IoT for Power Utility: Fundamentals, Frontiers and Strategy Training Course

The primary goal of this training is to clarify what the 5G network entails and its influence on smart technologies. I aim to illustrate both the benefits and drawbacks of this technological synergy (5G / IoT) and outline the development trajectory of the network, which has been oriented toward the smart world from its inception.

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

This instructor-led, live training (online or onsite) is designed for advanced-level participants who wish to understand and leverage the emerging intersection of 6G technologies and IoT applications.

By completing this course, learners will gain the ability to:

• Explain the core technical concepts behind 6G.
• Assess how 6G will reshape IoT device communication and architecture.
• Evaluate 6G-enabled IoT use cases across industries.
• Prepare 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 generation of government data and digital archiving rates are surging, driven by the rapid proliferation of mobile devices and applications, smart sensors and IoT devices, cloud computing solutions, and citizen-facing portals. As digital information expands in volume and complexity, the challenges associated with information management, processing, storage, security, and disposition become increasingly intricate. Emerging tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector is reaching a critical tipping point, recognizing that information is a strategic asset. Consequently, governments must protect, leverage, and analyze both structured and unstructured information to better fulfill 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, personnel, 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 represents one of the intelligent industry solutions that enable governments to make better decisions by taking action based on patterns revealed through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these goals requires far more than simply 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," noted 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 allocated more than $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 daunting as its promise is encouraging. One significant challenge is efficient data storage. With budgets always tight, agencies must minimize the per-megabyte cost of storage while keeping data easily accessible so users can retrieve it when and how they need it. Backing up massive quantities of data further exacerbates this challenge.

Effectively analyzing data presents another major hurdle. Many agencies utilize commercial tools that allow them to sift through mountains of data, identifying 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. This 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 Bulgaria (online or onsite) is designed for intermediate IT professionals and business managers who wish to understand how IoT and edge computing can drive efficiency, real-time processing, and innovation across various industries.

Upon completing this training, participants will be able to:

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

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

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

• Understand the core concepts and advantages of Edge Computing.
• Identify use cases and examples suitable for Edge Computing application.
• Design and build Edge Computing solutions to facilitate faster data processing and lower operational costs.

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

This instructor-led training session, available both online and onsite, is tailored for entry-level technical professionals eager to grasp and implement embedded systems and IoT principles using C programming and microcontroller architectures.

Upon completing this training, participants will be capable of:

• Gaining a thorough understanding of embedded system architecture and its constituent parts.
• Writing and compiling C code to facilitate interaction with embedded hardware.
• Operating microcontroller peripherals, including timers and ADCs.
• Comprehending the role embedded systems play within IoT architectures.

Course Format

• Engaging lectures and group discussions.
• Extensive practical exercises and hands-on practice.
• Live-lab implementation exercises.

Customization Options

• For tailored training on this subject, please reach out to us to make arrangements.

This instructor-led, live training in Bulgaria (online or onsite) is tailored for 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) constitutes a network infrastructure that wirelessly links physical objects and software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. C is a general-purpose programming language widely recommended for IoT development due to its pervasive use and advantages in low-level programming.

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

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

• Install and configure NetBeans for programming IoT systems with C
• Comprehend the fundamentals of IoT architecture
• Recognize the benefits of utilizing C in IoT 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 intensive hands-on practice

Note

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

This hands-on course offers a thorough introduction to the Internet of Things (IoT), spanning from device-level programming to cloud-based data processing and visualization. Participants will examine the entire IoT architecture—including sensors, communication protocols, microcontrollers, and cloud integration—through guided exercises utilizing development boards such as ESP32 and Raspberry Pi. Upon completing the course, learners will be equipped to construct a full IoT pipeline: capturing sensor data, transmitting it via MQTT/HTTP, processing it on cloud platforms like Azure IoT Hub, AWS IoT Core, or Google Cloud IoT, and visualizing it using tools such as Grafana or Power BI. The curriculum also addresses security best practices and simulated cyber threats to guarantee secure and robust deployments.

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. Each engineering layer involves considerations of economics, standards, regulations, and the evolving state of the art. For the first time, a concise course is offered to cover 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 cuts across multiple technology domains to develop awareness of an IoT system, its components, and how it can benefit businesses and organizations.

Includes a live demo 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 effectively.

Estimates for the Internet of Things (IoT) market value are massive, since by definition, 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 numerous inexpensive wireless technologies added by the overwhelming adoption of smartphones and tablets in every home. The explosive growth of mobile devices led to the present demand for IoT.

Due to unbounded opportunities in the 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 developing IoT systems and further managing their sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their devices with the Internet or Mobile apps.

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, Government, Mobile Cellular, and other areas.

Basic introduction to all 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 apps 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 common IoT devices like Home automation, Smoke alarms, vehicles, military applications, home health, etc.

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

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

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

• Install and configure the necessary tools and frameworks (such as the Eclipse Open IoT Stack) for building Java-based IoT systems
• Grasp the core principles of IoT architecture
• Utilize the Eclipse Open IoT Stack for Java to connect and manage devices within an IoT environment
• Construct, test, and deploy an IoT system leveraging Java

Audience

• Software Developers
• Engineers

Format of the course

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

Note

• For inquiries regarding customized training for this course, please contact us to make arrangements.

IoT technology stands apart from other technological domains due to its complexity, spanning nearly every branch of engineering—including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each layer of IoT engineering involves considerations of economics, standards, regulations, and the evolving state of the art. This course offers a comprehensive overview of these critical aspects for the first time.

For manufacturing professionals, the most vital aspect is understanding advancements in the Industrial Internet of Things (IIoT). These include predictive and preventative maintenance, condition-based machine monitoring, production and energy optimization, supply-chain improvements, and maximizing the uptime of manufacturing utilities.

Summary

• An advanced training program focused on the current state of the art in IoT within Smart Factories.
• Spanning multiple technology domains to build awareness of IoT systems, their components, and how they can enhance efficiency for manufacturing managerial professionals.
• Live demonstrations of model IIoT applications designed for smart factories.

Target Audience

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

Duration 3 Days (8 hours per day)

Estimates for the Internet of Things (IoT) market value are substantial, as IoT represents an integrated, diffused layer of devices, sensors, and computing power overlaying consumer, B2B, and government industries. The number of IoT connections is growing rapidly: 1.9 billion devices today, projected to reach 9 billion by 2018. By that year, the number of connected devices will roughly equal the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer sector, numerous products and services have already integrated with IoT, including kitchen and home appliances, parking systems, RFID, lighting and heating products, as well as various Industrial Internet applications.

While the underlying technologies of IoT are not entirely new—given that M2M communication has existed since the birth of the Internet—the last few years have seen significant changes. These include the emergence of inexpensive wireless technologies and the widespread adoption of smartphones and tablets in every home. 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, with numerous innovations taking place since then. This course will introduce the key innovations in the IIoT space.

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

Course Objective

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

1. Examination of the business and technology behind common IIoT platforms such as Siemens MindSphere and Azure IoT.
2. Exploration of open-source and commercial enterprise cloud platforms for AWS IoT, Azure IoT, Watson IoT, and Mindsphere, alongside other minor IoT clouds.
3. Review of open-source and commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and Arm MbedLPC.
4. Discussion of security issues and solutions for IIoT.
5. Development of Mobile/Desktop/Web applications for registration, data acquisition, and control.
6. M2M Wireless protocols for IoT (WiFi, LoRa, BLE, Ethernet, EtherCAT, PLC): Guidelines on when and where to use each.
7. Basic introduction to all IoT elements: Mechanical systems, Electronics/sensor platforms, Wireless and wired protocols, Mobile-to-Electronics integration, Mobile-to-enterprise integration, Data analytics, and the total control plane.

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. Python is a high-level programming language widely recommended for IoT development due to its clear syntax and extensive community support.

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

Upon completing this training, participants will be capable of:

• Grasping the fundamentals of IoT architecture
• Learning the basics of using the Raspberry Pi
• Installing and configuring Python on the Raspberry Pi
• Understanding the advantages of using Python for programming IoT systems
• Building, testing, deploying, and troubleshooting an IoT system using Python and the Raspberry Pi

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.

In this instructor-led, live training in Bulgaria, 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 to 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.