Nginx Training Course

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

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

• Understand the principles of IoT and edge computing and their role in digital transformation.
• Identify use cases for IoT and edge computing in manufacturing, logistics, and energy sectors.
• Differentiate between edge and cloud computing architectures and deployment scenarios.
• Implement edge computing solutions for predictive maintenance and real-time decision-making.

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

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

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

This instructor-led, live training in the UK (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.

ThingsBoard is an open source IoT platform that offers device management, data collection, processing and visualization for your IoT solution.

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

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

• Install and configure ThingsBoard
• Understand the 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

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.

Kura is an open source Java-based framework for IoT that enables access to underlying hardware, communication with M2M/IoT Integration Platforms, gateway management, and network configurations management.

In this instructor-led, live training, participants will learn the fundamentals of Kura and how they can use it for their IoT solutions.

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

• Install and configure Kura
• Understand the fundamentals and core features of Kura
• Build, test, deploy, and troubleshoot IoT solutions with Kura

Audience

• Developers
• Programmers

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 the UK, participants will learn about the various aspects of NB-IoT (also known as LTE Cat NB1) as they develop and deploy a sample NB-IoT based application.

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

• Identify the different components of NB-IoT and how to fit together to form an ecosystem.
• Understand and explain the security features built into NB-IoT devices.
• Develop a simple application to track NB-IoT devices.

The aim of the training is to explain what the 5G network is and what impact it has on smart technologies. I want to show you both the advantages and disadvantages of these technological relationships (5G / IoT) and show you the directions of development of the network, which - from the very beginning - was dedicated to the smart world.

Advances in technologies and the increasing amount of information are transforming how business is conducted in many industries, including government. Government data generation and digital archiving rates are on the rise due to the rapid growth of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, information management, processing, storage, security, and disposition become more complex as well. New capture, search, discovery, and analysis tools are helping organizations gain insights from their unstructured data. The government market is at a tipping point, realizing that information is a strategic asset, and government needs to protect, leverage, and analyze both structured and unstructured information to better serve and meet mission requirements. As government leaders strive to evolve data-driven organizations to successfully accomplish mission, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions will be created from a mashup of the most disruptive technologies:

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

IDC predicts that by 2020, the IT industry will reach $5 trillion, approximately $1.7 trillion larger than today, and that 80% of the industry's growth will be driven by these 3rd Platform technologies. In the long term, these technologies will be key tools for dealing with the complexity of increased digital information. Big Data is one of the intelligent industry solutions and allows government to make better decisions by taking action based on patterns revealed by analyzing large volumes of data — related and unrelated, structured and unstructured.

But accomplishing these feats takes far more than simply accumulating massive quantities of data.“Making sense of thesevolumes of Big Datarequires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information,” Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog.

The White House took a step toward helping agencies find these technologies when it established the National Big Data Research and Development Initiative in 2012. The initiative included more than $200 million to make the most of the explosion of Big Data and the tools needed to analyze it.

The challenges that Big Data poses are nearly as daunting as its promise is encouraging. Storing data efficiently is one of these challenges. As always, budgets are tight, so agencies must minimize the per-megabyte price of storage and keep the data within easy access so that users can get it when they want it and how they need it. Backing up massive quantities of data heightens the challenge.

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

Custom-developed Big Data tools also are allowing agencies to address the need to analyze their data. For example, the 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 find a link that can alert doctors to aortic aneurysms before they strike. It’s also used for more mundane tasks, such as sifting through résumés to connect job candidates with hiring managers.

Insurtech (a.k.a Digital Insurance) refers to the convergence of insurance + new technologies. In the field of Insurtech "digital insurers" apply technology innovations to their business and operating models in order to reduce costs, improve the customer experience and enhance the agility of their operations.

In this instructor-led training, participants will gain an understanding of the technologies, methods and mindset needed to bring about a digital transformation within their organizations and in the industry at large. The training is aimed at managers who need to gain a big picture understanding, break down the hype and jargon, and take the first steps in establishing an Insurtech strategy.

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

• Discuss Insurtech and all its component parts 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

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

Format of the course

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

Introduction

Constrained by traditional voice and data revenue, CSPs (communication service providers) are looking for new source of revenue from IoT services provided to homes, office and personals. As a result, IoT is becoming the part of new OSS and BSS model.

Summary

• Case studies of successful IoT service integration by Telcos
• Integration of IoT services with OSS
• New kind of local IoT data/service/connectivity offering
• Vertical IoT -total service sale vs IoT middleware sale.
• Integration of IoT sale in BSS

Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 12 B by 2019 and 100B+ by 2025.

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.

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.

As DLT become more understood in recent years and its capability to solve enterprise business use cases become evident, technologist have been exploring Distributed Ledger Technology (DLT) (such as Blockchain or IOTA) to solve use cases that have been daunting industries for years. Unlike existing technologies, one of the key features of DLT is its unparalleled capability to provide, traceability, accountability and immutable records that can be accessed at any point in time. One application area of interest in DLT is securing heterogenous networks. The technology has to be secured, immutable and offer real time transaction.

Course Objective

1. Give introduction of migration of centralized cloud based IoT to decentralized edge based IoT (with example of smart car charging, P2P energy grids)
2. Drawing the layers of vulnerability at each stack and between the stack
3. Learning about the DLT (Blockchain and DAG – direct acyclic graph) in IoT initiatives in IBM, Samsung, IOTA foundation and some other large players.
4. Case studies and application areas for DLT in IoT

Introduction

Unlike other technologies, IoT is far more complex encompassing almost every branch of core Engineering-Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics and Mobile. For each of its engineering layers, there are aspects of economics, standards, regulations and evolving state of the art. This is for the firs time, a modest course is offered to cover all of these critical aspects of IoT Engineering.

For Faculty members, it is of paramount interest that they should have an overall background of evolving IoT standards. To apply for grants in IoT areas, faculties must be exposed to  new research directions where they can fit their existing skills. They also need to be aware of  overall idea of funding areas in IoT. This course will address those evolving areas where they can attract more research and industrial grants in IoT.

Summary

• An advanced training program covering the current state of the art in Internet of Things
• Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help faculties to write more project proposals in IoT domain
• Live demo of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation and use cases around connected devices & things   
• Introduction to latest areas of IoT which needs more research both from structural and engineering point of view 

Overview

Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 12 B by 2019 and 100B+ by 2025.

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.

Over the last three years, engineering in IoT has seen massive changes primarily driven by Microsoft, Google and Amazon. These large behemoths have invested billions of dollars to develop IoT platforms that are  more easy to manage and secure. Also IoT edge has gained a lot of momentum in both research and deployment as only means for practical IoT implementation.  5G is also promising to transform the business of IoT.  This has led to an unprecedented large swath of new areas of research funding in IoT.

Course Objective

Main objective of this course is to introduce emerging technological options, platforms and case studies of IoT implementation in emerging verticals ( smart cities, smart manufacturing, agriculture, public safety etc) and horizontals ( edge computing, PaaS platforms, 5G-IoT etc.) for the University researchers.

1. 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
2. M2M Wireless protocols for IoT- WiFi, Zigbee/Zwave, Bluetooth, ANT+ : When and where to use which one?
3. Edge Platforms for IoT
4. Known PaaS clouds for IoT- Azure, Google and AWS
5. Security issues and security solutions for IoT
6. Open source /commercial enterprise cloud platform for  AWS-IoT apps, Azure -IOT, Watson-IOT cloud in addition to other minor IoT clouds
7.  Emerging research areas in IoT edge computation, 5G-IoT and many other horizontals.

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

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

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

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

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

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

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

Audience

• Managers
• Entrepreneurs

Format of the course

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

Note

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