Online Internet of Things (IoT) Training in New Zealand

This instructor-led, live training in New Zealand (online or onsite) is designed for advanced-level IoT developers and smart home enthusiasts who want 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 such as MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimise IoT automation workflows.

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

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

Upon completing this course, learners will be able to:

• Explain the core technical concepts underpinning 6G.
• Assess how 6G will reshape IoT device communication and architecture.
• Evaluate 6G-enabled IoT use cases across various industries.
• Develop strategies for integrating 6G capabilities into existing IoT solutions.

Course Format

• Concept-focused lectures combined with expert-led discussions.
• Practical exercises designed to reinforce key engineering principles.
• Case-based exploration and scenario analysis within a guided environment.

Course Customisation Options

• For tailored versions of this training aligned with your organisation's technology roadmap, please contact us to arrange.

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

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

• Understand the core principles and benefits of Federated Learning in IoT and edge computing contexts.
• Implement Federated Learning models on IoT devices to enable decentralised AI processing.
• Reduce latency and enhance real-time decision-making in edge computing environments.
• Tackle challenges related to data privacy and network constraints in IoT systems.

This instructor-led, live training in New Zealand (available online or on-site) is designed for intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI to enhance 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 New Zealand (online or on-site) 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.
• Optimise TinyML models for efficient power and memory usage.

This instructor-led, live training in New Zealand (delivered online or on-site) is designed for intermediate-level IT professionals and business managers seeking to understand the potential of IoT and edge computing to drive efficiency, enable real-time processing, and foster innovation across 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 within the manufacturing, logistics, and energy sectors.
• Differentiate between edge and cloud computing architectures and deployment scenarios.
• Implement edge computing solutions for predictive maintenance and real-time decision-making.

Embedded systems are purpose-built computing systems designed to perform dedicated functions within larger systems. IoT (Internet of Things) is a network of interconnected physical devices embedded with sensors and software that communicate and exchange data over the internet.

This instructor-led, live training (online or on-site) 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:

• Understand the architecture and components of embedded systems.
• Write and compile C code for embedded hardware interaction.
• Work with microcontroller peripherals such as timers and ADCs.
• Understand how embedded systems contribute to IoT architectures.

Course Format

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

Course Customisation Options

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

The aim of this training is to explain what the 5G network is and the impact it has on smart technologies. We will explore both the advantages and disadvantages of these technological relationships (5G / IoT) and outline the network's development direction—since its inception, it has been designed specifically for the smart world.

The aim of this training is to clarify what Smart solutions are—and what they are not—including technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Blockchain, Virtual Reality (VR), and the Metaverse. We will explore the advantages and disadvantages of these emerging technological domains.

Technological advances and the exponential growth of information are reshaping how business is conducted across many sectors, including the public sector. Driven by the rapid proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals, government data generation and digital archiving rates are climbing. As digital information expands and grows more complex, so too do the challenges of managing, processing, storing, securing, and disposing of it. Emerging tools for capture, search, discovery, and analysis are enabling organisations to extract valuable insights from unstructured data. The government sector stands at a critical juncture, recognising that information is a strategic asset. To better serve the public and meet mission requirements, government bodies must protect, leverage, and analyse both structured and unstructured information. As leaders strive to evolve into data-driven organisations capable of successfully fulfilling their missions, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions will emerge from a convergence of the most disruptive technologies:

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

Big Data stands as one of the key intelligent industry solutions, empowering government to make better decisions by acting on patterns revealed through the analysis of vast data volumes—both related and unrelated, structured and unstructured.

However, achieving these outcomes requires far more than merely accumulating massive quantities of data. "Making sense of these volumes of Big Data requires cutting-edge tools and technologies that can analyse 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.

Taking a step towards helping agencies identify these technologies, the White House established the National Big Data Research and Development Initiative in 2012. This initiative included over $200 million in funding to maximise the benefits of the Big Data explosion and the tools required to analyse it.

The challenges posed by Big Data are nearly as daunting as the promise it offers is encouraging. Efficient data storage is one such challenge. As always, budgets remain tight, meaning agencies must minimise the per-megabyte cost of storage while ensuring data remains easily accessible so users can retrieve it when needed and in the format they require. Backing up massive quantities of data further heightens this challenge.

Effectively analysing the data presents another major hurdle. Many agencies employ commercial tools that enable them to sift through mountains of data, identifying trends that can improve operational efficiency. (A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save more than $500 billion while simultaneously fulfilling mission objectives.)

Custom-developed Big Data tools are also enabling agencies to meet 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. The system has assisted medical researchers in identifying links that can alert doctors to aortic aneurysms before they strike. It is also employed for more routine tasks, such as screening resumes to connect job candidates with hiring managers.

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

In this instructor-led training, participants will gain a clear understanding of the technologies, methods, and mindset required to drive digital transformation within their organisations and across the wider industry. The training is designed for managers who need a high-level overview, wish to cut through the hype and jargon, and are ready to take the first steps toward developing an Insurtech strategy.

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

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

Audience

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

Format of the course

• Part lecture, part discussion, with exercises and case study group activities

This instructor-led, live training in New Zealand (online or on-site) is designed for product managers and developers who wish to leverage Edge Computing to decentralise data management, achieving faster performance by utilising smart devices located at the source network.

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

• Understand the core concepts and advantages of Edge Computing.
• Identify practical use cases and examples where Edge Computing can be applied.
• Design and build Edge Computing solutions that enable faster data processing and reduce operational costs.

This instructor-led, live training in New Zealand (on-site or remote) is designed for engineers seeking to set up, deploy, and manage secure IoT applications.

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

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

The Internet of Things (IoT) 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 enhances the user experience by blending virtual, computer-generated elements with the physical real-world environment. AR enables businesses to provide users with a real-time, real-world view of information. These two technologies are seeing rapidly growing adoption across multiple industries.

In this instructor-led, live training, participants will learn the fundamentals of IoT and AR and apply these insights to their organisation's 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 regarding IoT and AR

Audience

• Managers
• Entrepreneurs

Format of the course

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

Note

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

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

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

• Understand the core principles of IoT, including its components and communication techniques.
• Learn how to utilise Arduino communication modules suitable for various IoT systems.
• Learn how to use and program a mobile app to control Arduino devices.
• Use a Wi-Fi module to connect an 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 with one another and exchange data through network communications, cloud computing, and data capture. Azure provides a comprehensive suite of cloud services, including an IoT Suite composed of preconfigured solutions that 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:

• Understand the fundamentals of IoT architecture
• Install and configure Azure IoT Suite
• Appreciate the benefits of using Azure in programming IoT systems
• Implement various Azure IoT services (IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, IoT Device Management)
• Build, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

Course Format

• A blend of lecture, discussion, exercises, and extensive hands-on practice

Note

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

The Internet of Things (IoT) is 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. C is a 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.

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

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

Audience

• Developers
• Engineers

Course Format

• A blend of lecture, discussion, exercises, and extensive hands-on practice

Note

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

Unlike other technologies, the Internet of Things (IoT) is far more complex, encompassing nearly every branch of core engineering: mechanical, electronics, firmware, middleware, cloud, analytics and mobile. For each of these engineering layers, there are economic considerations, standards, regulations and an evolving state of the art. For the first 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 the Internet of Things.

Cuts across multiple technology domains to build awareness of IoT systems and their components, and how they can benefit businesses and organisations.

Live demonstrations of model IoT applications showcasing practical deployments across diverse 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 respective organisations who want to learn how to harness IoT to make their systems and processes more efficient.

Entrepreneurs and investors looking to build new ventures who want 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, by definition, IoT is an integrated and diffused layer of devices, sensors and computing power that overlays entire consumer, business-to-business and government industries. The IoT will account for an increasingly large number of connections: 1.9 billion devices today, rising to 9 billion by 2018. By that year, the number 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 crossed over into the IoT, including kitchen and home appliances, parking systems, RFID, lighting and heating products, and numerous applications within the Industrial Internet.

However, the underlying technologies of IoT are not new, as machine-to-machine (M2M) communication has existed since the birth of the internet. What has changed in the last couple of years is the emergence of numerous inexpensive wireless technologies, compounded by the overwhelming adoption of smartphones and tablets in every home. The explosive growth of mobile devices has driven the current demand for IoT.

Due to the unbounded opportunities in the IoT business, a large number of small and medium-sized entrepreneurs have jumped on the IoT gold rush bandwagon. Additionally, the emergence of open-source electronics and IoT platforms has made the development of IoT systems and the management of their sizeable production increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their devices with the internet or mobile apps.

This training is intended as a technology and business review of an emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the basics of IoT technology and business.

Course Objective

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

A basic introduction to all elements of IoT: mechanical, electronics/sensor platforms, wireless and wireline protocols, mobile-to-electronics integration, mobile-to-enterprise integration, data analytics and the total control plane.

M2M wireless protocols for IoT: WiFi, Zigbee/Zwave, Bluetooth, ANT+: When and where to use each one?

Mobile, desktop and web apps for registration, data acquisition and control. Available M2M data acquisition platforms for IoT: Xively, Omega and NovoTech, etc.

Security issues and security solutions for IoT.

Open-source and commercial electronics platforms for IoT: Raspberry Pi, Arduino, ArmMbedLPC, etc.

Open-source and commercial enterprise cloud platforms for IoT apps: AWS, Azure IoT, Watson IoT cloud, in addition to other minor IoT clouds.

Studies of the business and technology aspects of common IoT devices such as home automation, smoke alarms, vehicles, military applications, 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 programming language renowned for its "write once, run anywhere" capability, is highly recommended for IoT development due to its portability and efficiency.

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

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

• Install and configure the requisite tools and frameworks (Eclipse Open IoT Stack) for programming IoT systems with Java
• Grasp the fundamental principles of IoT architecture
• Utilise 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 combination of lectures, discussions, exercises, and extensive hands-on practice

Note

• Should you wish to arrange customised training for this course, please contact us to make the necessary arrangements.

Unlike other technologies, IoT is far more complex, encompassing almost every branch of core engineering: mechanical, electronics, firmware, middleware, cloud, analytics, and mobile. For each of these engineering layers, there are critical considerations regarding economics, standards, regulations, and the evolving state of the art. For the first time, a modest course is offered to cover all of these essential aspects of IoT engineering.

For manufacturing professionals, the most critical aspect is to understand advancements in the area of the Industrial Internet of Things. This includes predictive and preventative maintenance, condition-based monitoring of machinery, production optimisation, energy optimisation, supply-chain optimisation, and the uptime of manufacturing utilities, among other key areas.

Summary

• An advanced training program covering the current state of the art in the Internet of Things within smart factories.
• Spans multiple technology domains to build awareness of IoT systems and their components, demonstrating 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 organisations who wish to learn how to harness 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, 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 large number of connections: 1.9 billion devices today, rising to 9 billion by 2018. In that year, the number of connected devices 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 crossed over into the IoT, including kitchen and home appliances, parking systems, RFID, lighting and heating products, and a number of applications in the Industrial Internet.

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

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

This training is intended as a technology and business review of an emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the basics of IoT technology and business.

Course Objective

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

1. Studies of the business and technology of common IIoT platforms such as Siemens MindSphere and Azure IoT.
2. Open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure-IoT, Watson-IoT, MindSphere IIoT cloud, in addition to other minor IoT clouds.
3. Open-source and commercial electronics platforms for IoT, including Raspberry Pi, Arduino, Arm Mbed LPC, etc.
4. Security issues and security solutions for IIoT.
5. Mobile, desktop, and web apps for registration, data acquisition, and control.
6. M2M wireless protocols for IoT: WiFi, LoRaWAN, BLE, Ethernet, EtherCAT, PLC – when and where to use which one?
7. Basic introduction to all elements of IoT: mechanical, electronics/sensor platforms, wireless and wireline protocols, mobile-to-electronics integration, mobile-to-enterprise integration, data analytics, and the total control plane.

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

Blockchain is a decentralised database system that stores data in ledgers distributed across multiple nodes.

Combining blockchain technology with IoT enables access to and the supply of IoT data without the need for centralised control. This integration unlocks a range of new possibilities and delivers multiple benefits for business organisations.

In this instructor-led, live remote training, participants will learn how blockchain and IoT can work together through a series of hands-on, live-lab exercises.

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

• Understand how blockchain and IoT can work together to deliver solutions for their organisation
• Explore various tools and resources to implement a blockchain-based IoT solution for their organisation

Audience

• Developers
• Managers

Course Format

• A blend of lecture, discussion, exercises and extensive hands-on practice.

Note

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

The proliferation of connected devices is disrupting numerous industries, with the power utility sector being no exception. Power utility companies currently face four key challenges arising from the growth of the Internet of Things (IoT):

1. Machines, controllers, Human-Machine Interfaces (HMI), and SCADA systems are increasingly being connected to the cloud by vendors promising enhanced analytics and insights for predictive and preventative maintenance. However, strict quarantine policies surrounding critical assets mean that power companies cannot utilise these new IoT features offered by machine and controller vendors.
2. With the ever-decreasing cost of solar and wind power microgrids, utility companies will soon experience a decline in revenue from 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, EV charging grid services, and peer-to-peer (P2P) energy trading between homes, microgrids, and batteries. All of this requires facilitation through smart metering, smart grids, and secure transactions, which are only possible via Distributed Ledger Technology (DLT) like IOTA. Additionally, utilities are exploring the provision of smart city services to city authorities.
3. For critical infrastructure such as dams, the International Committee on Large Dams (ICOLD) requires real-time Structural Health Monitoring (SHM). This ensures that any impending danger of dam, rock, or tunnel collapse can be detected in advance, allowing for the timely evacuation of affected populations.
4. A new emerging revenue area is EV charging in parking facilities. The question remains: how can IoT facilitate smart charging and smart parking?

Over the past three years, IoT engineering has undergone massive changes, primarily driven by Microsoft, Google, and Amazon. These industry giants have invested billions of dollars to develop IoT platforms that are easier to manage and more secure. Furthermore, IoT edge computing has gained significant momentum in both research and deployment as the only viable means for practical IoT implementation. With 5G promising to transform the IoT business landscape, an unprecedented amount of research funding has been directed towards new IoT areas. Consequently, it is now absolutely essential for any practicing engineer to understand the IoT platforms developed by major players such as AWS, Google, and especially Microsoft.

However, none of the platforms mentioned above offer a completely exhaustive or comprehensive solution for scalable IoT. Merely deploying smart metering to millions of homes requires additional technology to secure the smart meters, radio networks, IoT management systems, and various other secured services. The strategy, pricing, and security of any IoT deployment must be optimal and acceptable. Given the sheer amount of interdisciplinary knowledge required, it is nearly impossible for any single company to assemble a team capable of meeting all these requirements.

This course is a modest attempt to educate key decision-makers, developers, and security experts about the challenges, risks, and practical methods for deploying IoT in next-generation power utility businesses.

In addition, with scalable deployment, managing IoT services for thousands of sensors and connections is emerging as a distinct engineering discipline. Formally known as managed IoT services, this area is experiencing rapid growth, as the challenges of scaling IoT are far greater than simply building the systems. This includes ensuring the security of over-the-top firmware and software updates, managing sensor and system calibration, performing auto-diagnosis of connection issues, identifying the root causes 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, covering smart metering, smart vehicles, SHM (Structural Health Monitoring), power quality diagnosis, and smart contracts. It provides a basic introduction to all elements of IoT, including mechanical systems, electronic and 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 and Mobile Applications for IoT, and Centralised versus Decentralised IoT.
2. The IoT ecosystem for business, third-party device management, and risk management across the entire IoT ecosystem.
3. M2M wireless protocols for IoT: WiFi, SigFox, LORA, LPWAN, Zigbee/Zwave, Bluetooth, and ANT+; guidance on when and where to use each protocol.
4. Fundamentals of IoT Gateways: Risks, management, and ecosystem considerations.
5. Mobile, desktop, and web applications for registration, data acquisition, and control, including available M2M data acquisition platforms for IoT such as AWS IoT, Azure IoT, and Google IoT.
6. Security issues and solutions for IoT, including a review of security across all technology stacks.
7. Enterprise IoT platforms such as Microsoft Azure IoT Suite, AWS IoT, Google IoT, and Siemens MindSphere.
8. Smart metering, Open Smart Grid Protocols (OSGP), ANSI C12.18 Protocols, NIST standards for HAN (Home Area Network), HomePlug Powerline Alliance, and security standards for smart meters (IEC 62056).
9. Distributed Ledger Technology (DLT) such as Blockchain, HyperLedger, and DAG (Directed Acyclic Graph) for smart contracts, P2P transactions, and smart vehicle charging.
10. IoT for critical infrastructure, including dams, transformers, substations, and high-tension wires.

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

• Understand the fundamentals of IoT architecture
• Gain a foundational understanding of using Raspberry Pi
• Install and configure Python on Raspberry Pi
• Explore the benefits of using Python for programming IoT systems
• Build, test, deploy, and troubleshoot an IoT system using Python and Raspberry Pi

Audience

• Developers
• Engineers

Course Format

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

Note

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

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

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

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

• Understand the core principles of IoT, including its key components and communication techniques
• Learn how to configure the Raspberry Pi specifically for IoT applications
• Build and deploy their own IoT sensor system

Audience

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

Course Format

• A blend of lecture, discussion, exercises, and extensive hands-on practice

Note

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

Over the last three years, IoT engineering has undergone massive changes, primarily driven by Microsoft, Google and Amazon. These industry giants have invested billions of dollars to develop IoT platforms that are easier to manage and secure specific data perimeters. Additionally, IoT edge has gained significant momentum in both research and deployment, becoming the primary means for practical IoT implementation. 5G also promises to transform the IoT business landscape. This has resulted in an unprecedented surge of new research funding areas in IoT.

However, large-scale adoption of IoT remains slow due to security concerns at various levels. Securing firmware and gateways is far from ideal. A major issue is the disagreement among different large IoT vendors regarding security standards. Microsoft Azure and Amazon AWS have pushed forward with their own security standards, whereas NIST is advocating for a more comprehensive approach. The OWASP model of 10 layers of IoT security made some impact but ultimately failed to gain widespread traction due to non-adoption by major IoT platforms like Azure or Google.

Another major area of concern is firmware security. Primarily, most firmware remains vulnerable to patching, whether via OTA (Over-the-Air) or locally through a hardware port.

Course Objective

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

In this instructor-led, live training in New Zealand, participants will explore Internet of Things (IoT) architectures and gain an understanding of the various IoT security solutions relevant to their organisations.

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

• Understand IoT architectures.
• Identify emerging IoT security threats and corresponding solutions.
• Implement IoT security technologies within their organisations.

This instructor-led, live training in New Zealand (available online or on-site) is tailored for developers and programmers who wish to install, configure, and manage the Kaa platform to build robust 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) refers to direct automated communication between networked mechanical or electronic devices.

In this instructor-led, live training in New Zealand, participants will explore the various facets of NB-IoT (also known as LTE Cat NB1) as they develop and deploy a sample NB-IoT-based application.

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

• Identify the distinct components of NB-IoT and understand how they integrate to form a cohesive ecosystem.
• Understand and articulate the security features embedded within NB-IoT devices.
• Develop a simple application to track NB-IoT devices.

In this instructor-led, live training in New Zealand, participants will learn how to maximise Nginx performance while setting up, configuring, monitoring, and troubleshooting the system to handle various forms of HTTP and TCP traffic. Key topics include configuring the most critical parameters in Nginx, the operating system, and virtual machines to extract maximum value from the platform.

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

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

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

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

Audience

• Software engineers
• Hardware engineers
• Developers

Course format

• A blend of lecture, discussion, exercises, and extensive hands-on practice

Note

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