Internet of Things (IoT) Training in Tashkent

This instructor-led, live training in Tashkent (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.

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

Designed for advanced-level participants eager to understand and harness the emerging intersection of 6G technologies and IoT applications, this instructor-led training is available both online and onsite.

Upon completing this course, learners will be able to:

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

Course Format

• Concept-focused lectures paired with expert discussions.
• Practical exercises designed to reinforce key engineering principles.
• Guided exploration of cases and scenario analysis.

Customization Options

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

This instructor-led, live training in Tashkent (available online or on-site) is designed for intermediate-level professionals seeking to leverage Federated Learning to optimize IoT and edge computing solutions.

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

• Grasp the core principles and advantages of Federated Learning in IoT and edge computing.
• 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.
• Tackle challenges related to data privacy and network constraints within IoT systems.

This instructor-led, live training in Tashkent (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 Tashkent (online or onsite) is designed for intermediate-level IoT developers, embedded engineers, and AI practitioners who want to apply TinyML for predictive maintenance, anomaly detection, and smart sensor solutions.

Upon completing this training, participants will be able to:

• Grasp the core concepts of TinyML and its role in IoT ecosystems.
• Configure a TinyML development environment tailored for IoT projects.
• Create and deploy ML models on low-power microcontrollers.
• Apply TinyML techniques for predictive maintenance and anomaly detection.
• Refine TinyML models to achieve optimal power efficiency and memory utilization.

This instructor-led, live training in Tashkent (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 completion of this training, participants will be able to:

• Understand the core principles of IoT and edge computing and their role in digital transformation.
• Identify use cases for IoT and edge computing in the 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.

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

This instructor-led, live training (available online or onsite) is designed for beginner-level technical professionals seeking to understand and apply embedded systems and IoT concepts using C and microcontroller architectures.

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

• Grasp the architecture and components of embedded systems.
• Write and compile C code for interacting with embedded hardware.
• Utilize microcontroller peripherals such as timers and ADCs.
• Understand the role of embedded systems within IoT architectures.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

The training aims to introduce participants to the realms of the Internet of Things (IoT) and blockchain, highlighting the advantages and disadvantages of these technological ecosystems.

This training aims to clarify what 5G networks are and their influence on smart technologies. We will explore both the advantages and disadvantages of the relationship between these technologies (5G/IoT), as well as the developmental trajectories of networks originally designed for the smart world.

The training aims to explain the definition of Smart Solutions (Internet of Things, AI, Blockchain, Virtual Reality, Metaverse) and highlight the benefits and drawbacks of these technological fields.

Dive 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 across diverse 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 fundamentally transforming business operations across various sectors, including government. The volume of government data and digital archiving is increasing rapidly, driven by the proliferation of mobile devices and applications, smart sensors and IoT 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 become increasingly challenging. New tools for capture, search, discovery, and analysis are enabling organizations to extract valuable insights from unstructured data. The government sector is at a critical tipping point, recognizing information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured data to better serve the public and meet mission requirements. As government leaders work to evolve into data-driven organizations, they are establishing the foundation to correlate dependencies across events, people, processes, and information.

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

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

Big Data represents a key intelligent industry solution, enabling governments to make better decisions by acting on patterns revealed through the analysis of large volumes of related and unrelated, structured and unstructured data.

However, achieving these outcomes requires more than just accumulating massive 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 helping agencies identify 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 necessary analytical tools.

The challenges posed by Big Data are nearly as formidable as the promise it offers. One major challenge is efficient data storage. With budgets often tight, agencies must minimize storage costs per megabyte while ensuring data remains easily accessible for users to retrieve when and how they need it. Backing up such massive data volumes adds another layer of complexity.

Effective data analysis presents another significant challenge. Many agencies utilize commercial tools 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 fulfilling mission objectives.

Custom-developed Big Data tools are also empowering agencies to meet their analytical 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 assisted medical researchers in identifying links that alert doctors to aortic aneurysms before they occur. It is also employed for more routine tasks, such as screening resumes to match job candidates with hiring managers.

Insurtech (also known as Digital Insurance) refers to the convergence of insurance and emerging technologies. Within the Insurtech domain, "digital insurers" leverage technological innovations in their business and operational models to reduce costs, enhance customer experience, and improve operational agility.

In this instructor-led training, participants will gain a comprehensive understanding of the technologies, methods, and mindset required to drive digital transformation within their organizations and across the broader insurance industry. The training is designed for managers who need to grasp the big picture, cut through the hype and jargon, and take the first concrete steps toward establishing an effective Insurtech strategy.

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

• Discuss Insurtech and its components in a structured and intelligent manner
• Identify and clarify the role of each key technology within the Insurtech ecosystem
• Draft a general strategy for implementing Insurtech initiatives within their organization

Audience

• Insurers
• Technology professionals within the insurance industry
• Insurance stakeholders
• Consultants and business analysts

Course Format

• A blend of lectures, group discussions, practical exercises, and case study activities

In this comprehensive course, combine the transformative potential of AI with the agility of edge computing. 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 needed to optimise AI performance for real-time processing and decision-making at the edge.

This instructor-led, live training in Tashkent (available online or on-site) is designed for product managers and developers who aim to leverage Edge Computing to decentralize data management, thereby achieving faster performance through the use of smart devices deployed directly on the source network.

Upon completing this training, participants will be able to:

• Grasp the fundamental concepts and key advantages of Edge Computing.
• Recognize practical use cases and real-world examples where Edge Computing can be effectively applied.
• Design and implement Edge Computing solutions that enable faster data processing while reducing operational costs.

Build a strong foundation in designing and managing a resilient edge computing infrastructure. Learn about open hybrid cloud infrastructures, managing workloads across diverse clouds, and ensuring flexibility and redundancy. This training provides essential knowledge on creating a scalable and secure infrastructure that supports the dynamic needs of modern applications with edge computing.

This instructor-led, live training in Tashkent (onsite or remote) is designed for engineers who wish to set up, deploy, and manage secure IoT applications.

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

• Develop and deploy applications to securely manage IoT devices.
• Integrate IoT devices with the Cloud in a secure manner.
• Integrate an IoT application with existing infrastructure.

The Internet of Things (IoT) represents an emerging technological domain that wirelessly connects physical objects with software applications for remote monitoring and control. Augmented Reality (AR) enhances user experience by overlaying virtual, computer-generated elements onto the physical real-world environment. This technology enables businesses to deliver real-time, contextual information directly to users. Both technologies are experiencing rapidly growing adoption rates across a wide range of industries.

Through this instructor-led live training, participants will gain a solid understanding of the fundamentals of IoT and AR and learn how to apply these insights to their organization's operations and strategic planning.

Upon completing this training, participants will be able to:

• Comprehend the core principles of IoT and AR
• Understand the operational mechanics of IoT and AR technologies
• Identify how IoT and AR can be integrated into business strategies
• Make well-informed strategic decisions regarding IoT and AR implementation

Audience

• Managers
• Entrepreneurs

Course Format

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

Note

• For customized training options, please contact us to arrange your session.

In this instructor-led, live training in Tashkent, participants will learn the fundamentals of IoT as they step through the creation of an Arduino-based IoT sensor system.

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

• Understand the principles of IoT, including IoT components and communication techniques.
• Learn how to use Arduino communication modules suitable for different IoT systems.
• Learn how to use and program a mobile app to control Arduino.
• Use a Wi-Fi module to connect the Arduino to another device.
• Build and deploy their own IoT Sensor System.

The Internet of Things (IoT) is 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 mechanisms. Azure provides a comprehensive suite of cloud services, including an IoT Suite with preconfigured solutions that assist developers in accelerating IoT project development.

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) refers to 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 technologies. C is a versatile programming language widely recommended for IoT development due to its widespread adoption and advantages in low-level programming.

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

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

• Install and configure NetBeans to facilitate IoT programming with C
• Grasp the core principles of IoT architecture
• Recognize the advantages of utilizing C for IoT system development
• Construct, test, deploy, and troubleshoot IoT systems using C

Target Audience

• Developers
• Engineers

Course Format

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

Note

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

This hands-on, practical 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 navigate the complete IoT architecture—including sensors, communication protocols, microcontrollers, and cloud integration—through guided exercises utilizing development boards such as ESP32 and Raspberry Pi. By the conclusion of the course, learners will be equipped to construct an end-to-end 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 the results using tools such as Grafana or Power BI. The curriculum also addresses security best practices and simulated cyber threats to guarantee robust and secure deployments.

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 critical considerations regarding economics, standards, regulations, and the evolving state of the art. For the first time, a comprehensive 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.

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

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 in an effective manner.

Estimates for the Internet of Things (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 numerous inexpensive wireless technologies added by the overwhelming adaptation of smartphones and Tablets in every home. The explosive growth of mobile devices led to present demand for 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 developing IoT systems and further managing its sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their device with the Internet or 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

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 platform for IoT - Xively, Omega, and NovoTech, etc.

Security issues and security solutions for IoT.

Open source/commercial electronics platform for IoT - Raspberry Pi, Arduino, ArmMbedLPC, etc.

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

Studies of 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) represents 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. 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.

Through this instructor-led live training, participants will gain the skills necessary 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, to program IoT systems with Java.
• Grasp the fundamental concepts of IoT architecture.
• Utilize the Eclipse Open IoT Stack for Java to connect and manage devices within an IoT solution.
• Construct, test, and deploy IoT systems using Java.

Audience

• Developers
• Engineers

Format of the course

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

Note

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

Unlike other technologies, IoT is far 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 aspects of economics, standards, regulations, and the evolving state of the art. For the first time, a modest course is offered to cover all of these critical aspects of IoT engineering.

For manufacturing professionals, the most critical aspect is to understand the advancements in the area of the Industrial Internet of Things, which includes predictive and preventative maintenance, condition-based monitoring of machines, production optimization, energy optimization, supply chain optimization, and uptime of manufacturing utilities, among others.

Summary

• An advanced training program covering the current state of the art in Internet of Things within Smart Factories.
• Spans multiple technology domains to build awareness of IoT systems and their components, and how they can support manufacturing managerial professionals.
• Live demonstrations of model IIoT applications for smart factories.

Target Audience

• Managers responsible for business and operational processes within their respective manufacturing organizations who want to learn how to leverage IoT to make their systems and processes more efficient.

Duration 3 Days (8 hours per day)

Estimates for the Internet of Things, or IoT, market value are massive, as 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 systems, RFID, lighting and heating products, and a number of applications in the Industrial Internet.

However, the underlying technologies of IoT are nothing new, as M2M communication has existed since the birth of the Internet. What has changed in the last couple of years is the emergence of numerous inexpensive wireless technologies, added to the overwhelming adoption of smartphones and tablets in every home. The explosive growth of mobile devices has led to the present demand for IoT.

Industrial IoT, or IIoT for manufacturing, has been widely in use since 2014, and since then a large number of IIoT innovations have taken place. This course will introduce all the important aspects of innovations in the Industrial IoT area.

This training is intended as a technology and business review of an emerging industry so that IoT enthusiasts and 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 smart factories for the manufacturing sector.

1. Studies of the business and technology of some of the common IIoT platforms like Siemens MindSphere and Azure IoT.
2. Open source and commercial enterprise cloud platforms for AWS-IoT apps, Azure-IoT, Watson-IoT, MindSphere IIoT cloud, in addition to other minor IoT clouds.
3. Open source and commercial electronics platforms for IoT: Raspberry Pi, Arduino, ArmMbedLPC, etc.
4. Security issues and security solutions for IIoT.
5. Mobile, Desktop, and Web apps for registration, data acquisition, and control.
6. M2M wireless protocols for IoT: WiFi, LoRaWAN, BLE, Ethernet, EtherCAT, PLC: When and where to use which one?
7. 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 the Total control plane.

The Internet of Things (IoT) serves as a network infrastructure that wirelessly connects physical objects with software applications, enabling them to communicate, exchange data, and leverage network communications, cloud computing, and data capture.

Blockchain operates as a decentralized database system, storing information within distributed ledgers across numerous nodes.

Integrating blockchain technology with IoT facilitates the accessibility and distribution of IoT data without relying on central control. This synergy unlocks a range of new possibilities and significant benefits for business organizations.

In this instructor-led, remote live training, participants will explore how blockchain and IoT collaborate through a series of hands-on, live laboratory exercises.

Upon completing this training, participants will be able to:

• Grasp how blockchain and IoT work in tandem to deliver solutions tailored to their organization
• Investigate various tools and resources available to implement a blockchain-based IoT solution for their organization

Audience

• Developers
• Managers

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 it.

Connected devices are disrupting many industries, and the power utility sector is no exception. Power utility companies currently face four key challenges stemming from the growth of the Internet of Things (IoT):

1. Machines, controllers, HMI, and SCADA systems are increasingly being connected to the cloud by vendors promising enhanced analytics and insights for predictive and preventative maintenance. However, quarantine policies surrounding critical assets mean that power companies cannot utilize these new IoT features offered by machine and controller vendors.
2. With the continuously decreasing cost of solar and wind power microgrids, utility companies will soon experience declining revenue from power generation. To compensate for lost production revenue, 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, peer-to-peer (P2P) energy trading between homes, microgrid-to-microgrid exchanges, microgrid-to-battery interactions, and home-to-battery solutions. All of this must be enabled through smart metering, smart grids, and secure transactions, which are only possible via Distributed Ledger Technology (DLT) like IOTA. Additionally, utilities are exploring the provision of smart city services to local authorities.
3. For critical infrastructure such as dams, the International Committee of Large Dams (ICOLD) requires real-time Structural Health Monitoring (SHM). This ensures that any impending danger of dam, rock, or tunnel collapse can be detected in advance, allowing affected populations to be evacuated promptly.
4. A new emerging revenue area is EV charging in parking facilities. How can IoT 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 industry giants have invested billions of dollars to develop more manageable and secure IoT platforms. Furthermore, IoT Edge has gained significant momentum in both research and deployment, becoming the only viable path for practical IoT implementation. With 5G promising to transform the IoT business landscape, there has been an unprecedented surge in research funding for new IoT areas. Consequently, it is absolutely essential for any practicing engineer to understand the IoT platforms developed by major players like AWS, Google, and especially Microsoft.

However, none of the aforementioned platforms offer a fully exhaustive or comprehensive solution for scalable IoT. For instance, deploying smart metering to millions of homes requires additional technologies to secure the meters, radio networks, IoT management solutions, and various other secure services. The strategy, pricing, and security of any IoT deployment must be optimal and acceptable. Given the vast amount of interdisciplinary knowledge required, it is nearly impossible for any single 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 about the challenges, risks, and practical methods for deploying IoT in next-generation power utility businesses.

In addition, as deployments scale, managing IoT services for thousands of sensors and connections has emerged as a distinct field of engineering research. Known formally as Managed IoT Services, this area is experiencing rapid growth because the challenges of scaling IoT are far greater than simply building it. This includes securing over-the-top firmware and software updates, managing sensor and system calibration, auto-diagnosing connection issues, pinpointing the 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 regarding IoT implementation in power utility companies, covering Smart Metering, Smart Cars, Structural Health Monitoring (SHM), Power Quality Diagnosis, and Smart Contracts. It provides a basic introduction to all elements of IoT, including mechanical and 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 across 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 protocol.
4. Fundamentals of IoT Gateways: Risks, management, and ecosystem considerations.
5. Mobile/Desktop/Web Apps for registration, data acquisition, and control – Overview of available M2M data acquisition platforms for IoT such as AWS IoT, Azure IoT, and Google IoT.
6. Security Issues and Solutions for IoT: A comprehensive review of security across all technology stacks.
7. Enterprise IoT Platforms: Including Microsoft Azure IoT Suites, AWS IoT, Google IoT, and Siemens MindSphere.
8. Smart Metering: Open Smart Grid Protocols (OSGP), ANSI C 2.18 Protocols, NIST Standards for HAN (Home Area Network), HomePlug Powerline Alliance, and the IEC 62056 Security Standard for Smart Meters.
9. Distributed Ledger Technology (DLT): Including Blockchain, HyperLedger, and DAG (Directed Acyclic Graph) for smart contracts, P2P transactions, and smart car charging.
10. IoT for Critical Infrastructure: Applications for dams, transformers, substations, and high-tension wires.

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 mechanisms. Python, a high-level programming language, is highly recommended for IoT development due to its clear syntax and robust community support.

In this instructor-led live training, participants will gain practical skills in programming IoT solutions using Python.

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

• Grasp the fundamentals of IoT architecture
• Master the basics of using Raspberry Pi
• Install and configure Python on a Raspberry Pi device
• Identify the advantages of utilizing Python for programming IoT systems
• Build, test, deploy, and troubleshoot an IoT system using Python and 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 make arrangements.

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 connectivity, cloud computing, and data collection.

In this instructor-led live training, participants will explore the fundamentals of IoT by guiding them through the development of an IoT sensor system using a Raspberry Pi.

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

• Grasping the core principles of IoT, including its components and communication methods
• Configuring a Raspberry Pi specifically for IoT applications
• Designing and deploying a custom IoT Sensor System

Audience

• Hobbyists
• Hardware and software engineers and technicians
• Technical professionals across all industries
• Novice developers

Course Format

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

Note

• The Raspberry Pi is compatible with various operating systems and programming languages. This course utilizes the Linux-based Raspbian OS and Python as the programming language. For specific setup requirements, please contact us to make arrangements.
• Participants must purchase their own Raspberry Pi hardware and components.

Over the past three years, the IoT engineering landscape has undergone dramatic transformations, largely propelled by tech giants such as Microsoft, Google, and Amazon. These industry leaders have invested billions of dollars to create IoT platforms that are not only easier to manage but also enhance data perimeter security. Additionally, IoT edge computing has gained significant traction in both research and practical deployment, becoming essential for real-world IoT implementation. The emergence of 5G also holds the promise of revolutionizing the IoT business model. Consequently, this has triggered an unprecedented surge in research funding across diverse IoT domains.

Despite this progress, the widespread adoption of IoT remains sluggish due to persistent security concerns at multiple levels. Securing firmware and gateways remains suboptimal. A critical challenge lies in the lack of consensus among major IoT vendors regarding security standards. For instance, while Microsoft Azure and Amazon AWS have advanced their own distinct security frameworks, NIST is advocating for a more comprehensive, unified standard. Although the OWASP IoT Security Top 10 model initially had some impact, it failed to gain substantial traction due to limited adoption by major platforms like Azure and Google.

Another significant area of concern is firmware security. Primarily, most firmware remains vulnerable to patching, whether delivered via Over-The-Air (OTA) updates or through local hardware ports.

Course Objective

1. Provide an introduction to technology stacks, data models, and vulnerabilities inherent in IoT.
2. Identify vulnerability layers within each stack and between interconnected stacks.
3. Analyze vulnerabilities arising from vendors and third-party devices.
4. Explore the NIST standards for IoT security.

In this instructor-led live training in Tashkent, participants will understand Internet of Things (IoT) architectures and learn about different IoT security solutions applicable to their organization.

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

• Understand IoT architectures.
• Understand emerging IoT security threats and solutions.
• Implement technologies for IoT security in their organization.

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

By the end of this training, participants will be capable of building, developing, managing, and implementing IoT applications for smart devices and machines using Kaa.

Machine-to-Machine (M2M) refers to direct automated communication between networked mechanical or electronic devices.

In this instructor-led live training in Tashkent, 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 understand how they integrate to form a complete ecosystem.
• Understand and explain the security features built into NB-IoT devices.
• Develop a simple application to track NB-IoT devices.

In this instructor-led live training held in Tashkent, participants will learn how to maximize Nginx's performance by setting it up, configuring it, monitoring it, and troubleshooting it for handling various forms of HTTP and TCP traffic. Covered topics include configuring the most critical parameters in Nginx, the operating system, and a virtual machine to achieve optimal value from Nginx.

ThingsBoard is an open-source IoT platform that provides device management, data collection, processing, and visualization for your IoT solution.

In this instructor-led live training, participants will learn how to integrate ThingsBoard into their IoT solutions.

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

• Install and configure ThingsBoard
• Understand the fundamentals of ThingsBoard features and architecture
• Build IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry device data routing
• Integrate ThingsBoard with Apache Spark for data aggregation from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Course format

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

Note

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