Nginx Training Course

This training aims to clarify the nature of 5G networks and their influence on smart technologies. We will explore the advantages and disadvantages of the relationship between 5G and IoT, while highlighting the developmental trajectory of a network designed from its inception for the smart world.

Positioned to revolutionize IoT ecosystems through ultra-fast connectivity, advanced sensing, and integrated AI capabilities, 6G represents the next-generation wireless communication standard.

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 core technical concepts underlying 6G.
• Evaluate how 6G will reshape IoT device communication and architecture.
• Assess 6G-enabled IoT use cases across various industries.
• Develop strategies for integrating 6G capabilities into existing IoT solutions.

Format of the Course

• Concept-focused lectures combined with expert discussion.
• Applied exercises designed to reinforce key engineering principles.
• Case-based exploration and scenario analysis in a guided environment.

Course Customization Options

• For tailored versions of this training aligned with your organizational technology roadmap, please contact us to arrange.

Technological advancements and the exponential growth of information are fundamentally reshaping business operations across various sectors, including government. The volume of government data generation and digital archiving is surging, driven by the rapid proliferation of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information becomes more expansive and complex, the management, processing, storage, security, and disposition of this data also become increasingly complicated. New tools for capturing, searching, discovering, and analyzing information are helping organizations extract valuable insights from unstructured data. The government sector is reaching a critical juncture, recognizing information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured information to better serve the public and meet mission requirements. As government leaders strive to evolve into data-driven organizations to successfully accomplish their missions, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions will emerge from a combination of the most disruptive technologies:

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

Big Data serves as an intelligent industry solution that enables governments to make better decisions by taking action based on patterns revealed through the analysis of large volumes of data—whether related or unrelated, structured or unstructured.

However, achieving these goals requires more than just accumulating massive quantities 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," Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy noted in a post on the OSTP Blog.

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

The challenges posed by Big Data are nearly as daunting as its promise is encouraging. Efficient data storage is one of these challenges. With budgets always tight, agencies must minimize the cost per megabyte of storage while keeping data easily accessible so users can retrieve it whenever and however they need it. The challenge is heightened by the need to back up massive quantities of data.

Effectively analyzing data is another major challenge. Many agencies employ commercial tools that allow them to sift through mountains of data, spotting trends that help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save more than $500 billion while also fulfilling mission objectives).

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

This instructor-led live training in South Korea (online or onsite) is designed for intermediate-level IT professionals and business managers who wish to understand the potential of IoT and edge computing for enabling efficiency, real-time processing, and innovation in various industries.

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

• Understand the principles of IoT and edge computing and their role in digital transformation.
• Identify use cases for IoT and edge computing in manufacturing, logistics, and energy sectors.
• 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 South Korea (online or onsite) is aimed at 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.

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

• Understand the fundamentals of Edge AI and its application in IoT.
• Set up and configure Edge AI environments for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making in 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 South Korea (online or onsite) targets product managers and developers who seek to utilize Edge Computing for decentralized data management, thereby enhancing performance through smart devices located at the network source.

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

• Grasp the fundamental concepts and benefits associated with Edge Computing.
• Recognize specific use cases and practical examples applicable to Edge Computing.
• Design and implement Edge Computing solutions that enable accelerated data processing and lower operational expenses.

Embedded systems are specialized computing platforms engineered to execute specific tasks within larger operational frameworks. The Internet of Things (IoT) refers to a vast network of physical devices integrated with sensors and software, enabling them to connect, communicate, and share data via the internet.

This instructor-led live training, available either online or on-site, is designed for technical professionals at the beginner level who aim to grasp and implement embedded systems and IoT principles using C programming and microcontroller architectures.

Upon completing this training, participants will be capable of:

• Comprehending the architecture and constituent parts of embedded systems.
• Writing and compiling C code to facilitate hardware interaction.
• Operating microcontroller peripherals, such as timers and Analog-to-Digital Converters (ADCs).
• Understanding the role of embedded systems within IoT architectures.

Course Format

• Engaging lectures and group discussions.
• Extensive exercises and practical application.
• Practical implementation within a live laboratory environment.

Customization Options

• For customized training arrangements, please reach out to us.

This instructor-led, live training in South Korea (online or onsite) is designed for intermediate-level professionals seeking to apply Federated Learning to optimize IoT and edge computing solutions.

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

• Grasp the core principles and advantages of Federated Learning within IoT and edge computing contexts.
• Deploy Federated Learning models on IoT devices to enable decentralized AI processing.
• Minimize latency and enhance real-time decision-making capabilities in edge computing environments.
• Address challenges related to data privacy and network constraints in IoT systems.

The Internet of Things (IoT) serves as 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. Azure provides a comprehensive suite of cloud services, including an IoT Suite that features 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.

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

• Understand the fundamentals of IoT architecture
• Install and configure Azure IoT Suite
• Learn the benefits of using Azure in programming IoT systems
• 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

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

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

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

During this instructor-led live training, participants will learn how to develop IoT solutions using C.

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

• Install and configure NetBeans to develop IoT systems with C
• Comprehend the fundamental principles of IoT architecture
• Appreciate the benefits of utilizing C for IoT system programming
• Build, test, deploy, and troubleshoot an IoT system using C

Audience

• Developers
• Engineers

Format of the course

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

Note

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

Unlike other technologies, the Internet of Things (IoT) is significantly more complex, spanning nearly every branch of core engineering, including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile domains. Each of these engineering layers involves critical considerations regarding economics, standards, regulations, and the evolving state of the art. This course offers a unique opportunity to comprehensively cover all these vital aspects of IoT engineering for the first time in a structured format.

Summary

An advanced training program designed to provide an in-depth look at the current state-of-the-art in the Internet of Things.

The curriculum cuts across multiple technology domains to develop a comprehensive awareness of IoT systems, their components, and how they can be leveraged to enhance business operations and organizational outcomes.

The program includes live demonstrations of model IoT applications, showcasing practical deployments across various industry verticals such as Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases involving connected devices.

Target Audience

Managers responsible for business and operational processes within their respective organizations who seek to understand how to harness IoT to improve system efficiency and operational workflows.

Entrepreneurs and Investors aiming to build new ventures and wishing to develop a deeper understanding of the IoT technology landscape to effectively leverage its potential.

The estimated value of the Internet of Things (IoT) market is substantial. By definition, IoT is an integrated and pervasive layer of devices, sensors, and computing power that overlays consumer, business-to-business, and government industries. The number of connections is growing rapidly: currently standing at 1.9 billion devices, with projections reaching 9 billion by 2018. By that year, this figure will be roughly equivalent to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer sector, numerous products and services have already transitioned into the IoT ecosystem, including kitchen and home appliances, parking systems, RFID solutions, lighting and heating products, and various applications within the Industrial Internet.

While the underlying technologies of IoT are not entirely new—given that Machine-to-Machine (M2M) communication has existed since the early days of the Internet—the landscape has shifted dramatically in recent years. This change is driven by the emergence of inexpensive wireless technologies and the widespread adoption of smartphones and tablets in households. The explosive growth in mobile device usage has directly fueled the current demand for IoT solutions.

Due to the unbounded business opportunities in the IoT space, a significant number of small and medium-sized entrepreneurs have joined the "IoT gold rush." Additionally, the rise of open-source electronics and IoT platforms has made the cost of developing and managing large-scale IoT production increasingly affordable. Existing electronic product owners are now facing pressure to integrate their devices with the Internet or mobile applications.

This training is designed to provide a technology and business review of this emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and business models.

Course Objective

The primary objective of this course is to introduce emerging technological options, platforms, and case studies of IoT implementation in areas such as home and city automation (smart homes and cities), the Industrial Internet, healthcare, government, mobile cellular networks, and other relevant fields.

The course provides a basic introduction to all elements of the IoT ecosystem, including Mechanical engineering, Electronics/sensor platforms, Wireless and wireline protocols, Mobile-to-Electronics integration, Mobile-to-enterprise integration, Data analytics, and the total control plane.

Key topics include M2M Wireless protocols for IoT—such as WiFi, Zigbee/Zwave, Bluetooth, and ANT+—and guidance on when and where to utilize each.

Discussions cover Mobile/Desktop/Web apps for registration, data acquisition, and control, along with available M2M data acquisition platforms for IoT, such as Xively, Omega, and NovoTech.

Security issues and corresponding solutions for IoT are thoroughly examined.

Open-source and commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and Arm Mbed LPC, are reviewed.

The course also covers open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure IoT, Watson IoT, and other minor IoT cloud services.

Case studies of the business and technology behind common IoT devices, such as home automation systems, smoke alarms, vehicles, military applications, and home health monitoring, are included.

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

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

By the end 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
• Understand the fundamentals of IoT architecture
• Use the Eclipse Open IoT Stack for Java to connect and manage devices in an IoT solution
• Build, test, and deploy an IoT system using Java

Audience

• Developers
• Engineers

Format of the course

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

Note

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

IoT technology is distinct in its complexity, spanning nearly every engineering discipline including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each layer involves considerations of economics, standards, regulations, and technological evolution. This course uniquely addresses these critical aspects of IoT engineering.

For manufacturing professionals, understanding the advancements in Industrial IoT is crucial. Key areas include predictive and preventive 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 current state-of-the-art IoT technologies in Smart Factories.
• Bridges multiple technology domains to build awareness of IoT systems, their components, and their value to manufacturing managerial professionals.
• Includes live demonstrations of model IIoT applications for smart factories.

Target Audience

• Managers responsible for business and operational processes within their manufacturing organizations who wish to leverage IoT to enhance system and process efficiency.

Duration 3 Days (8 hours per day)

The market value of the Internet of Things (IoT) is substantial. By definition, IoT is an integrated and pervasive layer of devices, sensors, and computing power that overlays consumer, B2B, and government industries. The number of IoT connections is growing rapidly: from 1.9 billion devices currently to an estimated 9 billion by 2018, equating to the combined total of smartphones, smart TVs, tablets, wearables, and PCs.

In the consumer sector, many products and services have already adopted IoT, including kitchen and home appliances, parking systems, RFID, lighting, heating products, and various Industrial Internet applications.

While the underlying technologies of IoT are not entirely new—M2M communication has existed since the early days of the Internet—the recent years have seen a shift due to the proliferation of inexpensive wireless technologies and the widespread adoption of smartphones and tablets in homes. This explosive growth in mobile devices has driven the current demand for IoT solutions.

Industrial IoT (IIoT) has been widely utilized in manufacturing since 2014, leading to numerous innovations. This course will introduce all significant aspects of these IIoT innovations.

This training provides a technology and business review of this emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and business models.

Course Objective

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

1. Study business and technology aspects of common IIoT platforms such as Siemens MindSphere and Azure IoT.
2. Explore open-source and commercial enterprise cloud platforms for AWS-IoT, Azure-IoT, Watson-IoT, MindSphere IIoT, and other minor IoT clouds.
3. Examine open-source and commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and Arm Mbed LPC.
4. Address security issues and solutions for IIoT.
5. Utilize Mobile/Desktop/Web apps for registration, data acquisition, and control.
6. Understand M2M wireless protocols for IoT (WiFi, LoRa, BLE, Ethernet, EtherCAT, PLC) and determine appropriate use cases for each.
7. Gain a basic introduction to all IoT elements: Mechanical systems, Electronics/sensor platforms, Wireless and wireline protocols, Mobile-to-Electronics integration, Mobile-to-enterprise integration, Data analytics, and the total control plane.

Connected devices are disrupting numerous industries, with power utilities being no exception. Utility companies currently face four primary challenges driven by the growth 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 governing 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-powered microgrids continues to drop, utility companies will likely experience declining revenue from traditional power generation. To offset this loss, companies must aggressively pursue new revenue streams, such as Home Energy Management as a Service, Energy Storage as a Service, grid services for EV charging, and grid services facilitating P2P energy trading between homes, between homes and microgrids, between microgrids, between microgrids and batteries, and between homes and batteries. These initiatives require smart metering, smart grids, and secure transactions enabled by distributed ledger technology (DLT) such as IOTA. Additionally, utilities are exploring the provision of smart city services to municipal authorities.
3. For critical infrastructure like dams, ICOLD (International Committee on Large Dams) mandates real-time Structural Health Monitoring (SHM). This allows for the early detection of impending collapse risks in dams, rocks, or tunnels, ensuring timely evacuation of affected populations.
4. Another emerging revenue opportunity lies in EV charging within parking facilities. This module explores how IoT can facilitate smart charging and smart parking solutions.

Over the past three years, IoT engineering has undergone massive transformations, primarily driven by Microsoft, Google, and Amazon. These tech giants have invested billions of dollars to develop IoT platforms that are easier to manage and more secure. Furthermore, IoT edge computing has gained significant momentum in both research and deployment as the primary method for practical IoT implementation. With 5G promising to revolutionize the IoT business landscape, there is an unprecedented surge in research funding across IoT. Consequently, for any practicing engineer, it is essential to understand the IoT platforms developed for major players like AWS, Google, and especially Microsoft.

However, none of the aforementioned platforms offer an exhaustive or completely comprehensive solution for scalable IoT. For instance, deploying smart metering to millions of homes requires additional technologies to secure the smart meters, radio networks, IoT management technology, and many other secured services. The strategy, pricing, and security of any IoT deployment must be optimal and acceptable. Given the vast interdisciplinary knowledge required, it is nearly impossible for any single company to assemble a team that meets all requirements alone.

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

Additionally, as IoT deployments scale, managing IoT services for thousands of sensors and connections has emerged as a distinct engineering discipline. This area, formerly known as managed IoT services, is experiencing rapid growth because the challenges of scalable IoT management are far greater than the initial build. 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 health of hardware and services in distributed systems.

Course Objectives

The main objective of this 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: mechanical components, electronics/sensor platforms, wireless and wireline protocols, mobile-to-electronics integration, mobile-to-enterprise integration, 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: Review of security across all technology stacks.
7. Enterprise IoT platforms such as Microsoft Azure IoT suites, AWS IoT, Google IoT, and Siemens MindSphere.
8. Smart Metering: Open Smart Grid Protocols (OSGP), ANSI C12.18 Protocols, NIST Standard for HAN (Home Area Network), HomePlug Powerline Alliance, and Smart Meter Security Standard - 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 applications for critical infrastructure like Dams, Transformers, Sub-stations, and High Tension Wires.

In this instructor-led live training in South Korea, 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.

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

• Identify the different components of NB-IoT and how they fit together to form an ecosystem.
• Understand and explain the security features built into NB-IoT devices.
• Develop a simple application to track NB-IoT devices.