Nginx Training Course

This training aims to clarify what 5G networks are and how they influence smart technologies. We will explore both the benefits and drawbacks of the synergy between 5G and the Internet of Things (IoT), while highlighting the developmental trajectory of networks designed from the outset for the smart ecosystem.

6G represents the next generation of wireless communication standards, poised to revolutionise IoT ecosystems through ultra-fast connectivity, advanced sensing, and integrated AI capabilities.

This instructor-led, live training (available online or onsite) is designed for 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 organisational technology roadmap, please contact us to arrange.

Advancements in technology and the exponential growth of data are reshaping business operations across various sectors, including the government sector. Government agencies are experiencing a surge in data generation and digital archiving, driven by the rapid proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information becomes more expansive and complex, the management, processing, storage, security, and disposition of this data become increasingly intricate. New tools for capture, search, discovery, and analysis are enabling organisations to extract valuable insights from unstructured data. The government sector is at a critical juncture, recognising that information is a strategic asset. Governments must protect, leverage, and analyse both structured and unstructured information to better serve citizens and meet mission objectives. As government leaders strive to evolve into data-driven organisations to successfully achieve their missions, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions are being developed through the integration of the most disruptive technologies:

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

Big Data represents an intelligent industry solution that enables government entities to make better decisions by taking action based on patterns revealed through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these outcomes requires far more than simply 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.

The White House took a significant step toward helping agencies identify these technologies when it established the National Big Data Research and Development Initiative in 2012. This initiative included more than $200 million to maximise the potential of the Big Data explosion and the tools needed to analyse it.

The challenges posed by Big Data are nearly as daunting as its promise is encouraging. Efficiently storing data is one such challenge. With budgets always tight, agencies must minimise the per-megabyte cost of storage and keep data readily accessible so users can retrieve it when and how they need it. Backing up massive quantities of data further heightens this challenge.

Effectively analysing data is another major challenge. Many agencies employ commercial tools that enable them to sift through mountains of data, spotting trends that help them operate more efficiently. A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save more than $500 billion while also fulfilling mission objectives.

Custom-developed Big Data tools are also allowing agencies to address their need for data analysis. For example, Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The system has helped medical researchers identify a link that can alert doctors to aortic aneurysms before they occur. It is also used for more routine tasks, such as sifting through resumes to connect job candidates with hiring managers.

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

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

• Comprehend the principles of IoT and edge computing and their pivotal role in digital transformation.
• Recognise practical use cases for IoT and edge computing within the manufacturing, logistics, and energy sectors.
• Distinguish between edge and cloud computing architectures and their respective deployment scenarios.
• Deploy edge computing solutions to facilitate predictive maintenance and real-time decision-making.

This instructor-led, live training in Australia (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:

• Grasp 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 Australia (online or onsite) is designed for product managers and developers who wish to use Edge Computing to decentralize data management for improved performance, leveraging smart devices located on the source network.

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

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

Embedded systems are specialised computing solutions designed to execute specific tasks within broader technological environments. The Internet of Things (IoT) refers to a network of physical devices equipped with sensors and software, enabling them to connect, communicate, and share data via the internet.

This instructor-led, live training (available online or onsite) is tailored for beginner-level technical professionals looking to grasp and apply concepts related to embedded systems and IoT using C programming and microcontroller architectures.

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

• Comprehend the architecture and key components of embedded systems.
• Write and compile C code to facilitate interaction with embedded hardware.
• Utilise microcontroller peripherals, including timers and ADCs.
• Understand the role embedded systems play within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• Hands-on implementation within a live-lab environment.

Course Customisation Options

• To request a customised training session for this course, please get in touch with us to make arrangements.

This instructor-led, live training in Australia (online or onsite) targets intermediate-level professionals eager to apply Federated Learning to optimise IoT and edge computing solutions.

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

• Grasp the principles and advantages of Federated Learning in IoT and edge computing.
• Deploy Federated Learning models on IoT devices for decentralized AI processing.
• Minimise latency and enhance real-time decision-making within edge computing environments.
• Navigate challenges pertaining to data privacy and network constraints in IoT systems.

The Internet of Things (IoT) refers to 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 recommended for IoT development due to its widespread availability and low-level programming advantages.

During 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 in programming IoT systems
• 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 customised training for this course, please contact us to arrange.

Unlike other technologies, the Internet of Things (IoT) is significantly more complex, encompassing nearly every branch of core engineering—Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. For each engineering layer, there are critical considerations regarding economics, standards, regulations, and the evolving state of the art. For the first time, a comprehensive yet accessible course is offered to cover all these critical aspects of IoT engineering.

Summary

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

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

Live demonstrations of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases around connected devices & things.

Target Audience

Managers responsible for business and operational processes within their respective organizations who want to know how to harness IoT to make their systems and processes more efficient.

Entrepreneurs and Investors who are looking to build new ventures and want to develop a better understanding of the IoT technology landscape to see how they can leverage it in an effective manner.

Estimates for the Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.

In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet.

However, the underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT.

Due to unbounded opportunities in IoT business, a large number of small and medium sized entrepreneurs jumped on a bandwagon of IoT gold rush. Also due to emergence of open source electronics and IoT platform, cost of development of IoT system and further managing its sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their device with Internet or Mobile app.

This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business.

Course Objective

Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in home & city automation (smart homes and cities), Industrial Internet, healthcare, Govt., Mobile Cellular and other areas.

Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and Total control plane

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

Mobile/Desktop/Web app- for registration, data acquisition and control –Available M2M data acquisition platform for IoT–Xively, Omega and NovoTech, etc.

Security issues and security solutions for IoT

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

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

Studies of business and technology of some of the common IoT devices like Home automation, Smoke alarm, vehicles, military, home health etc.

The Internet of Things (IoT) constitutes a network infrastructure that seamlessly connects physical devices and software applications via wireless links, enabling them to communicate and exchange data through network protocols, cloud computing, and data capture mechanisms. Java, a versatile programming language celebrated for its "write once, run anywhere" capability, is highly recommended for IoT development due to its portability and efficiency.

Through this instructor-led live training, participants will gain the skills to programme IoT solutions using Java.

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

• Install and configure necessary tools and frameworks, such as the 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

Target Audience

• Developers
• Engineers

Course Format

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

Note

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

Unlike many other technologies, IoT is significantly more complex, spanning almost every branch of core engineering—including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each engineering layer presents its own economic, standards, regulatory, and state-of-the-art considerations. For the first time, this course offers a comprehensive overview of these critical aspects of IoT engineering.

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

Summary

• An advanced training program covering the latest developments in Internet of Things technologies within smart factories.
• Crosses multiple technology domains to build awareness of IoT systems, their components, and how they can assist manufacturing managerial professionals.
• Live demonstration of model IIoT applications designed for smart factories.

Target Audience

• Managers responsible for business and operational processes within their respective manufacturing organisations 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 substantial. By definition, IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays consumer, business-to-business, and government industries. The number of IoT connections is growing rapidly, rising from 1.9 billion devices today to an estimated 9 billion by 2018. In 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 transitioned into the IoT ecosystem, including kitchen and home appliances, parking solutions, RFID, lighting and heating products, and various applications within the Industrial Internet.

However, the underlying technologies of IoT are not entirely new, as Machine-to-Machine (M2M) communication has existed since the birth of the Internet. What has changed in recent years is the emergence of numerous inexpensive wireless technologies, driven by the widespread adoption of smartphones and tablets in every household. The explosive growth of mobile devices has led to the current demand for IoT.

Industrial IoT (IIoT) for manufacturing has been in widespread use since 2014, with a large number of IIoT innovations occurring since then. This course will introduce all the important aspects of these innovations in the Industrial IoT sector.

This training is intended as a technology and business review of this emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the basics 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 smart factories for the manufacturing sector.

1. Study of the business and technology behind common IIoT platforms such as Siemens MindSphere and Azure IoT.
2. Overview of open-source and commercial enterprise cloud platforms for IoT applications, including AWS IoT, Azure IoT, Watson IoT, Mindsphere IIoT cloud, and other smaller IoT clouds.
3. Open-source and commercial electronics platforms for IoT, such as Raspberry Pi, Arduino, and Arm Mbed LPC.
4. Security issues and security solutions for IIoT.
5. Mobile, Desktop, and Web applications for registration, data acquisition, and control.
6. M2M wireless protocols for IoT, including WiFi, LoRaWAN, BLE, Ethernet, EtherCAT, and PLC: Understanding when and where to use each.
7. Basic introduction to all IoT elements: 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 power utilities being no exception. Utility companies currently face four primary challenges driven by the growth of IoT.

1. Machines, controllers, HMIs, and SCADA systems are increasingly becoming cloud-connected, with vendors promising enhanced analytics and insights via their data for predictive and preventative maintenance. However, the strict quarantine policies regarding critical assets prevent power companies from utilising these new IoT features offered by machine and controller vendors.
2. With the continuously decreasing costs of solar and wind power microgrids, utility companies will soon experience declining revenue from power generation. To compensate for this loss, companies must aggressively pursue new revenue streams such as home energy management as a service, energy storage as a service, and providing grid services for EV charging, peer-to-peer (P2P) energy trading between homes and microgrids, microgrid-to-microgrid transfers, microgrid-to-battery connections, and home-to-battery interactions. These activities require smart metering, smart grids, and secure transactions facilitated by Distributed Ledger Technology (DLT) such as IOTA. Additionally, utilities are exploring opportunities to offer smart city services to local authorities.
3. For critical infrastructure like dams, the International Committee on Large Dams (ICOLD) requires real-time Structural Health Monitoring (SHM) to provide early warnings of impending dangers such as dam, rock, or tunnel collapses, allowing for the evacuation of affected individuals.
4. Another emerging revenue area is EV charging in car parks. This module explores how IoT can facilitate smart charging and smart parking solutions.

Over the past three years, engineering in IoT has undergone massive changes, primarily driven by Microsoft, Google, and Amazon. These tech giants have invested billions of dollars into developing IoT platforms that are easier to manage and secure. IoT edge computing has gained significant momentum in both research and deployment as the practical means for implementing IoT. Furthermore, 5G promises to transform the IoT business landscape, leading to unprecedented levels of research funding in this field. Consequently, for any practicing engineer, it is essential to understand the IoT platforms developed by major players like AWS, Google, and especially Microsoft.

However, none of the aforementioned platforms offer an exhaustive or fully comprehensive solution for scalable IoT. For instance, deploying smart meters to millions of homes requires additional technologies to secure the meters, radio networks, IoT management technology, and many other secured services. Strategy, pricing, and security for any IoT deployment must be optimal and acceptable. Given the extensive interdisciplinary knowledge required, it is difficult for any 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 approaches to deploying IoT for next-generation power utility businesses.

Additionally, with scalable deployments, managing IoT services for thousands of sensors and connections is emerging as a separate engineering subject of research. This area, formally known as managed IoT services, is experiencing rapid growth because the challenges of scalable IoT are much greater than simply building them. This includes securing over-the-top firmware/software updates, managing sensor and system calibration, auto-diagnosing connection issues, narrowing down root causes of API failures, and tracking the hardware and service health of distributed systems.

Course objectives

The main objective of the course is to introduce emerging technological options, platforms, and case studies of IoT implementation in power utility companies, including smart metering, smart cars, structural health monitoring (SHM), power quality diagnosis, and smart contracts. It provides a basic introduction to all elements of IoT, such as mechanical aspects, electronics/sensor platforms, wireless and wireline protocols, mobile-to-electronics integration, mobile-to-enterprise integration, and 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 centralized versus 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/Z-Wave, Bluetooth, ANT+: Understanding 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. Overview of available M2M data acquisition platforms for IoT: AWS IoT, Azure IoT, Google IoT.
6. Security issues and solutions for IoT: A review of security across 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), HomePlug Powerline Alliance, and the security standard 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 car charging.
10. IoT applications for critical infrastructure like dams, transformers, substations, and high-tension wires.

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

In this instructor-led, live training in Australia, participants will explore the key aspects of NB-IoT (also referred to as LTE Cat NB1) while developing and deploying a sample NB-IoT-based application.

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

• Identify the various components of NB-IoT and understand how they integrate to form a cohesive ecosystem.
• Understand and explain the security features inherent in NB-IoT devices.
• Develop a simple application to track NB-IoT devices.