IoT All-in-One Training Course

The primary goal of this training is to clarify what 5G networks are and how they impact smart technologies. We aim to demonstrate both the benefits and drawbacks of this technological synergy (5G/IoT) and explore the development trajectory of a network designed from the outset for the smart era.

6G represents the upcoming generation of wireless communication standards, poised to revolutionize IoT ecosystems by delivering ultra-fast connectivity, advanced sensing capabilities, and integrated AI.

This instructor-led live training, available both online and onsite, is designed for advanced participants seeking to understand and harness the emerging convergence of 6G technologies and IoT applications.

Upon completing this course, learners will be able to:

• Articulate the fundamental technical concepts underpinning 6G.
• Assess the impact of 6G on IoT device communication and architectural design.
• Evaluate 6G-enabled IoT use cases across various industries.
• Develop strategies for integrating 6G capabilities into existing IoT solutions.

Course Format

• Concept-driven lectures supplemented by expert-led discussions.
• Practical exercises designed to reinforce key engineering principles.
• Guided exploration of case studies and scenario analysis.

Customization Options

• For customized training aligned with your organization's technology roadmap, please contact us to arrange a session.

Technological advancements and the exponential growth of information are fundamentally reshaping business operations across numerous sectors, including the public sector. Government data generation and digital archiving volumes are surging, driven by the proliferation of mobile devices and applications, smart sensors and connected devices, cloud computing solutions, and citizen-facing digital portals. As digital information expands and becomes increasingly complex, the management, processing, storage, security, and disposition of that data become more intricate. Emerging tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector is at a critical juncture, recognizing information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured information to better serve citizens and meet mission objectives. As government leaders strive to evolve into data-driven organizations, they are establishing the foundation to correlate dependencies across events, personnel, processes, and information.

High-impact government solutions will emerge from integrating the most disruptive technologies:

• Mobile devices and applications
• Cloud services
• Social business technologies and networking
• Big Data and analytics

Big Data represents a transformative industry solution, empowering governments to make superior decisions by acting on patterns revealed through the analysis of vast volumes of data—both related and unrelated, structured and unstructured.

However, achieving this requires more than simply accumulating large amounts of data. "Making sense of these volumes of Big Data requires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information," noted Tom Kalil and Fen Zhao from the White House Office of Science and Technology Policy in a post on the OSTP Blog.

The White House took a significant step toward supporting agencies in finding these technologies by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to capitalize on the explosion of Big Data and develop the necessary tools to analyze it.

The challenges posed by Big Data are nearly as daunting as the promise it offers. Efficiently storing data is one such challenge. With budgets always under pressure, agencies must minimize the cost per megabyte of storage while ensuring data remains easily accessible so users can retrieve it whenever and however they need it. Backing up these massive data volumes further intensifies the challenge.

Effectively analyzing data is another major hurdle. Many agencies utilize commercial tools that enable them to sift through vast amounts of data, identifying trends that enhance operational efficiency. (A recent MeriTalk study revealed that federal IT executives believe Big Data could help agencies save over $500 billion while also meeting mission objectives.)

Custom-developed Big Data tools are also allowing agencies to meet their data analysis needs. For instance, the Computational Data Analytics Group at Oak Ridge National Laboratory has made its Piranha data analytics system available to other agencies. This system has helped medical researchers identify links that can alert doctors to aortic aneurysms before they occur. It is also used for routine tasks, such as sifting through resumes to match job candidates with hiring managers.

This instructor-led live training in Romania (online or onsite) targets intermediate-level IT professionals and business managers who want to understand how IoT and edge computing can drive efficiency, real-time processing, and innovation across different industries.

By the end of this training, participants will be able to:

• Understand the foundational concepts of IoT and edge computing and their role in digital transformation.
• Identify use cases for IoT and edge computing in manufacturing, logistics, and energy.
• Differentiate between edge and cloud computing architectures and deployment scenarios.
• Implement edge computing solutions for predictive maintenance and real-time decision-making.

This instructor-led, live training in Romania (online or onsite) is designed for intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.

Upon completion of this training, participants will be able to:

• Grasp the fundamentals of Edge AI and its role in IoT.
• Set up and configure Edge AI environments tailored for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making within IoT systems.
• Integrate Edge AI with various IoT protocols and platforms.
• Address ethical considerations and best practices in Edge AI for IoT.

This instructor-led, live training in Romania (online or onsite) targets product managers and developers aiming to utilize Edge Computing to decentralize data management for improved performance, capitalizing on smart devices at the network source.

Upon completion of this training, participants will be capable of:

• Comprehending the fundamental principles and benefits of Edge Computing.
• Recognizing specific use cases and examples suitable for Edge Computing implementation.
• Designing and constructing Edge Computing solutions to accelerate data processing and lower operational expenses.

Embedded systems are specialized computing devices engineered to execute specific tasks within broader systems. The Internet of Things (IoT) refers to a network of physical devices equipped with sensors and software that connect, communicate, and share data via the internet.

This instructor-led live training, available online or on-site, targets beginner-level technical professionals aiming to grasp and apply embedded systems and IoT principles using C and microcontroller architectures.

Upon completing this course, participants will be capable of:

• Comprehending the architecture and components of embedded systems.
• Writing and compiling C code for direct embedded hardware interaction.
• Operating microcontroller peripherals, such as timers and ADCs.
• Understanding the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical activities.
• Hands-on implementation in a live-lab setting.

Customization Options

• To arrange a customized training session for this course, please get in touch with us.

This instructor-led, live training in Romania (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.

By the end of this training, participants will be able to:

• Understand the principles and benefits of Federated Learning in IoT and edge computing.
• Implement Federated Learning models on IoT devices for decentralized AI processing.
• Reduce latency and improve real-time decision-making in edge computing environments.
• Address challenges related to data privacy and network constraints in IoT systems.

The Internet of Things (IoT) represents a network infrastructure that wirelessly links physical devices and software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Azure provides a comprehensive suite of cloud services, including an IoT Suite with preconfigured solutions designed to help developers accelerate the creation of IoT projects.

In this instructor-led live training, participants will learn how to develop IoT applications using Azure.

Upon completing this training, participants will be able to:

• Grasp the fundamentals of IoT architecture
• Install and configure the Azure IoT Suite
• Understand the advantages of leveraging Azure for IoT system programming
• Implement various Azure IoT services (IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, IoT Device Management)
• Build, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

Format of the course

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• To request customized training for this course, please contact us to arrange.

The Internet of Things (IoT) represents a network infrastructure that wirelessly links physical objects with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture mechanisms. C is a general-purpose programming language highly recommended for IoT development due to its widespread availability and advantages in low-level programming.

In this instructor-led live training session, participants will acquire the skills necessary to program IoT solutions using C.

Upon completing this training, participants will be capable of:

• Installing and configuring NetBeans for IoT system development in C
• Grasping the core principles of IoT architecture
• Appreciating the advantages of utilizing C for programming IoT systems
• Constructing, testing, deploying, and troubleshooting an IoT system using C

Audience

• Developers
• Engineers

Format of the course

• A blend of lectures, discussions, exercises, and intensive hands-on practice

Note

• To request customized training for this course, please contact us to arrange.

Unlike many other technologies, IoT is significantly more complex, encompassing almost every branch of core engineering: Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. For each of its engineering layers, there are critical aspects of economics, standards, regulations, and the evolving state of the art. This course offers, for the first time, a modest yet comprehensive overview of all these critical aspects of IoT engineering.

Summary

An advanced training program covering the current state of the art in the Internet of Things.

It crosses multiple technology domains to develop awareness of an IoT system, its components, and how it can help businesses and organizations.

Includes live demos of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases around connected devices & things.

Target Audience

Managers responsible for business and operational processes within their respective organizations who want to know how to harness IoT to make their systems and processes more efficient.

Entrepreneurs and Investors who are looking to build new ventures and want to develop a better understanding of the IoT technology landscape to see how they can leverage it in an effective manner.

Estimates for the Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.

In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet.

However, the underlying technologies of IoT are nothing new as M2M communication existed since the birth of the Internet. However, what changed in the last couple of years is the emergence of a number of inexpensive wireless technologies added by the overwhelming adoption of smartphones and tablets in every home. Explosive growth of mobile devices led to present demand of IoT.

Due to unbounded opportunities in IoT business, a large number of small and medium-sized entrepreneurs jumped on the bandwagon of the IoT gold rush. Also due to the emergence of open source electronics and IoT platforms, the cost of development of an IoT system and further managing its sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their device with the Internet or a mobile app.

This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business.

Course Objective

The main objective of the course is to introduce emerging technological options, platforms, and case studies of IoT implementation in home & city automation (smart homes and cities), Industrial Internet, healthcare, Govt., Mobile Cellular, and other areas.

Basic introduction of all the elements of IoT: Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics, and Total control plane.

M2M Wireless protocols for IoT: WiFi, Zigbee/Zwave, Bluetooth, ANT+: When and where to use which one?

Mobile/Desktop/Web app for registration, data acquisition, and control – Available M2M data acquisition platforms for IoT – Xively, Omega, and NovoTech, etc.

Security issues and security solutions for IoT.

Open source/commercial electronics platforms for IoT: Raspberry Pi, Arduino, Arm Mbed LPC, etc.

Open source/commercial enterprise cloud platforms for AWS-IoT apps, Azure-IoT, Watson-IoT cloud, in addition to other minor IoT clouds.

Studies of the business and technology of some of the common IoT devices like Home automation, Smoke alarm, vehicles, military, home health, etc.

The Internet of Things (IoT) refers to a network infrastructure that wirelessly links physical objects with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. As a general-purpose language known for its "write once, run anywhere" philosophy, Java is highly recommended for IoT development due to its efficiency and portability.

In this instructor-led live training, participants will learn how to program IoT solutions using Java.

Upon completion of this training, participants will be able to:

• Install and configure tools and frameworks (such as the Eclipse Open IoT Stack) for programming IoT systems with Java
• Grasp the fundamentals of IoT architecture
• Utilize the Eclipse Open IoT Stack for Java to connect and manage devices within an IoT solution
• Build, test, and deploy an IoT system using Java

Audience

• Developers
• Engineers

Course Format

• A mix of lectures, discussions, exercises, and extensive hands-on practice

Note

• To request a customized training session for this course, please contact us to arrange.

Unlike many other technologies, IoT is significantly more complex, spanning nearly every branch of core engineering—including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. For each engineering layer, there are economic considerations, standards, regulations, and an evolving state of the art. This course offers a comprehensive overview of these critical IoT engineering aspects, marking the first time such a holistic approach has been presented in this format.

For manufacturing professionals, the most critical aspect is understanding advancements in the Industrial Internet of Things. Key areas include predictive and preventative maintenance, condition-based machine monitoring, production and energy optimization, supply-chain efficiency, and maximizing the uptime of manufacturing utilities.

Summary

• An advanced training program covering the current state of the art in Internet of Things technologies within Smart Factories.
• A live demonstration of model Industrial IoT (IIoT) applications designed for smart factories.

Target Audience

Duration 3 Days ( 8 hours / day)

Estimates for the Internet of Things (IoT) market value are substantial, as IoT is defined as an integrated and diffused layer of devices, sensors, and computing power that overlays consumer, business-to-business, and government industries. The number of connections is growing rapidly: from 1.9 billion devices today to an expected 9 billion by 2018. In that year, IoT devices will roughly equal the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer space, many products and services have already integrated IoT, including kitchen and home appliances, parking systems, RFID, lighting, heating products, and numerous applications within the Industrial Internet.

However, the underlying technologies of IoT are not entirely new, as Machine-to-Machine (M2M) communication has existed since the dawn of the Internet. What has changed in recent years is the emergence of numerous inexpensive wireless technologies, driven by the widespread adoption of smartphones and tablets in households. This explosive growth in mobile devices has created the current demand for IoT.

Industrial IoT (IIoT) has been widely used in manufacturing since 2014, leading to a significant number of IIoT innovations. This course will introduce all important aspects of these innovations in the IIoT field.

This training is intended for a technology and business review of this emerging industry, helping IoT enthusiasts and entrepreneurs grasp the basics of IoT technology and business models.

Course Objective

The main objective of the course is to introduce emerging technological options, platforms, and case studies of IoT implementation in smart factories for the manufacturing sector.

1. Studies of business and technology of some of the common IIoT platform like Siemens MindSphere and Azure IoT.
2. Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT, Mindsphere IIoT cloud in addition to other minor IoT clouds
3. Open source/commercial electronics platform for IoT-Raspberry Pi, Arduino , ArmMbedLPC etc
4. Security issues and security solutions for IIoT
5. Mobile/Desktop/Web app- for registration, data acquisition and control –
6. M2M Wireless protocols for IoT- WiFi, LoPan, BLE, Ethernet, Ethercat, PLC : When and where to use which one?
7. Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and Total control plane

Connected devices are transforming numerous industries, with the power utility sector being no exception. Power utility companies currently face four primary challenges arising from the expansion of IoT:

1. Vendors are increasingly connecting machines, controllers, HMIs, and SCADA systems to the cloud, promising enhanced analytics and insights for predictive and preventative maintenance. However, strict quarantine policies for critical assets prevent power companies from fully utilizing these IoT features offered by machine and controller vendors.
2. As the cost of solar and wind power microgrids continues to decline, utility companies face shrinking revenues from traditional power generation. To offset this loss, companies must aggressively pursue new revenue streams, such as Energy Management as a Service for homes, Energy Storage as a Service, grid services for EV charging, and grid services for peer-to-peer (P2P) energy trading between homes, microgrids, and batteries. These initiatives require smart metering, smart grids, and secure transactions facilitated by Distributed Ledger Technology (DLT) like IOTA. Additionally, utilities are exploring the provision of smart city services to municipal authorities.
3. For critical infrastructure such as dams, ICOLD (International Committee on Large Dams) mandates real-time Structural Health Monitoring (SHM). This allows for early warning of potential collapses in dams, rocks, or tunnels, enabling the evacuation of people in affected areas.
4. A new and emerging revenue source is EV charging in parking facilities. The course will explore how IoT can enable smart charging and smart parking solutions.

Over the past three years, IoT engineering has undergone massive changes, driven primarily by tech giants Microsoft, Google, and Amazon. These companies have invested billions in developing IoT platforms that are easier to manage and secure. Furthermore, IoT edge computing has gained significant momentum as a practical means of implementing IoT. The advent of 5G promises to further transform the IoT business landscape, leading to unprecedented investment in IoT research. Consequently, it is essential for practicing engineers to understand IoT platforms developed by major players like AWS, Google, and especially Microsoft.

However, none of these platforms offer a comprehensive, scalable solution out of the box. Deploying smart metering to millions of homes requires additional technologies for securing smart meters, radio networks, IoT management tools, and other secured services. The strategy, pricing, and security of any IoT deployment must be optimized and acceptable. Given the interdisciplinary knowledge required, it is challenging for any company to assemble a team capable of meeting all these requirements.

This course is a modest attempt to educate key decision-makers, developers, and security experts on the challenges, risks, and practical methods for deploying IoT in next-generation power utility businesses.

Additionally, scalable deployment has made managing IoT services for thousands of sensors and connections a distinct field of engineering research. This area, formally known as managed IoT services, is experiencing rapid growth because the challenges of scalable IoT are far greater than building it. These challenges include securing over-the-top firmware/software updates, managing sensor and system calibration, auto-diagnosing connection issues, identifying root causes of API failures, and tracking the hardware and service health of distributed systems.

Course Objectives

The main objective of the course is to introduce emerging technological options, platforms, and case studies of IoT implementation in power utility companies, including smart metering, smart cars, SHM (structural health monitoring), power quality diagnosis, and smart contracts. Participants will receive a basic introduction to all IoT elements, including mechanical aspects, electronics/sensor platforms, wireless and wireline protocols, mobile-to-electronics integration, mobile-to-enterprise integration, and data-analytics and control plane applications.

1. IoT Technology Stacks: Devices, Gateways, Edge, Edge Cloud, Public Cloud, IoT databases, Web & Mobile Applications for IoT, Centralized vs. Decentralized IoT.
2. IoT ecosystem for business, third-party device management, and risk management of the entire IoT ecosystem.
3. M2M Wireless protocols for IoT: WiFi, SigFox, LoRa, LPWAN, Zigbee/Z-Wave, Bluetooth, ANT+: When and where to use each.
4. Fundamentals of IoT Gateways: Risks, management, and ecosystem.
5. Mobile/Desktop/Web apps for registration, data acquisition, and control. Available M2M data acquisition platforms for IoT: AWS IoT, Azure IoT, Google IoT.
6. Security issues and solutions for IoT, including a review of security across all technology stacks.
7. Enterprise IoT platforms such as Microsoft Azure IoT suites, AWS IoT, Google IoT, Siemens MindSphere.
8. Smart Metering, Open Smart Grid Protocols (OSGP), ANSI C2.18 Protocols, NIST Standard for HAN (Home Area Network), HomePlug Powerline Alliance, Security Standard for Smart Meter: IEC 62056.
9. Distributed Ledger Technology (DLT) such as Blockchain, Hyperledger, and DAG (Directed Acyclic Graph) for smart contracts, P2P transactions, and smart car charging.
10. IoT for critical infrastructure like dams, transformers, substations, and high-tension wires.

In this instructor-led live training in Romania, participants will explore the various aspects of NB-IoT (also known as LTE Cat NB1) while developing and deploying a sample NB-IoT-based application.

Upon completion of this training, participants will be able to:

• Identify the different components of NB-IoT and understand how they integrate to form an ecosystem.
• Understand and explain the security features embedded within NB-IoT devices.
• Develop a simple application to track NB-IoT devices.