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 represents the subsequent generation of wireless communication standards, poised to revolutionize IoT ecosystems through ultra-high-speed connectivity, sophisticated sensing capabilities, and seamlessly integrated AI functions.

This instructor-led live training, available both online and onsite, is designed for advanced-level participants seeking to comprehend and capitalize on the emerging convergence of 6G technologies and IoT applications.

Upon completion of this course, learners will be equipped to:

• Articulate the fundamental technical principles underpinning 6G.
• Analyze how 6G will transform IoT device communication and structural frameworks.
• Evaluate 6G-enabled IoT use cases across various sectors.
• Develop strategies for incorporating 6G capabilities into current IoT solutions.

Course Format

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

Course Customization Options

• For customized versions of this training that align with your organization's 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) targets intermediate-level IT professionals and business managers who want to understand how IoT and edge computing can foster efficiency, real-time processing, and innovation across different industries.

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

• Understand the core principles of IoT and edge computing and their part in digital transformation.
• Identify practical applications for IoT and edge computing in manufacturing, logistics, and energy.
• Differentiate between edge and cloud computing architectures and deployment contexts.
• Implement edge computing solutions to facilitate predictive maintenance and real-time decision-making.

Embedded systems are specialized computing devices engineered to execute specific tasks within larger frameworks. The Internet of Things (IoT) refers to a vast network of physical devices equipped with sensors and software, enabling them to connect and share data across the internet.

This instructor-led live training, available either online or onsite, is designed for technical professionals at a beginner level who aim to grasp and implement embedded systems and IoT principles using C programming and microcontroller architectures.

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

• Gaining insight into the architecture and components of embedded systems.
• Writing and compiling C code to facilitate hardware interaction.
• Utilizing microcontroller peripherals, including timers and ADCs.
• Comprehending the role of embedded systems within IoT architectures.

Course Format

• Engaging lectures and discussions.
• Extensive exercises and practical sessions.
• Practical implementation within a live-lab environment.

Options for Customizing the Course

• To arrange a tailored training session for this course, please get in touch with us.

This training aims to clarify what the 5G network is and its impact on smart technologies. We will examine both the advantages and disadvantages of the relationship between these technologies (5G / IoT) and explore the developmental directions of a network that has been dedicated to the smart world from its inception.

The objective of the training is to explain what constitutes intelligent solutions (Internet of Things, AI, Blockchain, Virtual Reality, Metaverse) versus what does not, and to illustrate the advantages and disadvantages of these technological spheres.

Technological advancements and the exponential growth of information are reshaping business operations across numerous sectors, including government. The generation of government data and the pace of digital archiving are accelerating, driven by the surge in mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information becomes more expansive and complex, managing, processing, storing, securing, and disposing of this data grows increasingly difficult. New tools for capturing, searching, discovering, and analyzing data are enabling organizations to extract valuable insights from their unstructured data. The government sector is reaching a critical juncture, recognizing information as a strategic asset. Government bodies must protect, leverage, and analyze both structured and unstructured information to better serve the public and fulfill mission requirements. As government leaders work to transform into data-driven organizations to successfully achieve their missions, they are establishing the framework to correlate dependencies across 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 represents an intelligent industry solution that enables government entities to make better decisions by acting on patterns revealed through the analysis of large volumes of data—whether related or unrelated, structured or unstructured.

However, achieving this requires more than simply accumulating massive quantities of data. "Making sense of these volumes of Big Data requires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information," 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 moved to assist agencies in finding 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 tools required to analyze it.

The challenges posed by Big Data are nearly as formidable as its promise is encouraging. Efficiently storing data is one such challenge. Budgets are always tight, so agencies must minimize the cost per megabyte of storage while keeping data readily accessible so users can retrieve it when and how they need it. Backing up massive amounts of data further intensifies this challenge.

Effectively analyzing the data is another major hurdle. Many agencies utilize commercial tools that allow them 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 more than $500 billion while also meeting mission objectives.)

Custom-developed Big Data tools are also enabling agencies to address their data analysis needs. 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 helped medical researchers identify links that can alert doctors to aortic aneurysms before they occur. It is also used for more routine tasks, such as sifting through resumes to match job candidates with hiring managers.

Insurtech (also known as Digital Insurance) represents the convergence of the insurance industry with new technologies. Within the Insurtech sector, "digital insurers" leverage technological innovations to transform their business and operating models, aiming to reduce costs, improve customer experiences, and increase operational agility.

This instructor-led training will help participants understand the technologies, methods, and mindsets required to drive digital transformation within their organizations and across the broader industry. The course is specifically designed for managers who need a comprehensive overview, want to cut through the hype and jargon, and are ready to take initial steps toward establishing an Insurtech strategy.

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

• Discuss Insurtech and its various components intelligently and systematically
• Identify and demystify the role of each key technology within Insurtech.
• Draft a general strategy for implementing Insurtech within their organization

Audience

• Insurance professionals
• Technologists working within the insurance industry
• Insurance stakeholders
• Consultants and business analysts

Course Format

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

This instructor-led, live training in Norway (online or onsite) is designed for product managers and developers seeking to decentralize data management for improved performance, by leveraging smart devices located on the source network.

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

• Grasp the fundamental concepts and benefits of Edge Computing.
• Recognize practical use cases and real-world examples of Edge Computing applications.
• Design and implement Edge Computing solutions to accelerate data processing and lower operational costs.

This instructor-led, live training in Norway (onsite or remote) is targeted 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 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) represents 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. Azure provides a comprehensive suite of cloud services, including an IoT Suite with preconfigured solutions designed to help developers accelerate the creation of IoT projects.

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

Upon completing this training, participants will be able to:

• Grasp the fundamental concepts of IoT architecture
• Install and configure the Azure IoT Suite
• Understand the advantages of using Azure for IoT system programming
• Implement various Azure IoT services (including IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, and IoT Device Management)
• Build, test, deploy, and troubleshoot an IoT system utilizing Azure

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 arrange.

The Internet of Things (IoT) constitutes a network infrastructure that wirelessly links physical objects with software applications. This connectivity enables these entities to communicate and exchange data through network communications, cloud computing, and data capture mechanisms. C is a general-purpose programming language widely recommended for IoT development due to its pervasive presence and advantages in low-level programming.

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

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

• Install and configure NetBeans for developing IoT systems with C
• Grasp the fundamentals of IoT architecture
• Appreciate the benefits of utilizing C in IoT programming
• Build, test, deploy, and troubleshoot an IoT system using C

Audience

• Developers
• Engineers

Format of the course

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

Note

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

Unlike many other technological domains, 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, this modest course offers a comprehensive coverage of all these critical aspects of IoT Engineering.

Summary

An advanced training program detailing the current state of the art in the Internet of Things.

It bridges multiple technology domains to develop awareness of IoT systems and their components, illustrating how they can drive value for businesses and organizations.

Includes live demonstrations of model IoT applications to showcase practical deployments across various industry sectors such as 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 seek to understand how to harness IoT to enhance system and process efficiency.

Entrepreneurs and Investors aiming to build new ventures who wish to develop a deeper understanding of the IoT technology landscape to leverage it effectively.

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

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

While the underlying technologies of IoT are not entirely new—M2M communication has existed since the early days of the Internet—the landscape has changed drastically in recent years due to the emergence of inexpensive wireless technologies and the widespread adoption of smartphones and tablets in households. The explosive growth of mobile devices has fueled the current demand for IoT.

Given the unbounded opportunities in the IoT business sector, a large number of small and medium-sized entrepreneurs have joined the IoT "gold rush." Additionally, the emergence of open-source electronics and IoT platforms has made the development and subsequent large-scale production of IoT systems increasingly affordable. Existing electronic product owners are now facing 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, allowing IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and business models.

Course Objective

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

It provides a basic introduction to all elements of IoT: Mechanical components, Electronics/sensor platforms, Wireless and wireline protocols, Mobile-to-Electronics integration, Mobile-to-enterprise integration, Data analytics, and the Total control plane.

It covers M2M Wireless protocols for IoT (WiFi, Zigbee/Zwave, Bluetooth, ANT+), discussing when and where to use each.

It explores Mobile/Desktop/Web apps for registration, data acquisition, and control, along with available M2M data acquisition platforms for IoT such as Xively, Omega, and NovoTech.

It addresses security issues and solutions for IoT.

It examines open-source/commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and Arm MbedLPC.

It reviews open-source/commercial enterprise cloud platforms for AWS IoT apps, Azure IoT, Watson IoT cloud, in addition to other minor IoT clouds.

It includes studies of the business and technology of common IoT devices, such as home automation, smoke alarms, vehicles, military applications, and home health.

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 general-purpose language renowned for its "write once, run anywhere" capability, is highly recommended for IoT development due to its portability and efficiency.

In this instructor-led live training, participants will learn how to develop 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, for programming IoT systems with Java
• Gain a solid understanding of IoT architecture fundamentals
• Utilize the Eclipse Open IoT Stack for Java to connect and manage devices within an IoT solution
• Construct, test, and deploy an IoT system using Java

Audience

• Developers
• Engineers

Format of the course

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

Note

• For customized training options for this course, please contact us to arrange a session.

Unlike other technological domains, the Internet of Things (IoT) is significantly more complex, spanning nearly every branch of core engineering—including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each engineering layer involves economic considerations, standards, regulations, and the evolving state of the art. This course offers, for the first time, a comprehensive yet accessible overview of these critical aspects of IoT Engineering.

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

Summary

• An advanced training program covering the current state of the art in Internet of Things technologies within Smart Factories.
• Crosses multiple technology domains to develop a holistic awareness of IoT systems, their components, and how they can enhance efficiency for manufacturing managerial professionals.
• Includes live demonstrations of model IIoT applications designed for smart factories.

Target Audience

• Managers responsible for business and operational processes within their respective manufacturing organizations who wish to understand 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 (IoT) market value are massive. By definition, IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The number of connections is rapidly increasing: from 1.9 billion devices today to an estimated 9 billion by 2018. By that year, the IoT connection count will be roughly equal to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer space, many products and services have already integrated into the IoT ecosystem, including kitchen and home appliances, parking systems, RFID, lighting and heating products, as well as numerous applications in the Industrial Internet.

While the underlying technologies of IoT are not entirely new—M2M communication has existed since the early days of the Internet—the landscape has shifted dramatically in recent years. This change is driven by the emergence of numerous inexpensive wireless technologies and the overwhelming adoption of smartphones and tablets in every home. The explosive growth of mobile devices has led to the current demand for IoT solutions.

Industrial IoT (IIoT) for manufacturing has been widely adopted since 2014, leading to a significant number of IIoT innovations. This course will introduce all the important aspects of these innovations in the Industrial IoT sector.

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

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 common IIoT platforms, such as Siemens MindSphere and Azure IoT.
2. Overview of open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure IoT, Watson IoT, MindSphere IIoT cloud, along with other minor IoT clouds.
3. Overview of open-source and commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and Arm Mbed LPC.
4. Security issues and security solutions for IIoT.
5. Mobile/Desktop/Web applications for registration, data acquisition, and control.
6. M2M Wireless protocols for IoT, including WiFi, LoRa, BLE, Ethernet, EtherCAT, and PLC: Understanding when and where to use each.
7. Basic introduction to all elements of IoT: Mechanical systems, 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 numerous industries, with the power utility sector being no exception. Power utility companies currently face four primary challenges arising from the growth 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 governing critical assets prevent power companies from utilizing 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 will soon experience declining revenue from power generation. To compensate for lost power 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, and grid services for peer-to-peer (P2P) energy trading between homes, microgrids, and batteries. These initiatives require facilitation through 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 such as dams, ICOLD (International Committee of Large Dams) mandates real-time Structural Health Monitoring (SHM) to identify impending collapse risks in dams, rocks, or tunnels, allowing for the timely evacuation of affected populations.
4. A new emerging revenue area is EV charging in parking facilities. IoT can play a pivotal role in facilitating 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 tech giants have invested billions to develop IoT platforms that are easier to manage and secure. Furthermore, IoT edge computing has gained significant momentum as the primary means 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 essential 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 comprehensive solution for scalable IoT. For instance, deploying smart meters to millions of homes requires additional technologies for securing the meters, radio networks, IoT management systems, 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 challenging for any company to assemble a team capable of meeting all requirements.

This course is a modest attempt 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.

Additionally, as deployment scales, managing IoT services for thousands of sensors and connections is emerging as a separate engineering research subject. This area, formally known as managed IoT services, is experiencing rapid growth because the challenges of scalable IoT are significantly greater than the initial build. This includes 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 hardware and service health in distributed systems.

Course objectives

The main objective of the 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 also provides a basic introduction to all IoT elements: mechanical components, 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.
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 - reviewing the security of all technology stacks.
7. Enterprise IoT platforms such as 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 Standard for HAN (Home Area Network), Home Plug Powerline Alliance, and 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 like dams, transformers, substations, and high-tension wires.

The Internet of Things (IoT) serves as a network infrastructure that wirelessly connects physical objects and software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Python is a high-level programming language highly recommended for IoT 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) 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.

In this instructor-led live training, participants will master the fundamentals of IoT by building an IoT sensor system using the Raspberry Pi.

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

• Grasp the principles of IoT, including its components and communication methods
• Configure the Raspberry Pi specifically for IoT applications
• Construct and deploy their own IoT Sensor System

Audience

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

Format of the course

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

Note

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

Over the past three years, IoT engineering has undergone significant transformation, largely driven by tech giants such as Microsoft, Google, and Amazon. These industry leaders have invested billions to create IoT platforms that facilitate easier management and enhanced security for data perimeters. Additionally, IoT edge computing has gained considerable traction in both research and deployment as the primary method for practical IoT implementation. The advent of 5G is also poised to revolutionize the IoT business landscape, leading to an unprecedented surge in research funding across various IoT domains.

However, widespread adoption of IoT remains slow due to security concerns at multiple levels. Securing firmware and gateways is far from ideal. A major hurdle is the lack of consensus among prominent IoT vendors regarding security standards. While Microsoft Azure and Amazon AWS have advanced their own proprietary security standards, NIST is promoting a more comprehensive framework. Although the OWASP IoT Top 10 security model had some influence, it struggled to gain broad adoption due to the lack of support from major platforms like Azure and Google.

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

Course Objective

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

In this instructor-led live training in Norway, participants will understand Internet of Things (IoT) architectures and learn about 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) targets 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) denotes the direct, automated exchange of data between connected mechanical or electronic devices.

In this instructor-led, live training in Norway, participants will explore 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 understand how they 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 Nginx's performance by setting up, configuring, monitoring, and troubleshooting it to handle various forms of HTTP and TCP traffic. Topics include configuring critical Nginx parameters and optimizing the operating system and virtual machine to extract maximum value from Nginx.

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

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

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

• Install and configure ThingsBoard
• Understand the core principles of ThingsBoard's features and architecture
• Develop IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka to route telemetry data from devices
• Integrate ThingsBoard with Apache Spark to aggregate data from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Course format

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

Note

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