IoT Programming with C Training Course

This training aims to clarify what a 5G network is and its impact on smart technologies. We will explore both the advantages and disadvantages of the synergy between these technologies (5G/IoT) and highlight the development paths of a network designed from the ground up for the smart world.

6G represents the upcoming generation of wireless communication standards, poised to revolutionize IoT ecosystems by delivering ultra-fast connectivity, advanced sensing capabilities, and integrated AI functionalities.

This instructor-led live training, available either online or on-site, is designed for advanced participants seeking to comprehend and exploit the emerging convergence of 6G technologies and IoT applications.

Upon completing this course, learners will be able to:

• Describe the fundamental technical concepts underpinning 6G.
• Evaluate how 6G will transform IoT device communication and architecture.
• Assess 6G-enabled IoT use cases across various industries.
• Develop strategies for incorporating 6G capabilities into current IoT solutions.

Course Format

• Concept-driven lectures supplemented by expert-led discussions.
• Practical exercises tailored to reinforce core engineering principles.
• Guided exploration of case studies and scenario analysis.

Customization Options

• For customized versions of this training that align with your organization's technology roadmap, please reach out to us to arrange.

Technological advancements and the exponential growth of information are fundamentally reshaping business operations across various sectors, including government. Government data generation and digital archiving are accelerating due to the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information expands and grows more complex, the challenges associated with information management, processing, storage, security, and disposition intensify. Emerging tools for capture, search, discovery, and analysis are enabling organizations to derive valuable insights from unstructured data. The government sector has reached a critical juncture, recognizing information as a strategic asset. Agencies must now protect, leverage, and analyze both structured and unstructured information to better serve the public and fulfill mission requirements. As government leaders work to evolve into data-driven organizations capable of achieving their missions, they are establishing the foundation to correlate dependencies among events, personnel, processes, and information.

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

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

Big Data serves as an intelligent industry solution, empowering government entities to make superior decisions by acting on patterns identified through the analysis of large volumes of related and unrelated, structured and unstructured data.

However, achieving these results requires more than merely accumulating vast amounts of data. As Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy noted in an OSTP Blog post, "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."

The White House moved to support agencies in identifying these technologies by launching the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to capitalize on the surge of Big Data and the necessary analytical tools.

The challenges presented by Big Data are as significant as its potential benefits are promising. Efficient data storage remains a key challenge. With budgets often constrained, agencies must minimize the cost per megabyte of storage while ensuring data remains readily accessible for users when and how they need it. The requirement to back up massive data volumes further complicates this task.

Effective data analysis is another major hurdle. Many agencies utilize commercial tools to sift through large datasets, identifying trends that enhance operational efficiency. (A recent MeriTalk study revealed that federal IT executives believe Big Data could help agencies save over $500 billion while meeting mission objectives.)

Custom-developed Big Data tools are also enabling agencies to meet their analytical needs. For instance, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. This system has assisted medical researchers in identifying links that can alert doctors to aortic aneurysms before they occur. It is also employed for routine tasks, such as screening resumes to match job candidates with hiring managers.

This instructor-led, live training in Argentina (online or onsite) is tailored for intermediate-level IT professionals and business managers who want to understand how IoT and edge computing can drive efficiency, real-time processing, and innovation across diverse industries.

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

• Comprehend the foundational principles of IoT and edge computing and their significance in digital transformation.
• Identify practical use cases for IoT and edge computing in manufacturing, logistics, and energy.
• Differentiate between edge and cloud computing architectures along with their deployment scenarios.
• Deploy edge computing solutions for predictive maintenance and real-time decision-making.

This instructor-led, live training in Argentina (online or onsite) targets intermediate-level developers, system architects, and industry professionals aiming to leverage Edge AI to enhance IoT applications with intelligent data processing and analytics capabilities.

By the conclusion 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 Argentina (online or onsite) targets product managers and developers who aim to utilize Edge Computing to decentralize data management for improved performance, by leveraging smart devices located on the source network.

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

• Comprehend the fundamental concepts and benefits of Edge Computing.
• Recognize specific use cases and practical examples suitable for Edge Computing implementation.
• Design and construct Edge Computing solutions aimed at accelerating data processing and lowering operational expenses.

Embedded systems are specialized computing devices engineered to execute specific tasks within broader operational frameworks. The Internet of Things (IoT) refers to a network of physical devices equipped with sensors and software, enabling them to connect and exchange data over the internet.

This instructor-led training, available both online and on-site, is designed for technical professionals at the beginner level who aim to grasp and implement embedded systems and IoT concepts using C programming and microcontroller architectures.

Upon completing this course, participants will be capable of:

• Comprehending the architecture and components of embedded systems.
• Writing and compiling C code to facilitate interaction with embedded hardware.
• Utilizing microcontroller peripherals, such as timers and Analog-to-Digital Converters (ADCs).
• Understanding the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

Delivered by an instructor via live online or onsite sessions in Argentina, this training targets intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.

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

• Grasp the fundamental principles and advantages of Federated Learning in IoT and edge computing.
• Deploy Federated Learning models on IoT devices for decentralized AI processing.
• Minimize latency and enhance real-time decision-making within edge computing environments.
• Tackle challenges concerning data privacy and network limitations in IoT systems.

The Internet of Things (IoT) refers to a network infrastructure that wirelessly connects physical devices with software applications, enabling them to communicate, exchange data, and interact through network communications, cloud computing, and data capture. Azure provides a comprehensive suite of cloud services that includes an IoT Solution offering preconfigured frameworks to help developers accelerate the creation of IoT projects.

Through 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
• Learn 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

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.

Unlike many other technologies, the Internet of Things (IoT) is significantly more complex, spanning nearly every branch of core engineering including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each engineering layer of IoT involves critical considerations of economics, standards, regulations, and the evolving state of the art. For the first time, this modest course offers a comprehensive coverage of these essential aspects of IoT Engineering.

Summary

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

Crosses multiple technology domains to build awareness of IoT systems, their components, and how they can drive efficiency for businesses and organizations.

Features live demonstrations of model IoT applications to showcase practical deployments across various industry sectors, such as 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 understand how to leverage IoT to enhance system and process efficiency.

Entrepreneurs and Investors seeking to build new ventures and aiming to develop a deeper understanding of the IoT technology landscape to effectively leverage its potential.

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

In the consumer space, numerous 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 the last few years is the emergence of numerous inexpensive wireless technologies, driven by the overwhelming adoption of smartphones and tablets in every home. The explosive growth of mobile devices has led to the current demand for IoT.

Due to the unbounded opportunities in the IoT business sector, a large number of small and medium-sized entrepreneurs have joined the IoT gold rush. Additionally, the emergence of open-source electronics and IoT platforms has made the cost of developing IoT systems and managing their significant production increasingly affordable. Existing electronic product owners are now experiencing pressure to integrate their devices with the Internet or mobile apps.

This training is designed to provide 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 home & city automation (smart homes and cities), the Industrial Internet, healthcare, government, mobile cellular networks, and other areas.

Provide a basic introduction to all elements of IoT, including Mechanical systems, Electronics/sensor platforms, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data analytics, and the Total control plane.

Explore M2M Wireless protocols for IoT, such as WiFi, Zigbee/Zwave, Bluetooth, and ANT+, discussing when and where to utilize each one.

Examine Mobile/Desktop/Web apps for registration, data acquisition, and control, along with available M2M data acquisition platforms for IoT such as Xively, Omega, and NovoTech.

Address security issues and security solutions for IoT.

Review open-source/commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and ArmMbedLPC.

Discuss open-source/commercial enterprise cloud platforms for AWS-IoT apps, Azure-IoT, Watson-IoT, in addition to other minor IoT clouds.

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

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 connections, cloud computing, and data capture. 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.

In this instructor-led live training, participants will gain the skills necessary to develop IoT solutions using Java.

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

• Install and configure the necessary tools and frameworks, specifically the Eclipse Open IoT Stack, to program IoT systems in Java
• Grasp the core principles of IoT architecture
• Utilize the Eclipse Open IoT Stack for Java to connect and manage devices within an IoT environment
• Develop, test, and deploy an IoT system employing Java

Target Audience

• Software Developers
• Engineers

Course Format

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

Note

• For inquiries regarding customized training for this course, please contact us to make 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 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 manufacturing professional, most critical aspect is to understand the advancement in the area of Industrial Internet of things, which includes predictive and preventative maintenance, condition based monitoring of the machines, production optimization, energy optimization, supply-chain optimization and uptime of manufacturing utilities etc.

Summary

• An advanced training program covering the current state of the art in Internet of Things in Smart Factories.
• Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help manufacturing managerial professionals
• Live demo of model IIoT applications for smart factories

Target Audience

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

Duration 3 Days ( 8 hours / day)

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: 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.

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 Industrial IoT area.

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 smart factories for manufacturing sectors.

1. Studies of business and technology of some of the common IIoT platform like Siemens MindSphere and Azure IoT.
2. Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT, Mindsphere IIoT cloud in addition to other minor IoT clouds
3. Open source/commercial electronics platform for IoT-Raspberry Pi, Arduino , ArmMbedLPC etc
4. Security issues and security solutions for IIoT
5. Mobile/Desktop/Web app- for registration, data acquisition and control –
6. M2M Wireless protocols for IoT- WiFi, LoPan, BLE, Ethernet, Ethercat, PLC : When and where to use which one?
7. 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

Connected devices are disrupting numerous industries, with power utilities being no exception. Power utility companies face four primary challenges driven by the expansion of the Internet of Things (IoT):

1. Machines, controllers, HMI, and SCADA systems are increasingly being connected to the cloud by vendors who promise enhanced analytics and insights for predictive and preventative maintenance. However, the strict quarantine policies governing critical assets prevent power companies from fully utilizing these new IoT features offered by machine and controller vendors.
2. As the cost of solar and wind power microgrids continues to drop, utility companies anticipate declining revenue from traditional power generation. To offset this loss, they must aggressively pursue new revenue streams, such as home energy management as a service, energy storage as a service, grid services for EV charging, and grid services for peer-to-peer energy trading between homes, microgrids, and batteries. All of these services require smart metering, smart grids, and secure transactions, which are made possible through Distributed Ledger Technology (DLT) like IOTA. Additionally, utilities are exploring opportunities to provide smart city services to municipal authorities.
3. For critical infrastructure such as dams, the International Committee of Large Dams (ICOLD) mandates real-time Structural Health Monitoring (SHM). This allows for the early detection of potential collapse risks in dams, rock formations, or tunnels, enabling timely evacuation of affected populations.
4. A new revenue opportunity is emerging in EV charging within parking facilities, raising questions about how IoT can facilitate smart charging and smart parking solutions.

Over the past three years, engineering in IoT has undergone massive changes, largely driven by Microsoft, Google, and Amazon. These tech giants have invested billions of dollars to develop IoT platforms that are easier to manage and more secure. IoT edge computing has also gained significant momentum as the primary means for practical IoT implementation. The advent of 5G promises to transform the IoT business landscape, leading to unprecedented investment in research funding. 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 these platforms offer a fully exhaustive or comprehensive solution for scalable IoT. For instance, deploying smart meters to millions of homes requires additional technology for securing the meters, radio networks, IoT management technologies, and various other secured services. The strategy, pricing, and security of any IoT deployment must be optimized and acceptable. Given the interdisciplinary knowledge required, it is nearly impossible for a 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 on the challenges, risks, and practical approaches to deploying IoT for next-generation power utility business models.

Furthermore, with scalable deployment, managing IoT services for thousands of sensors and connections is emerging as a distinct engineering discipline. This area, formerly known as managed IoT services, is experiencing rapid growth as the challenges of scalable IoT are far greater than simply building them. This includes securing over-the-top firmware/software updates, managing sensor and system calibration, auto-diagnosing connection issues, identifying 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 Cars, SHM (structural health monitoring), Power Quality Diagnosis, and Smart Contracts. It provides a basic introduction to all elements of IoT, including mechanical and electronics/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 & Mobile Applications for IoT, Centralized vs 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/Zwave, Bluetooth, ANT+: When and where to use which one
4. Fundamentals of IoT Gateways: Risks, Management, and Ecosystem
5. Mobile/Desktop/Web apps for registration, data acquisition, and control – Available M2M data acquisition platforms for IoT: AWS IoT, Azure IoT, Google IoT
6. Security issues and solutions for IoT: Review of security across all technology stacks
7. Enterprise IoT platforms such as Microsoft Azure IoT suites, AWS IoT, Google IoT, Siemens MindSphere
8. Smart Metering, Open Smart Grid Protocols (OSGP), ANSI C 2.18 Protocols, NIST Standard for HAN (Home Area Network), Home Plug Powerline Alliance, Security Standard for Smart Meter: 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 for critical infrastructure like dams, transformers, substations, and high-tension wires

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. Python, a high-level programming language, is highly recommended for IoT development due to its clear syntax and extensive community support.

This instructor-led, live training equips participants with the skills to program IoT solutions using Python.

Upon completion, participants will be able to:

• Comprehend the fundamentals of IoT architecture
• Master the basics of using Raspberry Pi
• Install and configure Python on Raspberry Pi
• Understand the advantages of employing Python for IoT system programming
• Build, test, deploy, and troubleshoot an IoT system utilizing Python and Raspberry Pi

Audience

• Developers
• Engineers

Format of the course

• A combination of lectures, discussions, exercises, and intensive hands-on practice

Note

• For those seeking customized training for this course, please contact us to arrange a session.

In this instructor-led live training in Argentina, participants will explore the various aspects of NB-IoT (also known as LTE Cat NB1) while developing and deploying 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 understand how they integrate to form an ecosystem.
• Understand and explain the security features built into NB-IoT devices.
• Develop a simple application to track NB-IoT devices.