IoT Programming with C Training Course

Delve deeper into the innovative realm of edge computing with this advanced course. Explore sophisticated architectures and tackle integration challenges, preparing to leverage the full potential of edge computing in a variety of business environments. Gain expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that meet specific industry needs.

Technological advancements and the exponential growth of information are reshaping business operations across various sectors, including government. The proliferation of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals has significantly increased the volume of data generated and digitally archived by government entities. As digital information becomes more extensive and complex, managing, processing, storing, securing, and disposing of this data also grows in complexity. Innovative tools for capturing, searching, discovering, and analyzing unstructured data are enabling organizations to derive valuable insights. The government sector is reaching a critical juncture where it recognizes that information is a strategic asset. To better serve and meet mission requirements, government bodies need to protect, leverage, and analyze both structured and unstructured information effectively. Government leaders are working to transform their organizations into data-driven entities by establishing the necessary infrastructure to correlate dependencies among events, people, processes, and information.

High-value solutions in the government sector will emerge from a combination of the most disruptive technologies:

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

Big Data is one of the intelligent industry solutions that enable government agencies to make better decisions by leveraging patterns identified through the analysis of large, diverse data sets—both structured and unstructured.

Achieving these goals involves more than just collecting vast amounts of data. "To make sense of these volumes of Big Data, advanced tools and technologies are needed to analyze and extract meaningful insights from extensive and varied information streams," wrote Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy in a blog post.

To assist agencies in finding these necessary technologies, the White House launched the National Big Data Research and Development Initiative in 2012. The initiative allocated more than $200 million to capitalize on the surge of Big Data and the tools required for its analysis.

While the potential of Big Data is promising, it also presents significant challenges. Efficient data storage is one such challenge. Budget constraints mean agencies must minimize storage costs per megabyte while ensuring easy access to data when needed. Backing up large volumes of data adds to this complexity.

Effective data analysis is another major hurdle. Many agencies use commercial tools to sift through vast amounts of data, identifying trends that can enhance operational efficiency. A recent study by MeriTalk found that federal IT executives believe Big Data could help agencies save over $500 billion while also achieving their mission objectives.

Custom-developed Big Data solutions are also aiding agencies in analyzing their data. For instance, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other government entities. This system has helped medical researchers identify early warning signs for aortic aneurysms and is used for routine tasks such as matching 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

This instructor-led, live training in Serbia (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.

Combine the transformative power of AI with the agility of edge computing in this comprehensive course. Learn to deploy AI models directly on edge devices, from understanding CNN architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills to optimize AI performance for real-time processing and decision-making at the edge.

This instructor-led, live training in Serbia (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 Serbia (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.

Build a strong foundation in designing and managing a resilient edge computing infrastructure. Learn about open hybrid cloud infrastructures, managing workloads across diverse clouds, and ensuring flexibility and redundancy. This training provides essential knowledge on creating a scalable and secure infrastructure that supports the dynamic needs of modern applications with edge computing.

This instructor-led, live training in Serbia (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 Serbia, 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.

Unlike other technologies, IoT is significantly more intricate, encompassing a wide range of core engineering disciplines such as Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each layer of its engineering involves aspects of economics, standards, regulations, and the evolving state of the art. This course is uniquely designed to cover all these critical aspects of IoT Engineering comprehensively.

Summary

An advanced training program that explores the current state-of-the-art in Internet of Things technology.

This program spans multiple technological domains to provide a broad understanding of an IoT system and its components, demonstrating how it can benefit businesses and organizations.

Live demonstrations of model IoT applications will showcase practical IoT deployments across various 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 organizations who wish to learn how to leverage IoT to enhance system and process efficiency.

Entrepreneurs and Investors looking to establish new ventures and gain a deeper understanding of the IoT technology landscape to effectively utilize it in their projects.

The estimated market value of Internet of Things (IoT) is substantial, given that IoT is an integrated and pervasive layer of devices, sensors, and computing power that spans consumer, business-to-business, and government industries. By 2018, the number of connected devices is projected to reach 9 billion, rivaling the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

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

While the underlying technologies of IoT are not new—M2M communication has existed since the inception of the internet—the recent emergence of numerous inexpensive wireless technologies, coupled with the widespread adoption of smartphones and tablets, has driven the explosive growth of mobile devices, leading to the current demand for IoT.

The vast opportunities in the IoT business have attracted a significant number of small and medium-sized entrepreneurs. The rise of open-source electronics and IoT platforms has made it increasingly affordable to develop and manage IoT systems on a large scale. Existing electronic product owners are feeling pressure to integrate their devices with the internet or mobile apps.

This training program is designed to provide a comprehensive review of an emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and business.

Course Objective

The primary goal of the course is to introduce participants to emerging technological options, platforms, and case studies of IoT implementation in areas such as home and city automation (smart homes and cities), Industrial Internet, healthcare, government, mobile cellular networks, and others.

A basic introduction to all elements of IoT will be provided, including Mechanical components, Electronics/sensor platforms, Wireless and wireline protocols, Mobile-to-Electronics integration, Mobile-to-enterprise integration, Data analytics, and Total control plane.

Discussion on M2M wireless protocols for IoT—WiFi, Zigbee/Zwave, Bluetooth, ANT+—and when to use each one.

Coverage of mobile/desktop/web applications for registration, data acquisition, and control, including available M2M data acquisition platforms such as Xively, Omega, and NovoTech.

Examination of security issues and solutions for IoT.

Introduction to open-source and commercial electronics platforms for IoT, such as Raspberry Pi, Arduino, and ArmMbedLPC.

Overview of open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure-IOT, Watson-IOT cloud, and other minor IoT clouds.

Case studies on the business and technology aspects of common IoT devices like home automation systems, smoke alarms, vehicles, military applications, and home health solutions.

Unlike other technologies, the Internet of Things (IoT) is far more complex, encompassing almost every branch of core engineering—mechanical, electronics, firmware, middleware, cloud, analytics, and mobile. Each layer of IoT involves aspects of economics, standards, regulations, and evolving state-of-the-art advancements. This course marks a significant step by offering comprehensive coverage of all these critical aspects of IoT Engineering.

For professionals in the manufacturing sector, understanding the advancements in Industrial Internet of Things (IIoT) is crucial. This includes areas such as predictive and preventive maintenance, condition-based monitoring of machines, production optimization, energy management, supply-chain efficiency, and ensuring the uptime of manufacturing utilities.

Summary

• An advanced training program that covers the current state-of-the-art in Internet of Things for Smart Factories.
• This course spans multiple technology domains to develop a broad awareness of IoT systems, their components, and how they can benefit 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 organizations who want to understand how to leverage IoT to enhance the efficiency of their systems and processes.

Duration 3 Days (8 hours/day)

The market value estimates for the Internet of Things (IoT) are significant, as by definition, the IoT is an integrated and pervasive layer of devices, sensors, and computing power that overlays consumer, business-to-business, and government industries. The number of connections in the IoT is expected to grow from 1.9 billion today to 9 billion by 2018, roughly equal to the combined number of smartphones, smart TVs, tablets, wearable computers, and PCs.

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

While the underlying technologies of IoT are not new—M2M communication has existed since the birth of the internet—the recent emergence of numerous inexpensive wireless technologies, combined with the widespread adoption of smartphones and tablets in every household, has driven the current demand for IoT. The explosive growth of mobile devices has significantly contributed to this trend.

Since 2014, Industrial IoT (IIoT) has been widely adopted in manufacturing, leading to numerous innovations. This course will introduce all the important aspects of these innovations in the IIoT field.

The training is designed as a technology and business review of an emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the fundamentals of IoT technology and business.

Course Objective

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

1. Business and technology analysis of common IIoT platforms like Siemens MindSphere and Azure IoT.
2. Open-source and commercial enterprise cloud platforms for AWS-IoT apps, Azure-IoT, Watson-IoT, MindSphere IIoT cloud, as well as other minor IoT clouds.
3. Open-source and commercial electronics platforms for IoT, such as Raspberry Pi, Arduino, and ArmMbedLPC.
4. Security challenges and solutions for IIoT.
5. Mobile/Desktop/Web applications for registration, data acquisition, and control.
6. M2M wireless protocols for IoT—WiFi, LoPan, BLE, Ethernet, Ethercat, PLC: Understanding when and where to use each protocol.
7. Basic introduction to all elements of IoT, including mechanical components, electronics/sensor platforms, wireless and wired protocols, mobile-to-electronics integration, mobile-to-enterprise integration, data analytics, and the total control plane.

Machine-to-Machine (M2M) involves the direct and automated exchange of information between interconnected mechanical or electronic devices.

In this instructor-led, live training in Serbia, 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.

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.