Nginx Training Course

The aim of the training is to explain what the 5G network is and what impact it has on smart technologies. I want to show you both the advantages and disadvantages of these technological relationships (5G / IoT) and show you the directions of development of the network, which - from the very beginning - was dedicated to the smart world.

Positioned as the next generation of wireless standards, 6G is set to revolutionize IoT ecosystems by delivering ultra-fast connectivity, advanced sensing capabilities, and integrated AI.

This instructor-led live training, available online or onsite, targets advanced-level professionals seeking to understand and harness the emerging convergence of 6G technologies and IoT applications.

Upon completion, learners will be equipped to:

• Articulate the fundamental technical concepts underlying 6G.
• Assess how 6G will transform IoT device communication and architectural design.
• Evaluate IoT use cases enabled by 6G across various industries.
• Develop strategies for integrating 6G capabilities into current IoT solutions.

Course Format

• Concept-driven lectures combined with expert-led discussions.
• Practical exercises designed to reinforce core engineering principles.
• Guided case studies and scenario analysis.

Customization Options

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

Delve deeper into the innovative realm of edge computing with this advanced course. Explore sophisticated architectures and tackle integration challenges, preparing to leverage the full potential of edge computing in a variety of business environments. Gain expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that meet specific industry needs.

Technological advancements and the exponential growth of information are reshaping business operations across numerous sectors, including government. Government data creation and digital archiving are accelerating, driven by the proliferation of mobile devices and apps, 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 become increasingly challenging. New tools for capture, search, discovery, and analysis are enabling organizations to derive valuable insights from unstructured data. The government sector is at a critical juncture, recognizing information as a strategic asset. Governments must protect, leverage, and analyze both structured and unstructured information to better serve citizens and meet mission requirements. 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 are emerging from the integration of 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, enabling governments to make better decisions by acting on patterns revealed through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these goals requires more than just accumulating vast 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," wrote Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy 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 Big Data explosion 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 such challenge. With budgets always tight, agencies must minimize the cost per megabyte of storage and ensure data is easily accessible, allowing users to retrieve it when and how they need it. Backing up massive quantities of data further compounds this challenge.

Effective data analysis is another major hurdle. Many agencies utilize commercial tools to sift through vast amounts of data, identifying trends that improve operational efficiency. (A recent MeriTalk study found that federal IT executives believe Big Data could help agencies save over $500 billion while also fulfilling mission objectives.).

Custom-developed Big Data tools are also enabling agencies to meet their 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. 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 screening resumes to connect job candidates with hiring managers.

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

Upon completion 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.

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 Serbia (online or onsite) targets intermediate-level developers, system architects, and industry professionals eager to leverage Edge AI to boost IoT applications with intelligent data processing and analytics.

By the conclusion 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 Serbia (online or onsite) is designed for product managers and developers aiming to decentralize data management via Edge Computing to achieve faster performance, utilizing smart devices located within the source network.

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

• Understand the core concepts and advantages of Edge Computing.
• Identify use cases and examples where Edge Computing can be effectively applied.
• Design and build Edge Computing solutions for faster data processing and reduced operational costs.

Establish a solid foundation in designing and managing resilient edge computing infrastructure. Gain insights into open hybrid cloud setups, workload management across various clouds, and strategies for ensuring flexibility and redundancy. This training equips learners with the essential knowledge needed to build scalable, secure infrastructure capable of supporting the dynamic demands of modern applications through edge computing.

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

This instructor-led, live training (available online or onsite) is designed for technical beginners looking 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 core components of embedded systems.
• Writing and compiling C code to facilitate hardware interaction.
• Utilizing microcontroller peripherals, such as timers and Analog-to-Digital Converters (ADCs).
• Understanding the role of embedded systems within IoT architectures.

Course Format

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

Customization Options

• For a tailored training session, please contact us to arrange details.

This instructor-led, live training in Serbia (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:

• Comprehend the principles and advantages of Federated Learning in IoT and edge computing.
• Deploy Federated Learning models on IoT devices for decentralized AI processing.
• Minimize latency and enhance real-time decision-making capabilities in edge computing environments.
• Overcome challenges related to data privacy and network limitations in IoT systems.

Connected devices are disrupting numerous industries, with the power utility sector being no exception. Power utility companies are currently navigating four primary challenges arising from the proliferation 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 protecting critical assets prevent power companies from fully leveraging these new IoT features offered by machine and controller vendors.
2. As the costs of solar and wind power microgrids continue to decrease, utility companies face 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 P2P 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 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 early detection of potential collapses in dams, rock formations, or tunnels, enabling timely evacuation of affected populations.
4. Another emerging revenue opportunity is EV charging in parking facilities, raising the question of how IoT can facilitate smart charging and smart parking solutions.

Over the past three years, IoT engineering has undergone massive transformation, largely driven by Microsoft, Google, and Amazon. These tech giants have invested billions to develop IoT platforms that are easier to manage and more secure. Meanwhile, IoT edge computing has gained significant momentum in both research and deployment as the primary method for practical IoT implementation. The advent of 5G promises to further transform the IoT business landscape, leading to unprecedented investment in new areas of IoT research. Consequently, for any practicing engineer, understanding IoT platforms developed for major players like AWS, Google, and especially Microsoft is absolutely essential.

However, none of these platforms offer a fully comprehensive solution for scalable IoT. For instance, deploying smart meters to millions of homes requires additional technologies to secure the meters, radio networks, IoT management tools, and numerous other secured services. The strategy, pricing, and security of any IoT deployment must be optimal and acceptable. Given the interdisciplinary nature of this knowledge, it is nearly impossible for a single company to assemble a team capable of meeting all requirements.

This course aims 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, as IoT deployments scale, managing 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 greater than the initial implementation. Key challenges include securing over-the-top firmware/software updates, managing sensor and system calibration, auto-diagnosing connection issues, identifying the root cause of API failures, and tracking the hardware and service health of 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. It provides a basic introduction to all IoT elements—mechanical systems, electronics/sensor platforms, wireless and wireline protocols, mobile-to-electronics integration, mobile-to-enterprise integration, and data-analytics/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/Zwave, 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: A review of the security of 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 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 for critical infrastructure: Dams, Transformers, Sub-stations, High Tension Wires

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

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

This instructor-led, live training in Serbia (online or onsite) is aimed at advanced-level IoT developers and smart home enthusiasts who wish to automate IoT processes and create innovative solutions using n8n.

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

• Set up and configure n8n for IoT workflow automation.
• Integrate IoT devices and platforms using n8n nodes and connectors.
• Implement custom workflows to automate IoT tasks and processes.
• Use IoT protocols like MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimize IoT automation workflows.

The aim of this training is to clarify what constitutes Smart solutions (including the Internet of Things, AI, Blockchain, Virtual Reality, and the Metaverse) and what does not, while highlighting the advantages and disadvantages of these technological domains.