Internet of Things (IoT) Training in Belgrade

This instructor-led, live training in Belgrade (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 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.

This instructor-led, live training in Belgrade (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.

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

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

• Understand the fundamentals of TinyML and its applications in IoT.
• Set up a TinyML development environment for IoT projects.
• Develop and deploy ML models on low-power microcontrollers.
• Implement predictive maintenance and anomaly detection using TinyML.
• Optimize TinyML models for efficient power and memory usage.

This instructor-led, live training in Belgrade (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.

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.

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.

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.

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.

Insurtech (also known as Digital Insurance) represents the intersection of the insurance industry and emerging technologies. Within the Insurtech sector, 'digital insurers' leverage technological innovations to refine their business and operational models, aiming to lower costs, elevate the customer experience, and increase operational agility.

This instructor-led training helps participants understand the technologies, methods, and mindset required to drive digital transformation within their organizations and across the broader industry. The course is designed for managers who need to gain a comprehensive overview, cut through hype and jargon, and take initial steps in developing an Insurtech strategy.

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

• Discuss Insurtech and its various components intelligently and systematically
• Identify and clarify the role of key technologies within Insurtech.
• Develop a general strategy for implementing Insurtech within their organization

Audience

• Insurance companies
• Technologists working in the insurance industry
• Stakeholders in the insurance sector
• Consultants and business analysts

Course Format

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

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 Belgrade (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.

This instructor-led, live training in Belgrade (on-site or remote) is aimed at engineers who wish to set up, deploy and manage a secure IoT application.

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

• Develop and deploy applications to manage IoT devices securely.
• Securely integrate IoT devices to the Cloud.
• Integrate an IoT application with existing infrastructure.

The Internet of Things (IoT) is an evolving technology domain that wirelessly connects physical devices and software applications for remote monitoring and control. Augmented Reality (AR) enhances the user experience by overlaying virtual, computer-generated content onto the physical world. This enables businesses to deliver real-time, contextual information to users within their actual environment. Both technologies are experiencing rapid adoption across various industries.

In this instructor-led live training, participants will explore the core concepts of IoT and AR and apply these insights to their organizational operations and strategic planning.

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

• Grasp the fundamental principles of IoT and AR
• Comprehend the operational mechanics of IoT and AR technologies
• Identify opportunities to integrate IoT and AR into business strategies
• Make well-informed business 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 a session.

In this instructor-led live training conducted in Belgrade, participants will learn the fundamentals of IoT by building an Arduino-based IoT sensor system.

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

• Understand IoT principles, including its components and communication techniques.
• Learn how to employ Arduino communication modules for various IoT applications.
• Master the use and programming of a mobile app to control Arduino.
• Connect an Arduino to another device using a Wi-Fi module.
• Build and deploy their own IoT Sensor System.

The Internet of Things (IoT) constitutes 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. Azure provides a robust suite of cloud services, including an IoT Suite composed of preconfigured solutions designed to help developers accelerate the creation of IoT projects.

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

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

• Comprehend the fundamental principles of IoT architecture
• Install and configure the Azure IoT Suite
• Identify the advantages of utilizing Azure for IoT system programming
• Implement key Azure IoT services, including IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, and IoT Device Management
• Construct, test, deploy, and troubleshoot an IoT system utilizing Azure

Audience

• Developers
• Engineers

Format of the course

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

Note

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

The Internet of Things (IoT) refers to a network infrastructure that wirelessly connects physical devices with software applications, enabling them to communicate, 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.

In this instructor-led live training, participants will learn how 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 fundamental concepts of IoT architecture
• Understand the advantages of using C for IoT system programming
• Build, test, deploy, and troubleshoot an IoT system using C

Audience

• Developers
• Engineers

Course Format

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

Note

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

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 evolving state of the art. This is for the firs time, a modest course is offered to cover all of these critical aspects of IoT Engineering.

Summary

An advanced training program covering the current state of the art in 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 and 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 Internet of Things or 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 Internet. However what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT.

Due to unbounded opportunities in IoT business, a large number of small and medium sized entrepreneurs jumped on a bandwagon of IoT gold rush. Also due to emergence of open source electronics and IoT platform, cost of development of IoT system and further managing its sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their device with 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) constitutes 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. Java, a versatile language renowned for its "write once, run anywhere" philosophy, is highly recommended for IoT development due to its portability and efficiency.

During 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 capable of:

• Installing and configuring tools and frameworks, such as the Eclipse Open IoT Stack, to program IoT systems with 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
• Building, testing, and deploying IoT systems using Java

Audience

• Developers
• Engineers

Format of the course

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

Note

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

IoT differs significantly from other technologies due to its complexity, spanning nearly every core engineering discipline: Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each engineering layer involves specific considerations regarding economics, standards, regulations, and the evolving state of the art. This course offers a comprehensive overview of these critical IoT engineering aspects for the first time.

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

Summary

• An advanced training program covering the current state-of-the-art in IoT within smart factories.
• Crosses multiple technology domains to build awareness of IoT systems, their components, and how they can assist 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 wish to leverage IoT to enhance the efficiency of their systems and processes.

Duration 3 Days (8 hours per day)

Estimates for the IoT market value are substantial. By definition, IoT is an integrated and dispersed layer of devices, sensors, and computing power that overlays consumer, business-to-business, and government industries. The number of IoT connections is growing rapidly: from 1.9 billion devices today to an expected 9 billion by 2018. By that year, this number will roughly equal the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

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

However, the underlying technologies of IoT are not new; M2M communication has existed since the inception of the Internet. What has changed in recent years is the emergence of numerous inexpensive wireless technologies, driven by the widespread adoption of smartphones and tablets in households. The explosive growth of mobile devices has led to the current demand for IoT.

Industrial IoT (IIoT) for manufacturing has been widely utilized since 2014, leading to numerous innovations in the field. This course introduces all important aspects of these IIoT innovations.

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

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. Study the business and technology of common IIoT platforms like Siemens MindSphere and Azure IoT.
2. Explore open-source/commercial enterprise cloud platforms for AWS-IoT apps, Azure-IoT, Watson-IoT, Mindsphere IIoT cloud, and other minor IoT clouds.
3. Review open-source/commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and ArmMbedLPC, etc.
4. Address security issues and solutions for IIoT.
5. Mobile/Desktop/Web apps for registration, data acquisition, and control.
6. M2M Wireless protocols for IoT (WiFi, LoRa, BLE, Ethernet, EtherCAT, PLC): When and where to use each one?
7. Provide a basic introduction to all IoT elements: Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data analytics, and the Total control plane.

Connected devices are disrupting numerous industries, with 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

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

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

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

• Understand the fundamentals of IoT architecture
• Learn the basics of using Raspberry Pi
• Install and configure Python on Raspberry Pi
• Learn the benefits of using Python in programming IoT systems
• Build, test, deploy, and troubleshoot an IoT system using Python and Raspberry Pi

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, enabling them to communicate and exchange data through network communications, cloud computing, and data capture.

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

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

• Understanding IoT principles, including its components and communication techniques
• Learning how to configure the Raspberry Pi specifically for IoT applications
• Building and deploying their own IoT Sensor System

Audience

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

Format of the course

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

Note

• Raspberry Pi supports a variety of operating systems and programming languages. This course utilizes Linux-based Raspbian as the operating system and Python as the programming language. To request a specific setup, please contact us to arrange.
• Participants are responsible for purchasing the Raspberry Pi hardware and components.

Over the past three years, IoT engineering has undergone massive transformation, primarily driven by tech giants like Microsoft, Google, and Amazon. These industry leaders have invested billions to develop IoT platforms that are easier to manage and offer improved security for certain data perimeters. Additionally, IoT edge computing has gained significant momentum as a practical means of implementing real-world IoT solutions. The arrival of 5G is also poised to transform the IoT business landscape, leading to unprecedented funding for a wide range of new research areas within IoT.

However, large-scale IoT adoption remains slow due to security concerns at various levels. Securing firmware and gateways is far from ideal. One major issue is the lack of consensus among large IoT vendors regarding security standards. Microsoft Azure and Amazon AWS have pushed their own proprietary security standards, while NIST is developing a more comprehensive framework. The OWASP model of 10 layers of IoT security had some initial impact but ultimately failed to gain widespread traction due to non-adoption by major platforms like Azure and Google.

Another critical area of concern is firmware security. Most firmware remains vulnerable to patching issues, whether through OTA (Over-the-Air) updates or local hardware ports.

Course Objective

1. Provide an introduction to all technology stacks, data models, and vulnerabilities in IoT.
2. Map out the layers of vulnerability at each stack level and between stacks.
3. Analyze vulnerabilities originating from vendors and third-party devices.
4. Learn about the NIST standards for IoT security.

In this instructor-led, live training in Belgrade, participants will gain a comprehensive understanding of Internet of Things (IoT) architectures and explore various IoT security solutions that can be applied to their organizations.

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

• Comprehend IoT architectures.
• Identify emerging IoT security threats and their corresponding solutions.
• Implement technologies for IoT security within their organization.

This instructor-led live training in Belgrade (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.

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

In this instructor-led live training in Belgrade, 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 an ecosystem.
• Understand and explain the security features inherent in NB-IoT devices.
• Develop a simple application to track NB-IoT devices.

In this instructor-led, live training conducted in Belgrade, participants will learn to maximize Nginx's performance by configuring, monitoring, and troubleshooting it for various HTTP and TCP traffic scenarios. Key topics include configuring essential Nginx parameters, as well as optimizing the OS and virtual machine settings to achieve peak Nginx performance.

ThingsBoard is an open-source IoT platform providing device management, data collection, processing, and visualization for your IoT solutions.

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

Upon completing this training, participants will be able to:

• Install and configure ThingsBoard
• Understand the fundamentals of ThingsBoard's features and architecture
• Develop IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry data routing from devices
• Integrate ThingsBoard with Apache Spark for aggregating data from multiple devices

Target Audience

• Software engineers
• Hardware engineers
• Developers

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 arrange.