Online Internet of Things (IoT) Training in Norway

This instructor-led, live training in Norway (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.

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

This instructor-led, live training (online or onsite) is aimed at 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.

This instructor-led, live training in Norway (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.

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

• Understand the principles and benefits of Federated Learning in IoT and edge computing.
• Implement Federated Learning models on IoT devices for decentralized AI processing.
• Reduce latency and improve real-time decision-making in edge computing environments.
• Address challenges related to data privacy and network constraints in IoT systems.

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

By the end 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 systems designed to perform specific functions within larger systems. IoT (Internet of Things) is a network of interconnected physical devices equipped with sensors and software that communicate and exchange data over the internet.

This instructor-led, live training (online or onsite) is aimed at beginner-level technical professionals who wish 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:

• Comprehend the architecture and components of embedded systems.
• Write and compile C code for interacting with embedded hardware.
• Work with microcontroller peripherals such as timers and ADCs.
• Understand how embedded systems integrate into IoT architectures.

Format of the Course

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

Course Customization Options

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

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 the training is to explain what are - and what are not - Smart solutions (Internet of Things, AI, Blockchain, Virtual Reality, Metaverse) and to show the advantages and disadvantages of these technological worlds.

Advances in technology and the growing volume of information are reshaping business practices across various sectors, including government. The rapid expansion of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals has led to a significant increase in data generation and digital archiving by government entities. As the amount and complexity of digital information grow, the challenges related to managing, processing, storing, securing, and disposing of this data also become more intricate. New tools for capturing, searching, discovering, and analyzing unstructured data are enabling organizations to derive valuable insights. The government sector is at a critical juncture, recognizing that information is a strategic asset and that it must protect, leverage, and analyze both structured and unstructured data to better serve its mission requirements. Government leaders are working to transform their organizations into data-driven entities, laying the foundation to understand the interdependencies among events, people, 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 is one of the intelligent industry solutions that enable government to make better decisions by acting on patterns revealed through the analysis of large volumes of data—whether structured or unstructured, related or unrelated.

Achieving these goals requires more than just amassing vast amounts of data. "To make sense of these large volumes of Big Data, cutting-edge tools and technologies are necessary to analyze and extract useful insights from diverse streams of information," according to 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 to help agencies find these technologies by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to capitalize on the surge in Big Data and the tools needed for its analysis.

The challenges posed by Big Data are as formidable as its potential is promising. Efficient data storage is one of these challenges. Given tight budgets, agencies must minimize the cost per megabyte of storage while ensuring easy access to the data so that users can retrieve it quickly and in the format they need. Backing up large volumes of data further complicates this challenge.

Effective data analysis is another major hurdle. Many agencies use commercial tools to sift through vast amounts of data, identifying trends that can enhance operational efficiency. A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save more than $500 billion while also achieving their mission objectives.

Custom-developed Big Data tools are also assisting agencies in analyzing their data. For instance, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. This system has aided medical researchers in discovering a link that can alert doctors to aortic aneurysms before they occur. It is also used for more routine tasks, such as screening resumes to connect job candidates with hiring managers.

Insurtech, also known as Digital Insurance, represents the integration of insurance with cutting-edge technologies. In this field, "digital insurers" leverage technological innovations to optimize their business and operational models, aiming to reduce costs, enhance customer experiences, and increase operational agility.

This instructor-led training is designed to provide participants with a comprehensive understanding of the technologies, methods, and mindset required for digital transformation within their organizations and across the industry. The course is specifically targeted at managers who need to grasp the broader picture, demystify the hype and technical jargon, and take initial steps in formulating an Insurtech strategy.

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

• Discuss Insurtech and its various components with intelligence and a systematic approach.
• Identify and clarify the role of each key technology within Insurtech.
• Develop a general strategy for implementing Insurtech within their organization.

Audience

• Insurers
• Technologists in the insurance sector
• Insurance stakeholders
• Consultants and business analysts

Format of the course

• A combination of lectures, discussions, exercises, and group activities based on case studies.

This instructor-led, live training in Norway (online or onsite) is aimed at product managers and developers who wish to use Edge Computing to decentralize data management for faster performance, leveraging smart devices located on the source network.

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

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

This instructor-led, live training in Norway (onsite 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.

Internet of Things (IoT) is an emerging technology domain that connects physical objects and software applications wirelessly for remote sensing and control. Augmented Reality (AR) is a technology that improves user experience by blending virtual computer-generated elements with the physical real-world environment. AR allows businesses to provide users with a real-time and real-world view of information. These are two technologies that have been seeing a rapidly growing adoption rate across multiple industries.

In this instructor-led, live training, participants will learn the fundamentals of IoT and AR and apply these learnings to their organizations' operations and strategies.

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

• Understand the fundamentals of IoT and AR
• Learn how IoT and AR technologies work
• Understand how IoT and AR technologies can be applied to their business' strategy
• Make informed business decisions about IoT and AR

Audience

• Managers
• Entrepreneurs

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.

In this instructor-led, live training in Norway, 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 that can be used 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 connects physical objects and software applications wirelessly, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Azure provides a comprehensive set of cloud services, including an IoT Suite with preconfigured solutions designed to help developers accelerate the development of IoT projects.

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:

• Grasp the fundamentals of IoT architecture
• Install and configure Azure IoT Suite
• Discover the advantages of using Azure for programming IoT systems
• Implement various Azure IoT services, such as IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, and IoT Device Management
• Build, test, deploy, and troubleshoot an IoT system using 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 for this course, please contact us to arrange.

Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. C is a general-purpose programming language recommended for IoT due to its widespread use and low-level programming advantages.

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

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

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

Audience

• Developers
• Engineers

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

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

Unlike other technologies, the Internet of Things (IoT) is far more intricate, spanning virtually every core engineering discipline—mechanical, electronics, firmware, middleware, cloud, analytics, and mobile. Each layer of its engineering involves aspects of economics, standards, regulations, and the evolving state of the art. This course, for the first time, offers a comprehensive overview of all these critical aspects of IoT Engineering.

Summary

An advanced training program covering the current state of the art in Internet of Things (IoT).

This program spans multiple technology domains to develop an understanding of an IoT system and its components, as well as how it can benefit businesses and organizations.

Live demonstrations of model IoT applications will showcase practical IoT deployments across various industry sectors, including Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases involving connected devices and things.

Target Audience

Managers responsible for business and operational processes within their organizations who want to learn how to leverage IoT to enhance the efficiency of their systems and processes.

Entrepreneurs and investors looking to create new ventures and gain a better understanding of the IoT technology landscape to effectively utilize it in their endeavors.

The market value estimates for the Internet of Things (IoT) are substantial, given that the IoT is an integrated and pervasive layer of devices, sensors, and computing power that overlays consumer, business-to-business, and government industries. The number of IoT connections is expected to grow significantly: from 1.9 billion devices today to 9 billion by 2018. That year, it will be roughly equivalent to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer space, many products and services have already transitioned into the IoT, including kitchen and home appliances, parking solutions, RFID, lighting and heating systems, and various applications in the Industrial Internet.

While the underlying technologies of IoT are not new—M2M communication has existed since the inception of the internet—the recent emergence of numerous inexpensive wireless technologies, coupled with the widespread adoption of smartphones and tablets in every household, has driven the current demand for IoT. The explosive growth of mobile devices has further fueled this demand.

The vast opportunities in the IoT business have attracted a significant number of small and medium-sized entrepreneurs to join the IoT gold rush. The availability of open-source electronics and IoT platforms has made the development and management of IoT systems increasingly affordable. Existing electronic product manufacturers are feeling pressure to integrate their devices with the internet or mobile apps.

This training is designed to provide a technology and business review of this emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and its business applications.

Course Objective

The main objective of the course is to introduce participants to the latest technological options, platforms, and case studies of IoT implementation in areas such as home and city automation (smart homes and cities), Industrial Internet, healthcare, government, mobile cellular networks, and more.

The course will cover a basic introduction to all elements of IoT, including mechanical components, electronics/sensor platforms, wireless and wired protocols, integration of mobile with electronics, integration of mobile with enterprise systems, data analytics, and the total control plane.

It will also delve into M2M wireless protocols for IoT, such as WiFi, Zigbee/Zwave, Bluetooth, and ANT+, discussing when and where to use each one. The program will explore mobile/desktop/web applications for registration, data acquisition, and control, including available M2M data acquisition platforms like Xively, Omega, and NovoTech.

Security issues and solutions for IoT will be addressed, along with open-source and commercial electronics platforms such as Raspberry Pi, Arduino, and ArmMbedLPC. The course will also cover open-source and commercial enterprise cloud platforms like AWS-IoT apps, Azure-IOT, Watson-IOT cloud, and other minor IoT clouds.

Finally, the course will include case studies of common IoT devices, such as home automation systems, smoke alarms, vehicles, military applications, and home health solutions.

The Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, enabling them to communicate with each other and exchange data through network communications, cloud computing, and data capture. Java, known for its "write once, run anywhere" capability, is a versatile language recommended for IoT due to its portability and efficiency.

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

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

• Install and configure tools and frameworks (Eclipse Open IoT Stack) for programming IoT systems with Java
• Understand the core principles of IoT architecture
• Use the Eclipse Open IoT Stack for Java to connect and manage devices in an IoT solution
• Build, test, and deploy an IoT system using Java

Audience

• Developers
• Engineers

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

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

Unlike other technologies, IoT is far more intricate, spanning almost every core engineering discipline, including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each of these layers involves aspects of economics, standards, regulations, and the evolving state of the art. This course marks a significant step by covering all these critical aspects of IoT Engineering.

For manufacturing professionals, understanding advancements in the Industrial Internet of Things (IIoT) is crucial. This includes predictive and preventive maintenance, condition-based monitoring of machines, production optimization, energy efficiency, supply-chain optimization, and ensuring the uptime of manufacturing utilities.

Summary

• An advanced training program that delves into the current state-of-the-art in IoT for Smart Factories.
• It spans multiple technology domains to build awareness of an IoT system and its components, demonstrating how it can benefit manufacturing managerial professionals.
• Live demonstrations of model IIoT applications for smart factories are included.

Target Audience

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

Duration 3 Days (8 hours per day)

The market value of the Internet of Things (IoT) is projected to be enormous, as it integrates a vast layer of devices, sensors, and computing power across consumer, business-to-business, and government sectors. By 2018, the number of IoT connections is expected to reach 9 billion, roughly equal to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer space, numerous products and services have already transitioned into the IoT, including kitchen and home appliances, parking solutions, RFID technology, lighting and heating systems, and various Industrial Internet applications.

While the underlying technologies of IoT are not new—M2M communication has existed since the inception of the internet—the significant changes in recent years include the emergence of numerous inexpensive wireless technologies and the widespread adoption of smartphones and tablets. The explosive growth of mobile devices has driven the current demand for IoT.

Industrial IoT, or IIoT, has been widely used in manufacturing since 2014, leading to a surge of innovations. This course will introduce all the key aspects of these innovations in the Industrial IoT sector.

The training is designed as a technology and business review for an emerging industry, helping IoT enthusiasts and entrepreneurs grasp the fundamentals of IoT technology and business.

Course Objective

The primary goal of this course is to introduce emerging technological options, platforms, and case studies of IoT implementation in smart factories within the manufacturing sector.

1. Analysis of the business and technology behind common IIoT platforms like Siemens MindSphere and Azure IoT.
2. Exploration of open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure-IOT, Watson-IOT, Mindsphere IIoT cloud, and other minor IoT clouds.
3. Study of open-source and commercial electronics platforms for IoT, such as Raspberry Pi, Arduino, and ArmMbedLPC.
4. Examination of security issues and solutions in the context of IIoT.
5. Development of mobile, desktop, and web applications for registration, data acquisition, and control.
6. Overview of M2M wireless protocols for IoT, including WiFi, LoPan, BLE, Ethernet, Ethercat, PLC, with guidance on when and where to use each.
7. Basic introduction to all elements of IoT, covering mechanical components, electronics/sensor platforms, wireless and wireline protocols, mobile-to-electronics integration, mobile-to-enterprise integration, data analytics, and the total control plane.

Connected devices are disrupting many industries, and the power utility sector is no exception. Power Utility companies face four significant challenges due to the growth of IoT.

1. Machines, controllers, HMI (Human-Machine Interface), and SCADA systems are increasingly becoming cloud-connected by vendors who promise enhanced analytics and insights for predictive and preventative maintenance. However, the quarantine policy for critical assets means that these new IoT features from machine/controller vendors cannot be fully utilized by power companies.
2. As the cost of solar and wind power continues to decrease, utility companies will likely see a decline in revenue from power generation. To compensate for this loss, they must aggressively explore new revenue streams such as energy management services for homes, energy storage services, EV charging grid services, and peer-to-peer (P2P) energy trading between homes and microgrids. These services require smart metering, smart grids, and secure transactions, which can be facilitated by distributed ledger technology (DLT) like IOTA. Additionally, utilities are exploring opportunities to offer 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) to detect and prevent any impending dangers, ensuring the safety of affected populations.
4. Another emerging revenue area is EV charging in parking lots. IoT can facilitate smart charging and smart parking solutions.

Over the last three years, significant changes have occurred in IoT engineering, primarily driven by companies like Microsoft, Google, and Amazon. These giants have invested billions to develop more manageable and secure IoT platforms. The momentum of IoT edge technology has also increased, both in research and deployment, as it is essential for practical IoT implementation. 5G promises to transform the business landscape of IoT, leading to a surge in new areas of research funding. This makes it crucial for practicing engineers to understand the IoT platforms developed by major players like AWS, Google, and especially Microsoft.

However, none of these platforms offer an exhaustive or entirely comprehensive solution for scalable IoT. Deploying smart metering across millions of homes, for example, requires additional technology to secure meters, radio networks, and IoT management systems, among other services. The strategy, pricing, and security of any IoT deployment must be optimal and acceptable. Given the interdisciplinary nature of these requirements, it is challenging for companies to assemble a team that can meet all needs.

This course aims 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.

Additionally, managing IoT services for thousands of sensors and connections is emerging as a distinct engineering discipline. Known as managed IoT services, this field is experiencing rapid growth because the challenges of scalable IoT are more significant than building them. This includes securing over-the-top firmware/software updates, managing sensor calibration, diagnosing connection issues, identifying API failure root causes, and monitoring the 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. This includes smart metering, smart cars, structural health monitoring (SHM), power quality diagnosis, and smart contracts. It also covers the basics of all IoT elements—mechanical, 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, 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 Protocol
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: Review of Security Across 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 Standards for Smart Meters—IEC 62056
9. Distributed Ledger Technology (DLT) Such as Blockchain, HyperLedger, and DAG (Direct Acyclic Graph) for Smart Contracts, P2P Transactions, and Smart Car Charging
10. IoT for Critical Infrastructure Like Dams, Transformers, Substations, High-Tension Wires

Internet of Things (IoT) is a network infrastructure that links physical objects and software applications through wireless connections, enabling them to communicate and exchange data via network communications, cloud computing, and data capture. Python is a high-level programming language recommended for IoT due to its clear syntax and extensive community support.

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

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

• Grasp the fundamentals of IoT architecture
• Acquire the basics of using Raspberry Pi
• Install and configure Python on Raspberry Pi
• Understand the advantages 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

• 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.

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

In this instructor-led, live training, participants will gain an understanding of the fundamentals of IoT as they work through the process of creating an IoT sensor system using the Raspberry Pi.

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

• Grasp the principles of IoT, including its components and communication techniques
• Learn how to configure the Raspberry Pi for IoT applications
• Design and deploy their own IoT Sensor System

Audience

• Hobbyists
• Hardware and software engineers and technicians
• Technical professionals in various industries
• Beginner developers

Format of the course

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

Note

• The Raspberry Pi supports multiple operating systems and programming languages. This course will use Linux-based Raspbian as the operating system and Python as the programming language. If you require a different setup, please contact us to arrange.
• Participants are responsible for purchasing the necessary Raspberry Pi hardware and components.

Over the past three years, engineering in the Internet of Things (IoT) has undergone significant transformations, primarily driven by major players such as Microsoft, Google, and Amazon. These companies have invested billions to develop IoT platforms that are easier to manage and secure various aspects of data. Additionally, IoT edge computing has gained substantial momentum in both research and deployment, becoming a crucial component for practical IoT implementation. The advent of 5G is also poised to revolutionize the business landscape of IoT. This has led to an unprecedented surge in new areas of research funding within the IoT sector.

Despite these advancements, large-scale adoption of IoT remains slow due to security concerns at multiple levels. Securing firmware and gateways is far from ideal. One major issue is the lack of consensus among leading IoT vendors regarding security standards. Microsoft Azure and Amazon AWS have each promoted their own security frameworks, while NIST has proposed a more comprehensive standard. The OWASP model of 10 layers of IoT security had some impact but failed to gain widespread adoption due to resistance from major IoT platforms like Azure or Google.

Another significant concern is the security of firmware. Most firmware remains vulnerable to patching, whether through over-the-air (OTA) updates or local hardware ports.

Course Objective

1. Provide an introduction to all technology stacks, data models, and vulnerabilities in IoT.
2. Illustrate the layers of vulnerability at each stack and between stacks.
3. Address vulnerabilities associated with vendors and third-party devices.
4. Learn about the NIST standard for IoT security.

In this instructor-led, live training in Norway, participants will understand Internet of Things (IoT) architectures and learn the 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 Norway (online or onsite) is aimed at developers and programmers who wish to install, configure, and manage the Kaa platform to build IoT applications.

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

Machine-to-Machine (M2M) involves the direct, automated exchange of information between interconnected mechanical or electronic devices.

In this instructor-led, live training in Norway, participants will learn about the various aspects of NB-IoT (also known as LTE Cat NB1) as they develop and deploy 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.

In this instructor-led, live training in Norway, participants will learn how to maximize the performance of Nginx as they set up, configure, monitor and troubleshoot Nginx for handling various forms of HTTP / TCP traffic. Topics covered include how to configure the most important parameters in Nginx, the OS and a virtual machine to gain maximum value out of 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 core features and architecture of ThingsBoard
• Build IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry data routing from devices
• Integrate ThingsBoard with Apache Spark to aggregate data from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

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