Title: Application of Artificial Intelligence, to Improve the Its Concept, (intelligent transport systems). A Specific Study in the City of Campinas, In the Search of a Smart City

Abstract:  The fertility rate in the country, Brazil, fell from 6.16 children per woman to just 1.57 children in just over seven decades, from 1940 to 2014. In contrast, the population's life expectancy increased by 41.7 years in just over a century. In 1900, life expectancy was 33.7 years, making a significant leap in just over 11 decades, reaching 75.4 years in 2014. (AGÊNCIA BRASIL, 2016)

According to the UN (United Nations Organizations), currently, 55% of the world's population lives in urban areas and this proportion is expected to increase to 70% by 2050. In this context, cities would be having to assume more active roles in contributing to the national government initiatives to achieve the Sustainable Development Goals, SDGs. (ONU NEWS, 2019)

Technology has invaded different market segments and helped in the operation of different processes and tasks. There are different tools, systems, and software that meet the needs of daily work very efficiently, allowing the organization's professionals to become more strategic for the company in a super ergonomic work environment. (PROLABORE)

It is of fundamental importance to use data to make assertive decisions, thus prospecting a more qualified scenario for the benefits of all involved. (THE NEW YORK TIMES, 2012)

The present work has as its principle the realization of research with scope in the city of Campinas, located in the state of São Paulo. The objective is to analyze in an automated way the Ergonomic aspect of a public transport user in the municipality, specifically bus line No. 337, (Barão Geraldo Terminal / UNICAMP (State University of Campinas) chosen for its importance and demand, mainly used by professionals and students from Unicamp and Barão Geraldo. This line can be replicated to other lines in the city, other municipalities in the MRC (Metropolitan Region of Campinas), and even other municipalities in Brazil and abroad. It was chosen for its importance in the region, and for being an intelligent line. To achieve the objective of this work, a descriptive and comparative analysis method was used, taking into account the perspective of the city's public sector. With this, it is intended to take the reflection to the public administration of the city. To achieve smart public transport, it is necessary to achieve more sustainable, qualified, efficient, and comfortable development for its customers and third parties.

Prof. Gabriel Gomes De Oliveira
Researcher/Post Doctorate at UNICAMP
State University of Campinas, Brazil

Biography: He is currently a Researcher at the State University of Campinas (UNICAMP).

Develops research projects related to: Artificial Intelligence (AI), Big Data, Intelligent Information Systems (IIS), Internet of Things (IoT), Intelligent Transportation Systems (ITS), Smart Cities, and Sensors.

Reviewer of several Congresses and Journals, such as, (ACM, Elsevier, SAGE, Hindawi, IEEE, IET, Taylor Francis, Springer, and Wiley, among others) of national scope and mainly international, with more than 1200 Revisions, recognized by Publons or with Certificates issued. In addition to numerous publications in Conferences (ACM, IEEE, and Springer), and High Impact Factor Journals.

YP Chair IEEE Sensor and Systems Joint Council South Brazil (2022 to date).

Finally, Editor of Special Series of Scientific Journals, Editor of Springer Nature, (Smart Innovation, Systems, and Technologies), and IOP Publisher Invited to join as Associate Editor of Journals: IET Circuits, Devices & Systems and IET Wireless Sensor Systems (2022 -2025). And Academic Editor of the Journal PLOS ONE.

Title: Mathematical Structures in Signal Processing and Data Mining

Abstract:  Linear algebra, multivariate calculus, applied probability and statistics, and convex optimizations are well-established mathematical tools that have been used extensively in many signal processing and data mining applications. They led to developing a wide range of effective numerical algorithms for processing the longitudinal and other higher dimensional data that are organized in vectors and matrices. On the other hand, there are many other mathematical structures such as graphs, tensors, manifolds and so on, which can be used as structures for keeping numerical values. In this talk, I will introduce simplexes in graph signal processing, explain how tensors are different from high-dimensional matrices, define manifolds and topological spaces, and finish with a brief overview of category theory. All these topics can likely enable a new generation of more sophisticated signal processing techniques and methods.

Assoc. Prof. Pavel Loskot
ZJU-UIUC Institute, Zhejiang University, China

Biography: Pavel Loskot joined the ZJU-UIUC Institute, Haining, China, in January 2021 as Associate Professor after 14 years being the Senior Lecture at Swansea University in the UK. He obtained his PhD degree in Wireless Communications from the University of Alberta in Canada, and the MSc and BSc degrees in Radioelectronics and Biomedical Electronics, respectively, from the Czech Technical University of Prague in the Czech Republic. In the past 25 years, he was involved in numerous collaborative research and development projects, and also held a number of consultancy contracts with industry. Pavel Loskot is a Senior Member of the IEEE, a Fellow of the Higher Education Academy in the UK, and the Recognized Research Supervisor of the UK Council for Graduate Education. His current research interests focus on mathematical and probabilistic modeling, statistical signal processing and classical machine learning for multi-sensor data in biomedicine, computational molecular biology, and wireless communications.

Title: Development of Human-centered Service Robots based on AI Technologies

Abstract:  With the development of artificial intelligence technology, robots have started to be applied in industries, restaurants, hospitals, shops etc., for kinds of services like working or attracting customers. Most of the robot have their special tasks, and they can finish the tasks as well as avoid colliding with other pedestrians or objects. However, the human beings may have further requirements to the robot that they are asked to provide services considerately, both for the users and the other human beings around. Human-centered design for service robot has been noticed and developed. In this talk, human-centered designs for different kinds of service robots will be introduces including autonomous delivery robot, guide robot, hearing robot, cleaning robot etc., to show the different results and effectiveness of the service robots comparing with conventional ones. The considerate working ways can improve the social acceptances of service robots greatly and make the robot easier to be applied in human daily life. 

Asst. Prof. Bin Zhang
Kanagawa University, Japan

Biography: Bin Zhang: In 2011 graduated from Harbin Engineering University (Dept. of Automation), 2017 completed doctorate at University of Electro-Communications (Grad. School of Informatics and Eng.). Ph.D. of Engineering. Now assistant professor at Kanagawa University (Fac. of Eng., Dept. of Mech. Eng.). Research in intelligent robotics, signal processing, artificial intelligence and human interaction. Published more than 90 papers in these fields. Memberships: RSJ, JSME, IEEJ, IEICE, IEEE.

Title: To be added

Abstract:  to be added

Asst. Prof. Baha Ihnaini
Wenzhou-Kean University, China

Biography: Dr. Baha Ihnaini is an assistant professor at Wenzhou-Kean University, specializing in natural language processing (NLP) and sentiment analysis. He received his Ph.D. in Computer Science from Universiti Utara Malaysia (UUM). Dr. Ihnaini has a strong background in programming languages such as Python, Java, and C++. He is skilled in data mining tools like RapidMiner and has expertise in statistical analysis and algorithm design. His research interests include artificial intelligence, machine learning, sentiment analysis, and text classification. Dr. Ihnaini has published several papers in reputable journals and actively contributes to the academic community through his editorial board memberships and participation in international conferences. He is a member of professional organizations such as the Association for Computing Machinery (ACM). With a passion for research and teaching, Dr. Baha Ihnaini aims to make significant contributions to the field of NLP and advance our understanding of natural language data.

Title: The Role of AI in Healthcare:- Hope v/s Hype

Abstract:  As advancements in artificial intelligence (AI) continue to permeate every facet of society, the healthcare industry stands on the precipice of a profound transformation. In this keynote address, we delve into the delicate balance between hope and hype surrounding AI's integration into healthcare. We examine the tangible breakthroughs that AI has enabled, from personalized treatment plans to predictive analytics, while also scrutinizing the exaggerated expectations and ethical considerations that accompany its implementation. Through insightful analysis and real-world examples, we navigate the intricate landscape of AI in healthcare, offering valuable perspectives for stakeholders, practitioners, and policymakers alike. Join us as we explore the promise and pitfalls of AI, seeking to harness its full potential in advancing the delivery of quality care while mitigating the risks of overestimation and disillusionment.

Asst. Prof. Azhar Imran Mudasir
Air University, Islamabad, Pakistan

Biography: Dr. Azhar Imran Mudasir is an Assistant Professor at the Department of Creative Technologies, Faculty of Computing & Artificial Intelligence, Air University, Islamabad, Pakistan. He has completed his doctoral degree in Software Engineering from the Beijing University of Technology, China, and his master's degree in Computer Science from the University of Sargodha, Pakistan. He worked as a Senior Lecturer at the Department of Computer Science, University of Sargodha, Pakistan, from 2012 to 2017. He is a renowned expert in Image Processing, Healthcare Informatics, and Social Media Analysis. He is a regular member of IEEE and has contributed with 60+ research articles in well-reputed international journals and conferences. He is the editorial member and reviewer of various journals, including IEEE Access, MDPI Cancers, Applied Sciences, Mathematics, Springer Visual Computer, Talyor and Francis: Biomedical Imaging and Visualization, Multimedia Media Tools & Applications, IGI Global and Journal of Imaging, etc. Dr. Azhar has over 12 years of national and international academic experience as a Full-Time Faculty, teaching Software Engineering and core computing courses. Dr. Azhar has delivered guest talks and conducted seminars and trainings at numerous national and international forums in the past. He has contributed to multiple international conferences in diverse roles (keynote speaker, technical/ committee member, registration, speaker, etc.). His research interests include Image Processing, Social Media Analysis, Medical Image Diagnosis, Machine Learning, and Data Mining. He aims to contribute to interdisciplinary research of computer science and human-related disciplines.