IoT Programming with Java Training Course

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

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 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," 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 resumes to connect job candidates with hiring managers.

Insurtech (also known as Digital Insurance) represents the integration of insurance with new technologies. In this sector, "digital insurers" leverage technological advancements to refine their business and operational models, thereby reducing costs, enhancing customer satisfaction, and increasing operational flexibility.

This instructor-led training will equip participants with knowledge about the technologies, methodologies, and mindset required for digital transformation within their organizations and across the industry. The course is designed for managers who need to grasp a comprehensive overview, dispel myths and technical jargon, and initiate steps towards formulating an Insurtech strategy.

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

• Discuss Insurtech and its various components in a knowledgeable and structured manner
• Identify and clarify the role of each key technology within Insurtech
• Create a general strategy for implementing Insurtech within their organization

Audience

• Insurance professionals
• Tech experts in the insurance sector
• Insurance industry stakeholders
• Consultants and business analysts

Course Format

• A combination of lectures, discussions, exercises, and group activities involving case studies

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

In this instructor-led, live training in the UAE, 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.

In contrast to other technologies, IoT is significantly more intricate, encompassing nearly every branch of core engineering—Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each layer of its engineering has economic, standardization, regulatory, and evolving technological aspects. This course aims to comprehensively cover all these critical facets of IoT Engineering for the first time.

Summary

An advanced training program that delves into the current state-of-the-art in Internet of Things (IoT).

Covers multiple technology domains to develop an understanding of IoT systems and their components, highlighting how they can benefit businesses and organizations.

Demonstrates practical IoT applications across various industry sectors such as Industrial IoT, Smart Cities, Retail, Travel & Transportation, and connected devices through live examples.

Target Audience

This program is designed for managers overseeing business and operational processes within their organizations who wish to leverage IoT to enhance efficiency in systems and workflows.

Entrepreneurs and investors interested in launching new ventures can gain a deeper understanding of the IoT technology landscape to effectively utilize it in their initiatives.

The Internet of Things (IoT) market is projected to be massive, given its integration across consumer, business-to-business, and government sectors. It currently accounts for 1.9 billion devices and is expected to reach 9 billion by 2018, equating roughly to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

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

While the foundational technologies of IoT are not new—M2M communication has existed since the inception of the internet—the recent surge in inexpensive wireless technologies, coupled with widespread adoption of smartphones and tablets, has fueled the current demand for IoT solutions. The proliferation of mobile devices has driven this growth.

The vast opportunities within the IoT sector have attracted a significant number of small and medium-sized entrepreneurs to invest in IoT ventures. Additionally, the rise of open-source electronics and IoT platforms has made it increasingly affordable to develop and manage IoT systems at scale. Existing electronic product owners are under pressure to integrate their devices with internet or mobile applications.

This training is aimed at providing a comprehensive overview of an emerging industry for IoT enthusiasts and entrepreneurs, covering both technological and business aspects.

Course Objective

The primary goal of the course is to introduce new technological options, platforms, and case studies related to IoT implementation in areas such as home & city automation (smart homes and cities), Industrial Internet, healthcare, government sectors, Mobile Cellular, and more.

A basic introduction to all 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.

Exploration of M2M wireless protocols for IoT—WiFi, Zigbee/Zwave, Bluetooth, ANT+: Understanding the appropriate use cases for each protocol.

Demonstration of mobile/desktop/web apps for registration, data acquisition, and control—available M2M data acquisition platforms like Xively, Omega, NovoTech, etc.

Discussion on security issues and solutions in IoT.

Overview of open-source/commercial electronics platforms for IoT such as Raspberry Pi, Arduino, ArmMbedLPC, etc.

Review of open-source/commercial enterprise cloud platforms like AWS-IoT apps, Azure-IOT, Watson-IOT cloud, along with other minor IoT clouds.

Analysis of business and technology aspects of common IoT devices such as home automation systems, smoke alarms, vehicles, military applications, and home health solutions.

In contrast to other technologies, IoT is significantly more intricate, encompassing nearly every branch of core engineering—Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each layer of its engineering involves aspects of economics, standards, regulations, and the evolving state of technology. This marks the first time a comprehensive course is being offered to cover all these critical facets of IoT Engineering.

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

Summary

• An advanced training program that covers the latest developments in IoT within smart factories.
• Covers multiple technology domains to develop an understanding of IoT systems and their components, aiding manufacturing managerial professionals.
• Livestream demonstrations of model IIoT applications for smart factories.

Target Audience

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

Duration: 3 Days (8 hours/day)

The estimated market value for Internet of Things (IoT) is enormous, as it integrates a vast array of devices, sensors, and computing power across consumer, business-to-business, and government sectors. The IoT will account for an increasing number of connections: currently at 1.9 billion devices, this figure is expected to reach 9 billion by 2018, roughly equal to the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

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

However, the foundational technologies behind IoT are not new; machine-to-machine (M2M) communication has existed since the inception of the internet. What has changed over the past few years is the proliferation of inexpensive wireless technologies, alongside the widespread adoption of smartphones and tablets in homes. The explosive growth of mobile devices has driven current demand for IoT.

Industrial IoT (IIoT) for manufacturing has been widely used since 2014, with numerous IIoT innovations emerging since then. This course will introduce all key aspects of these advancements in the Industrial IoT domain.

This training is designed to provide a technology and business overview of an emerging industry so that IoT enthusiasts or entrepreneurs can understand the basics of IoT technology and its business applications.

Course Objective

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

1. Examination of the business and technology aspects of common IIoT platforms such as Siemens MindSphere and Azure IoT.
2. Exploration of open-source/commercial enterprise cloud platforms for AWS-IoT apps, Azure-IOT, Watson-IOT, Mindsphere IIoT Cloud, along with other minor IoT clouds.
3. Study of open-source/commercial electronics platforms for IoT including Raspberry Pi, Arduino, ArmMbedLPC, etc.
4. Discussion on security issues and solutions in IIoT.
5. Development of mobile/desktop/web applications for registration, data acquisition, and control.
6. Understanding M2M wireless protocols for IoT—WiFi, LoPan, BLE, Ethernet, Ethercat, PLC: when and where to use each one?
7. 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 total control plane.

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

In this instructor-led live training session, participants will learn the basics of IoT as they go through the process of creating an IoT sensor system using the Raspberry Pi.

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

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

Audience

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

Course Format

• Mixed lecture, discussion, exercises, and extensive hands-on practice

Note

• The Raspberry Pi supports multiple operating systems and programming languages. This course will use the Linux-based Raspbian as the operating system and Python for programming. For a specific setup request, please contact us to arrange.
• Participants must purchase their own Raspberry Pi hardware and components.

In the past three years, advancements in Internet of Things (IoT) engineering have been significantly influenced by major tech giants such as Microsoft, Google, and Amazon. These companies have invested billions to create more manageable and secure IoT platforms. Additionally, there has been substantial growth in both research and deployment of edge computing for practical IoT implementation. The advent of 5G is also anticipated to revolutionize the IoT business landscape, leading to a surge in new areas of research funding within the IoT domain.

Despite these advancements, widespread adoption of IoT remains sluggish due to various security concerns. Ensuring the safety of firmware and gateways has not been fully achieved. A significant issue lies in the lack of consensus among major IoT vendors regarding security standards. While Microsoft Azure and Amazon AWS have established their own security protocols, NIST (National Institute of Standards and Technology) is promoting a more comprehensive approach. Although the OWASP model with its 10 layers of IoT security has had some impact, it has not been widely adopted by leading platforms like Azure or Google.

Another major concern revolves around firmware security. Most firmware remains susceptible to vulnerabilities even when patched through over-the-air (OTA) updates or via hardware ports.

Course Objective

1. To provide an overview of the technology stacks, data models, and vulnerabilities associated with IoT.
2. To identify and analyze the layers of vulnerability within each stack and between different stacks.
3. To examine security issues arising from vendors and third-party devices.
4. To familiarize learners with the NIST standards for IoT security.

Machine-to-Machine (M2M) involves the automatic exchange of data between interconnected mechanical or electronic devices.

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

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

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

In this instructor-led, live training in the UAE, participants will learn how to maximize the performance of Nginx as they set up, configure, monitor and troubleshoot Nginx for handling various forms of HTTP / TCP traffic. Topics covered include how to configure the most important parameters in Nginx, the OS and a virtual machine to gain maximum value out of Nginx.

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

In this instructor-led live session, 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
• Grasp the core features and architecture of ThingsBoard
• Create IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry data routing from devices
• Connect ThingsBoard with Apache Spark to aggregate data from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Course Format

• The course includes lectures, discussions, exercises, and extensive hands-on practice.

Note

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