IEEE 6th World Forum on Internet of Things
5-9 April 2020 // New Orleans, Louisiana, USA

Tutorials

 

 Tutorial Submission Guidelines

 

Sunday, 5 April 2020 (4 hr)

TUT‐01: Internet of Things Systems: A Guided Tour with Interoperability Focus
TUT‐02: Dispersed Computing and IoT Data Marketplaces using Jupiter and I3
TUT‐03: Lifetime Extension Challenges and Techniques for Energy Harvesting‐Based IoT Networks
TUT‐04: Prototyping Mobile‐enabled Medical Devices using MIT App Inventor platform
TUT‐05: IoT for Smart Mobility

Sunday, 5 April 2020 (2 hr)

TUT‐06: AI‐STREAM Digital Transformation Challenge Event: The BIG Data vs Sparse Data Challenge
TUT‐07: Understanding IoT Security Risks and Resilience: From Networks to Supply Chain
TUT‐08: Challenges of IoT to Blockchain and other Distributed ledgers Models
TUT‐09: IoT enabled Optical Fibre Sensors for Healthcare Monitoring Applications
TUT‐10: Health Risk and Safety of 5G/IoT Services

 

TUT‐01: Internet of Things Systems: A Guided Tour with Interoperability Focus

Date: Sunday, 5 April 2020
Time: 9:30- 15:00
Room:
Camp Room

Presenters: 

Milan Milenkovic, IoTsense LLC, CA, USA

Milan Milenkovic is the founder of IoTsense LLC, an IoT technology development and strategy consultancy in the San Francisco Bay Area. As a principal engineer in Intel Labs and in Intel’s IoT Business Unit, he led a number of projects involving IoT system architecture and implementation, smart buildings and energy management, cloud and grid computing. Prior to Intel, he worked at IBM and in academia conducting research and leading prototype designs of a variety of emerging technology projects. Milan Milenkovic earned a M.Sc. degree in Computer Science from Georgia Institute of Technology and a Ph.D. in Electrical and Computer Engineering from the University of Massachusetts at Amherst. He has given invited talks at academic and industrial conferences and has authored a number of journal and conference papers, industry technical reports, standards, and holds U.S. and international patents. He is the author of the forthcoming book “Internet of Things: Concepts and System Design” (Springer). His prior books include two editions of a college text “Operating Systems: Concepts and Design” (McGraw-Hill) with several translations and international editions, a monograph on distributed database systems, and an IEEE tutorial on multimedia systems. He is a Fulbright Scholar, ACM Distinguished Engineer, and an IEEE Senior Member.

Abstract: This tutorial provides an overview of IoT systems and interoperability. It describes the key aspects of IoT system design and architecture, including coverage and analysis of all major components –sensors, edge, fog, communications, cloud, data processing with analytics ML and AI, security and management. The emphasis is on providing a balanced treatment at roughly equal level of depth for all covered topics, based on the presenter’s forthcoming book “Internet of Things: Concepts and System Design” (Springer). The presentation approach is function and purpose driven in the sense that each component is described in terms of the role it fulfills in the system’s overall mission. That is to safely and securely collect real-world data, analyze, and act on the findings in a manner that impacts the physical world either by means of direct actuation or by optimization of control processes. An important focus of the tutorial is to highlight the importance of and the need for semantic interoperability in IoT systems. It describes how this requirement is different from the world-wide web and why it is necessary to enable big IoT data aggregations for meaningful insights and processing by ML and AI techniques. It also provides the ability to (re)use the collected data – arguably the most important asset of an IoT system – even when evolving the implementation or migrating to another platform. The structure of information and data models commonly used for the purpose are described and their salient features are identified. Several examples of IoT object definitions are provided from the evolving IoT standards – IPSO (LWM2M), OCF,Haystack – to illustrate their similarities and differences. Three different levels of pragmatic interoperability – intra-domain, inter-domain, and multi-domain – are introduced and ways for achieving them in practice are outlined.

TUT‐02: Dispersed Computing and IoT Data Marketplaces using Jupiter and I3

Date: Sunday, 5 April 2020
Time:
  9:30- 15:00
Room:
Jackson Room

Presenters: 

Gowri Sankar Ramachandran, Quynh Nguyen, Sampad Mohanty and Bhaskar Krishnamachari, Viterbi School of Engineering, University of Southern California, USA

Bhaskar Krishnamachari is Professor of Electrical and Computer Engineering at the Viterbi School of Engineering at the University of Southern California. He is Director of the USC Viterbi Center for Cyber-Physical Systems and the Internet of Things (CCI). He has expertise in the design and analysis of algorithms and software for the internet of things, connected vehicles, distributed computing, machine learning, and blockchain technologies. He has co-authored more than 300 papers, and 2 textbooks, collectively cited more than 25000 times (per Google Scholar). He has received several best paper awards including at MobiCom and IPSN, the NSF CAREER Award and the ASEE Terman Award. In 2011, he was listed in MIT technology review magazine’s TR-35 list of top 35 innovators under the age of 35, and in 2015 was named one of Popular Science magazine’s “Brilliant 10”. He has been the co-founder of the Intelligent IoT Integrator (I3) consortium at USC, an effort to develop an open-source real-time data marketplace for smart communities, and his research group at USC has led the development of the Jupiter dispersed computing scheduler, an open-source tool for deploying complex computations over networks of computers.

Gowri Sankar Ramachandran is a Senior Research Associate at Center for Cyber-Physical Systems and the Internet-of-Things (CCI) at University of Southern California. His research interests are focused on Internet-of-Things (IoT). In particular, he works on the design, implementation, and deployment of energy-efficient IoT applications. He has over five years of experience in middleware for the IoT with strong expertise in run-time reconfiguration and management of IoT applications across all layers of the stack. He is also specialized in low power wireless communication and was involved in the deployment of IoT applications and testbeds using technologies such as LoRa, IEEE-802.15.4e, and WiFi. Lately, Gowri is exploring blockchain technology and its application in IoT. In 2017, Gowri and his team have received the second prize in LoRa Alliance Global IoT Challenge for their deployment of smart medical fridges in Kikwit, DR Congo. And, he has also won best paper awards at WICSA/CompArch, BigMM, Mobiquitous, and AFRICATEK. Gowri is also involved in the USC’s Intelligent Internet-of-Things Integrator (I3) consortium, which is a real-time data marketplace for smart cities.

Quynh Nguyen is a postdoctoral researcher at autonomous networks research group at University of Southern California. Her research interest includes distributed computing, network optimization, and vehicular networks. Quynh has been involved in the development of Jupiter, which is a dispersed computing framework to deploy complex computations over dispersed compute platforms.

 

 

Sampad Mohanty is a PhD candidate at the autonomous networks research group at the University of Southern California. His research interests include Internet of Things, edge computing and machine learning.

 

 

 

Abstract: Cities around the world are starting to deploy IoT applications to monitor and control the environment remotely. Covering a city with IoT deployments involving a single organization is economically expensive while introducing management complexity. Data marketplaces are being developed to help cities create ecosystems around IoT where application developers can buy real-time data from device owners. Such a model minimizes the management complexity while allowing the application developers to consume data from multiple devices and neighborhoods easily. In this tutorial, we present I3, an IoT data marketplace which simplifies the process of posting, finding, and subscribing to IoT data products. While I3 simplifies data collection for application developers, they still need to process and analyze the data to make informed decisions. We also present Jupiter, a dispersed computing framework that allows application developers to process IoT data efficiently using AI/ML pipelines over hybrid edge and cloud platforms.

TUT‐03: Lifetime Extension Challenges and Techniques for Energy Harvesting‐Based IoT Networks

Date: Sunday, 5 April 2020
Time:
9:30- 15:00
Room:
Parish Room

Presenters: 

Johan Jair Estrada-Lopez, Computer Engineering Group, Faculty of Mathematics,

Autonomous University of Yucatan (UADY) Merida, Yucatan, Mexico.

Johan J. Estrada-López was born in the city of Mérida, México. In 2001, he received the B.Sc. degree in electrical engineering from the Mérida Institute of Technology, Mérida, where he was the highest GPA in the class. He then received the M.Sc. degree in electrical engineering from the Center of Advanced Research and Studies (CINVESTAV), Guadalajara, México, in 2003, and the Ph.D. degree in electrical engineering in 2019 at the Analog & Mixed-Signal Center, Texas A&M University, College Station, TX, USA. He has been a recipient of the National Council of Science and Technology Scholarship (2014 – 2019) from the government of México, and both the TI Jack Kilby Excellence and Silicon Labs Fellowship at Texas A&M University. From 2012 to 2013, he worked as a Design Engineer with Vidatronic Inc. In 2017, he was a Design Intern with the Power Delivery Group, Intel Corporation, Hillsboro, OR, USA. In 2019, he worked as a Postdoctoral Researcher at the Analog and Mixed-Signal Center, Texas A&M University. He is currently an Associate Professor of Electrical and Computer Engineering with the Autonomous University of Yucatán, in México. His current research interests include CMOS mixed-signal and analog circuit design for energy harvesting and power management in mobile and wearable applications, and embedded system design for Wireless Sensor Networks and Internet of Things applications in agriculture and smart cities.

Abstract: Many Internet of Things (IoT) applications consist of a large number of wireless sensor node swith limited hardware and stringent constraints in terms of energy storage capability. Therefore, to deploy a reliable IoT network with uninterrupted service requires the judicious application of several energy conservation and energy harvesting techniques that would help to extend battery life or if possible, enable a complete energy-autonomous (batteryless) operation. In this tutorial, a general, systematic and comprehensive survey of lifetime extension methods is presented, with a specific focus on the sensors and network layers of the IoT architecture. Within that context, a thorough discussion on dynamic power management (DPM) techniques at the hardware level will be provided, together with the design of multiple-input energy harvesting circuits and systems. Finally, the development of alternative/novel harvesting transducers for IoT-related applications will be presented. Examples from both the speaker’s research work and from state-of-the-art literature will be given.

TUT‐04: Prototyping Mobile‐enabled Medical Devices using MIT App Inventor platform

Date: Sunday, 5 April 2020
Time:
9:30- 15:00
Room:
Royal Room

Presenters: 

Sarvesh Karkhanis, Freelance Educator and Tech. Consultant, Thane, Maharashtra, India

Sarvesh is a Featured Inventor, Entrepreneur, Maker, Science Communicator, Robotics-IoT Educator and a Computer Scientist. His invention of a medical device having potential to save lives of pre-mature babies, was recently featured in the news. Sarvesh recently won an award at the MIT App Inventor Summit 2019 which was held at MIT Media Lab, for his project about Rapid-Prototyping of Medical Devices. He is also a Certified MIT Master Trainer in Educational Mobile Computing from 2019 cohort. Sarvesh has a decade long experience of teaching Robotics, IoT and other technology related topics to high school and college students, as well as to professionals. He has been working with various development platforms such as Arduino, Raspberry Pi, Microbit and Beaglebone. Sarvesh is also a contributor to the Arduino Project. Working with 3D Printers, he has also completed MIT’s on-campus summer certificate program in Additive Manufacturing. Human Centric Design, Design Thinking and Constructionism are some of his topics of interest. He chooses to emphasize on use-case driven teaching approach. Being a great admirer of Dr. Seymour Papert’s approaches about education, Sarvesh has been implementing Dr. Papert’s teaching techniques into his own technology teachings. In addition to being interested in technology, Sarvesh is involved in various Leadership activities. Sarvesh was a delegate at the United Nations COP XI Biodiversity conference where he presented his paper about use of Technology for Environment Education. He has participated in a number of ecological expeditions with renowned researchers and assisted them with technology needs.

Abstract: This tutorial is a jump start lesson on how medical researchers or product designers in the field of Healthcare can utilize the powerful MIT App Inventor platform for rapid-prototyping of IoT enabled Medical devices. This tutorial is conducted in the DIY format and would enable audience to learn linking and utilizing simple rapid-prototyping tools to create an actual Medical Device prototype. Though the audience are not required to, they are encouraged to bring the recommended inexpensive material from the provided Bill of Material for an enriching hands-on experience, through which they would build the prototype IoT Medical Device.

TUT‐05: IoT for Smart Mobility

Date: Sunday, 5 April 2020
Time:
  9:30- 15:00
Room:
Commerce Room

Presenters: 

Ana Aguiar, University of Porto, Instituto de Telecomunicações, Portugal

Abstract: Smarter mobility is expected to play a key role in the reduction of urban carbon footprint by changing the way people move. The Internet of Things can foster this change by supporting better transportation planning and by improving the mobility experience in more environmental friendly modes.This tutorial will discuss requirements, challenges, and solutions for both dimensions, distilled from 7years of experimental projects in the field of intelligent mobility in the city of Porto. Concretely, the tutorial will cover the challenges of building and using mobile crowd sensing to collect data for urban planning research, and show how it may be useful. It will showcase applications that leverage wireless systems and mobile Internet of Things on public and soft transportation to improve the mobility experience in these more environmental friendly modes. Several examples of real world performance characterization will be presented and discussed, identifying limitations of the solutions and improvement opportunities. Finally, it will showcase how pieces can be integrated in a large trans disciplinary use case: eco-routing for city-wide traffic distribution

TUT‐05: Solving IoT Business Problems Using AI and ML

Date: Sunday, 5 April 2020
Time:
  9:30- 15:00
Room:
Commerce Room

Presenters: 

Megan Smith Branch, CertNexus, NY, USA

Mark Szewczul, Independent Contractor and CertNexus Contributor, NY, USA

Megan Smith Branch is Chief Operating and Product Officer for CertNexus, a global emerging tech certification startup based in Rochester, NY. Megan oversees the development, delivery and product engagement of CertNexus’ emerging technology certification solutions in cybersecurity, IoT, AI and data science. Her key objective is to create, promote and maintain high stakes certifications within emerging technologies so that organizations can accelerate technology initiatives through the building and validation of knowledge and skills. Megan sits on the board of the California Technology Council, is a member of the IoT Talent Consortium and Cybersecurity Credentials Collaborative (C3), NICE Training and Certification Working Group.

 

Mark is a Principal IIoT Security Architect with over 20 years of experience mastering numerous aspects of hardware design, system integration, pentesting and SDLC. His passion entails implementing best practices of security, privacy and safety principles at all 7-layers and beyond. Mark is a Key Contributor as Security Research Volunteer in the IoT Working Group of the Cloud Security Alliance and is a contributor to CertNexus’ CIoTP, CIoTSP and CAIP certifications. He has his MSEE in Information Science and Systems from Texas A&M University. Mark also has 3 patents and has published and presented numerous times.

Abstract: IoT harvests a proliferation of data. Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This tutorial shows you how to identify business problems that can implement machine learning to drive solutions, follow an ML workflow to form the problem within ML, and select appropriate toolsets to use.

Abstract: IoT harvests a proliferation of data. Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This tutorial shows you how to identify business problems that can implement machine learning to drive solutions, follow an ML workflow to form the problem within ML, and select appropriate toolsets to use.

TUT‐06: AI‐STREAM Digital Transformation Challenge Event: The BIG Data vs Sparse Data Challenge

Date: Sunday, 5 April 2020
Time:
9:30 – 11- 30
Room:
Fulton Room

Presenters: 

Ahmed Hag ElSafi and Rami Zewail, Smart Empower Innovation Labs Inc., Edmonton, Alberta, Canada

Ahmed Hag Elsafi holds a BSc and a MSc of Electronics and Communications Engineering, Arab Academy for Science and Technology, 2002 and 2004 respectively. He has 15 years of research and industrial development experience in areas of embedded systems and machine learning, with over 10 year in the Oil & Gas industry. He has published more than eighteen papers in the areas of IOT security, biometrics, machine learning, and medical image processing. He is currently a co-founder and consultant at Smart Empower Innovation Labs Inc., a Canadian-based R&D consultancy specialized in fields of machine learning and embedded systems. Mr. Hag-ElSafi is a member the Smart City Alliance in Alberta, Canada and the Association of Professional Engineers and Geoscientists of Alberta (APEGA). He has also served as technical reviewer for Apress -Springer, NY,US.

Rami Zewail received a BSc. and MSc. In Electronics & Communications Engineering, Arab Academy for Science and Technology, Egypt, in 2002 and 2004 respectively. And a PhD degree in Electrical and Computer Engineering, University of Alberta, Canada, in 2010. He has over 15 years of academic and industrial R&D experience in areas of embedded computing, machine learning, and signal processing. Dr Zewail’s research experience spans different fields such as Energy industry, Computer vision, biomedical, BlockChain, and IoT. Dr. Zewail has over 12 years of R&D experience in Oil &Gas sector. He has contributed to the scientific community with a patent and over 20 publications in areas of embedded computing, machine learning, and statistical modeling. Currently, he is co-founder of Smart Empower Innovations Labs Inc., an R&D consultancy specialized in fields of embedded systems and machine learning. Dr. Zewail is a member of the Institute of Electrical and Electronics Engineers (IEEE), the Association of Professional Engineers & Geoscientists (APEGA), The Canadian Association for Artificial Intelligence. He also has served as a reviewer for the Journal of Electronics Imaging, Journal of Optical Engineering for the SPIE society, and Apress Media LLC-Springer.

Abstract: In the Era of BIG Data and Internet-Of-Things, there has been an ever-growing demand for efficient modeling and analyzing of high-resolution and large-scale volumes of data from wide variety of sources. Efficient Handling of BIG Data is an essential building block of digital transformation and Industry4.0 Initiatives. In response to these challenges, efficient data representation has been drawing much attention lately within the research community. Concepts of sparse representation and compressed Sensing are emerging techniques that have great potentials to meet challenges such as device power consumption, data redundancy, bandwidth, and data storage and transmission. In this hands-on tutorial,the speakers would present an overview of the role sparsity in machine learning with application to Industrial Internet-of-Things (IIoT). The tutorial event would also include hands-on demonstration on how Sparse data analytics can help overcome some of the challenges in BIG DATA. The tutorial will be concluded with the release of a digital transformation competition with the theme “BIG Data vs Sparse data” . The competition would be open to participants through AI-STREAM: A Data science competition platform dedicated to Digital Transformation and Industry 4.0 Challenges.

TUT‐07: Understanding IoT Security Risks and Resilience: From Networks to Supply Chain

Date: Sunday, 5 April 2020
Time:
9:30 – 11- 30
Room:
Canal Room

Presenters: 

Junaid Farooq and Quanyan Zhu, New York University, NY, USA

Junaid Farooq is a Ph.D. Candidate at the Department of Electrical & Computer Engineering, New York University (NYU) Tandon School of Engineering. His research interests are in the design of secure and resilient IoT-enabled smart infrastructure systems & networks. He received a B.S. degree in Electrical Engineering from the National University of Sciences & Technology (NUST) and the M.S. degree in Electrical Engineering from the King Abdullah University of Science & Technology (KAUST) in 2013 and 2015 respectively. He was then a researcher at the Qatar Mobility Innovations Center (QMIC) in Doha, Qatar. He is a recipient of several awards including the President’s Gold Medal from NUST, the King Abdullah Fellowship award from KAUST, the Ernst Weber Fellowship from NYU, and the Athanasios Papoulis award from NYU.

Quanyan Zhu is an associate professor in the Department of Electrical and Computer Engineering at New York University. He received the B. Eng. in Honors Electrical Engineering with distinction from McGill University in 2006, the M.A.Sc. from University of Toronto in 2008, and the Ph.D. from the University of Illinois at Urbana Champaign (UIUC) in 2013. From 2013- 2014, he was a postdoctoral research associate at the Department of Electrical Engineering, Princeton University. He is a recipient of many awards including NSF CAREER Award, NSERC Canada Graduate Scholarship (CGS), Mavis Future Faculty Fellowships, and NSERC Postdoctoral Fellowship (PDF). His current research interests include resilient and secure interdependent critical infrastructures, Internet of things, cyber-physical systems, machine learning, network optimization and control.

Abstract: The widespread adoption of the IoT is becoming indispensable in all industry verticals such as in energy, transportation, communications, emergency services, public administration, defense, etc., due to their burgeoning scale and complexity. However, the cyber-physical integration is also opening doors for malicious cyber activity to sabotage their performance and/or operation. Furthermore, the IoT is composed of various different interconnected components that may be designed, manufactured, and operated by different entities located in different parts of the world. This adds an additional threat vector relating to the supply chain of the IoT ecosystem with possible attacks from backdoor and stealthy channels. Since the incapacitation or destruction of infrastructure systems can have a debilitating effect on national security, economy, public health, and safety, it is imperative to understand risks in IoT systems and take necessary steps to mitigate them. This tutorial is aimed at identifying and categorizing the different types of security risks in IoT systems starting from the network layer to the supply chain layer. It will also provide an overview of the potential strategies that can be employed to avoid the possibility of large scale coordinated attacks from network entities or supply chain actors. Finally, an overview of the possible research directions relating to the security and resilience of IoT systems will be provided.

TUT‐08: Challenges of IoT to Blockchain and other Distributed ledgers Models

Date: Sunday, 5 April 2020
Time:
9:30 – 11- 30
Room:
Magazine Room

Presenters: 

Gustavo Giannattasio, IEEE Technology and Engineering Management TEMS Member at Large
2020, Comsoc Uruguay Chapter Chair, Uruguay

Abstract: With the pervasive presence of Blockchain solutions in the industry, a real challenge arises when trying to apply for IoT solutions. The fact that the Trilemma (Scalability, Decentralization and Security)cannot be solved simultaneously by Conventional Blockchain models. Reason includes the large amount of sensors , the centralized model of most cloud solutions, and MCU limitations on security by design on the sensor are a real challenge. Some initiatives include sharding, partitioning, multichain and other forks of Blockchain but that is not enough considering the need to get rid of Miners on order to process micro transactions typical of most sensors. Typical IOT sensors sends a reduced set of parameters like temperature, humidity, pollution parameters, parking positions etc that actually represent a small amount of data not attractive to the Miners to validate. It is similar to the restriction applied to micro transactions where small amount of money is to be secured by Blockchain Miners cannot be used for microtransactions for the same reason. Data transfer Delay is perhaps one of the most crucial issues when trying to apply Blockchain, and this issue is not tolerable for M2M data transactions like Autonomous vehicles,Industrial Internet of things applied to Industry 4.0 etc.

TUT‐09: IoT enabled Optical Fibre Sensors for Healthcare Monitoring Applications

Date: Sunday, 5 April 2020
Time:
13:00 – 15:00
Room:
Fulton Room

Presenters: 

Elfed Lewis, Optical Fibre Sensors Research Centre (OFSRC), Dept. of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland

Elfed Lewis graduated with BEng (Hons) in Electrical and Electronic Engineering from Liverpool University in 1978 and was awarded his PhD from the same institution in 1987.  He is Associate Professor and Director of the Optical Fibre Sensors Research Centre at University of Limerick, which he founded in 1996.  He is Fellow of Institute of Physics, IET and Senior member IEEE. He has authored and co-authored more than 160 journal papers and made in excess of 300 contributions to international conferences. He currently holds 9 patents on Optical Fibre Sensor Devices. In 2005 he was recipient of the University of Limerick Special Achievement in Research Award and was a Fulbright Scholar with CREOL (University of Central Florida) in 2008.  He was Distinguished Lecturer for IEEE Sensors Council for the period July 2013-June 2015 and General Co-Chair of the recent IEEE 2019 World Forum on IoT held at University of Limerick, Ireland

Abstract: Wireless enabled sensors for use in IoT have shown massive recent growth due to the growing demand for a well-established market in commercial body parameter measurement e.g. heartbeat, step counting etc. However, there exists a real need for IoT enabled devices for patient monitoring in the clinical environment. Some of these measurements are quite specialized and require the use of niche sensors e.g. in the presence of strong electromagnetic fields such as those encountered in proximity to magnetic Resonance Imaging or Computerized Tomography (CT) scanning machines. This tutorial is designed to provide fundamentals that underpin modern optical fiber based sensors and their use as IoT enabled. An example of a real functioning sensor will be provided to demonstrate the working principle sreferred to above via description of a portable 3-D Printed Plastic Optical Fiber Sensor for monitoring of breathing pattern and respiratory rate.

TUT‐10: Health Risk and Safety of 5G/IoT Services

Date: Sunday, 5 April 2020
Time:
13:00 – 15:00
Room:
Canal Room

Presenters: 

Riadh W. Y. Habash, School of Electrical Engg. and Computer Science, University Of Ottawa,
Ontario, Canada

Abstract: Many of today’s inventions, ranging from wireless communication networks to intelligent environment (buildings, cities, transportation), intelligent living (automotive and consumer products), and intelligent enterprise (health, utilities, retail, manufacturing, energy, construction, agriculture), are so important and advantageous that we wonder how we ever lived without them. These inventions have become an integral part of our life. Sure, they are useful; however, we need to know that they are safe!With enhanced connectivity and use security, the concept of “5G/IoT/AI” is becoming a public good that everyone will have access to and right to know about. It is essentially about life, health, and safety. With the proliferation of the IoT smart connected devices, study of the interaction mechanisms between nonionizing electromagnetic (EM) fields and human body is significant to give learners as well as society a deeper, more meaningful glimpse into the impact of EM fields on human health and safety. The content setting of this tutorial offers participants the chance to develop knowledge in a wide domain of subjects including EM theory and applications, dosimetry (macro and micro), safety standards and exposure assessments, observational and experimental evaluation studies, and risk science, with a goal to bring the research methodology closer to user experience reach.