Nginx Training Course

The primary goal of this training is to clarify the nature of 5G networks and their influence on smart technologies. We will explore both the benefits and drawbacks of the synergy between 5G and the Internet of Things (IoT), while outlining the developmental trajectory of a network ecosystem designed from the outset 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 either online or onsite, is designed for advanced participants seeking to comprehend and exploit the emerging synergy between 6G technologies and IoT applications.

Upon completing this course, learners will be able to:

• Articulate the fundamental technical concepts underlying 6G.
• Evaluate how 6G will transform the communication protocols and architecture of IoT devices.
• Analyze 6G-enabled IoT use cases across various industries.
• Develop strategies for incorporating 6G capabilities into current 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.

Dive deeper into the innovative domain of edge computing with this advanced course. Explore complex architectures and tackle integration challenges, preparing to fully leverage the potential of edge computing across diverse business environments. Gain expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that address specific industry requirements.

Technological advancements and the exponential growth of data are reshaping operational practices across numerous sectors, including the public sector. Government data generation and digital archiving are accelerating, driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information becomes more voluminous and complex, the management, processing, storage, security, and retention of this data grow increasingly intricate. New tools for capture, search, discovery, and analysis are enabling organizations to derive 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 data to fulfill mission requirements and serve the public more effectively. As government leaders work to evolve into data-driven organizations, they are establishing the foundation to correlate dependencies among events, personnel, processes, and information.

High-value government solutions will emerge from the integration of several disruptive technologies:

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

Big Data represents an intelligent industry solution that empowers government entities to make better decisions by acting on patterns identified through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these outcomes requires more than simply accumulating massive amounts of data. As Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy noted in a post on the OSTP Blog, "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."

The White House facilitated agency access to these technologies by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to maximize the potential of the Big Data explosion and the tools required to analyze it.

The challenges posed by Big Data are nearly as formidable as its potential is promising. Efficient data storage remains a primary challenge. With budgets often constrained, agencies must minimize storage costs per megabyte while ensuring data remains easily accessible for users to retrieve as needed. Backing up massive data volumes further complicates this task.

Effective data analysis presents another significant challenge. Many agencies utilize commercial tools to sift through vast data sets, identifying trends that enhance operational efficiency. (A recent MeriTalk study indicated that federal IT executives believe Big Data could help agencies save over $500 billion while meeting mission objectives).

Custom-developed Big Data tools are also enabling agencies to meet their analytical needs. For instance, the Oak Ridge National Laboratory’s Computational Data Analytics Group 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 matching job candidates with hiring managers by reviewing resumes.

This instructor-led, live training in Italy (online or onsite) is designed for IT professionals and business managers at an intermediate level who wish to understand how IoT and edge computing can enhance efficiency, enable real-time processing, and foster innovation across various industries.

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

• Grasp the core principles of IoT and edge computing and their significance in digital transformation.
• Recognize specific use cases for IoT and edge computing within manufacturing, logistics, and energy industries.
• Distinguish between edge and cloud computing architectures and their respective deployment contexts.
• Deploy edge computing solutions to support predictive maintenance and real-time decision-making.

Combine the transformative power of AI with the agility of edge computing in this comprehensive course. Learn to deploy AI models directly on edge devices, from understanding CNN architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills to optimize AI performance for real-time processing and decision-making at the edge.

This instructor-led, live training in Italy (online or onsite) is designed for intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI to enhance 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 specific applications in IoT contexts.
• Set up and configure Edge AI environments tailored for IoT devices.
• Create and deploy AI models on edge devices for IoT solutions.
• Implement real-time data processing and decision-making mechanisms within IoT systems.
• Integrate Edge AI capabilities with diverse IoT protocols and platforms.
• Address ethical considerations and adhere to best practices for Edge AI in IoT.

This instructor-led, live training in Italy (online or onsite) is designed for product managers and developers aiming to decentralize data management for enhanced performance, utilizing smart devices located on the source network.

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

• Grasp the fundamental concepts and benefits of Edge Computing.
• Recognize specific use cases and scenarios where Edge Computing is applicable.
• Design and implement Edge Computing solutions to accelerate data processing and lower operational costs.

Establish a solid foundation in designing and managing resilient edge computing infrastructure. Gain insights into open hybrid cloud infrastructures, managing workloads across diverse cloud platforms, and ensuring flexibility and redundancy. This training provides essential knowledge for creating a scalable and secure infrastructure that supports the dynamic requirements of modern applications through edge computing.

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

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

Upon completing this training, participants will be capable of:

• Comprehending the architecture and components of embedded systems.
• Writing and compiling C code to facilitate interaction with embedded hardware.
• Utilizing microcontroller peripherals, including timers and ADCs.
• Understanding the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical applications.
• Hands-on implementation within a live laboratory environment.

Customization Options

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

This instructor-led, live training in Italy (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 objects 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 availability and advantages in low-level programming.

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

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

• Install and configure NetBeans for programming IoT systems with C
• Understand the fundamentals of IoT architecture
• Learn the benefits of using C in programming IoT systems
• Build, test, deploy, and troubleshoot an IoT system using C

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) constitutes a network infrastructure that wirelessly links physical objects with software applications. This connection enables mutual communication and data exchange through network communications, cloud computing, and data capture mechanisms. Java, recognized as a versatile language known for its "write once, run anywhere" capability, is a preferred choice for IoT development due to its portability and efficiency.

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

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

• Installing and configuring tools and frameworks, such as the Eclipse Open IoT Stack, to develop IoT systems in Java
• Gaining a solid understanding of IoT architecture fundamentals
• Utilizing the Eclipse Open IoT Stack for Java to connect and manage devices within an IoT solution
• Constructing, testing, and deploying IoT systems using Java

Target Audience

• Developers
• Engineers

Course Format

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

Note

• For customized training requests related to this course, please contact us to make arrangements.

Connected devices are disrupting many industries, and the power utility sector is no exception. Power utility companies currently face four primary challenges driven by the growth of the Internet of Things (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 provided by machine and controller vendors.
2. As the cost of solar and wind power microgrids continues to decline, utility companies anticipate a drop in 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, and grid services for EV charging and peer-to-peer energy trading between homes, microgrids, and batteries. Facilitating these services requires smart metering, smart grids, and secure transactions enabled by Distributed Ledger Technology (DLT) like IOTA. Additionally, utilities are exploring opportunities to provide smart city services to municipal authorities.
3. For critical infrastructure such as dams, ICOLD (International Committee of Large Dams) mandates real-time Structural Health Monitoring (SHM) to detect impending dangers like collapses. This early warning system allows for the timely evacuation of people in affected areas.
4. A new and emerging revenue area is EV charging in parking facilities. A key question is how IoT can facilitate smart charging and smart parking solutions.

Over the past three years, IoT engineering has undergone massive changes, primarily driven by Microsoft, Google, and Amazon. These tech giants have invested billions of dollars into developing IoT platforms that are easier to manage and more secure. IoT edge computing has also gained significant momentum as the primary method for practical IoT implementation. Furthermore, 5G promises to transform the IoT business landscape, leading to unprecedented research funding. Consequently, it is essential for practicing engineers to understand the IoT platforms developed for major players like AWS, Google, and particularly Microsoft.

However, none of the aforementioned platforms offer a completely exhaustive or comprehensive solution for scalable IoT. Deploying smart metering to millions of homes, for instance, requires additional technologies for securing smart meters, radio networks, IoT management, and various other secured services. The strategy, pricing, and security of any IoT deployment must be optimal and acceptable. Given the breadth of interdisciplinary knowledge required, it is nearly impossible for any single company to assemble a team capable of meeting all these requirements alone.

This course makes 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.

Furthermore, with scalable deployments, managing IoT services for thousands of sensors and connections has emerged as a separate engineering discipline. This area, formerly known as managed IoT services, is experiencing rapid growth because the challenges of scalable IoT are significantly greater than merely building the systems. Key challenges include securing over-the-top firmware/software updates, managing sensor and system calibration, automating connection issue diagnosis, identifying root causes of API failures, and tracking the health of hardware and services in 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. It also provides a basic introduction to all elements of IoT: 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, and 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/Zwave, Bluetooth, ANT+. Guidance on 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. Overview of available M2M data acquisition platforms for IoT: AWS IoT, Azure IoT, Google IoT.
6. Security issues and solutions for IoT: A review of security across all technology stacks.
7. Enterprise IoT platforms: Microsoft Azure IoT suites, AWS IoT, Google IoT, Siemens MindSphere.
8. Smart Metering standards: Open Smart Grid Protocols (OSGP), ANSI C 2.18 Protocols, NIST Standard for HAN (Home Area Network), Home Plug 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 applications for critical infrastructure: Dams, Transformers, Sub-stations, and High Tension Wires.

This instructor-led live training in Italy (online or onsite) is aimed at developers and programmers who wish to install, configure, and manage the Kaa platform to build IoT applications.

By the end of this training, participants will be able to build, develop, manage, and implement IoT applications for smart devices and machines using Kaa.