2020. Number of people were hospitalized and several deaths occurred.
This led to a massive strain on the healthcare systems worldwide. Due to this pandemic, the need for accelerating the digital tRobots were used during 2020 COVID period such as Swab Robot for samplecollection, Maitra robot for patient screening, Sanbot for accessing blood oxygen levels, Humanoid robot for fetching supplies to patient rooms, UVD robot for sanitizing COVID 19 patient rooms in hospitals. This area is been continuously growing, assisting patience as well as doctors and nursing staff. Image processing and hyper-spectral or multi-spectral imaging techniques, greatly help diagnosing various eye diseases - like Glaucoma, Age related Macular Degeneration (AMD), Diabetic Retinopathy etc. Breast cancer cases have been raising globally from last few decades.
Early stage detection of breast cancer is very important to decrease the mortality rate. Image processing, thermal imaging, microwave sensors are playing important role in early detection of breast cancer. The Internet of medical things (IoMT) is another application for medical and health related areas, for creating a digitized healthcare systems, for treating patients from their homes and connecting available medical resources and healthcare services. The Internet of Medical Things (IoMT) designates the interconnection of smart sensors, smart devices, and advanced lightweight communication protocols in order to improve patients’ health. Since IoMT uses critical health systems, there are several challenges, particularly in terms of reliable diagnosis, patient safety, and security of patient’s health history has been highlighted to provide the healthcare needs to people.
Vice President, Chiba University of Commerce, Research Fellow, The University of Tokyo
Abstract: Twitter is currently one of the most inﬂuential microblogging services on which users interact with messages. It is imperative to grasp the big picture of Twitter through analyzing its huge stream data.
In this study, we develop a new clustering method that automatically discovers people’s perspectives from large-scale Twitter data. Our method is based on the original technique - Data Polishing - that is one of the graph clustering techniques. We evaluate the computational efficacy of the proposed method and demonstrate its systematic improvement in scalability as the data volume increases. We also apply the proposed method to large-scale Twitter data (26 million tweets) about the COVID-19 Vaccination in Japan. The proposed method is able to structure topics and extract various reactions on tweets.