Internet of Things (IoT) Training in San Francisco

This instructor-led, live training (online or onsite) is designed for advanced-level IoT developers and smart home enthusiasts who wish to automate IoT processes and create innovative solutions using n8n. By the end of this training, participants will be able to: - Set up and configure n8n for government IoT workflow automation. - Integrate IoT devices and platforms using n8n nodes and connectors. - Implement custom workflows to automate IoT tasks and processes. - Utilize IoT protocols such as MQTT and REST APIs within n8n workflows. - Monitor, troubleshoot, and optimize IoT automation workflows.

6G is the next-generation wireless communication standard poised to revolutionize IoT ecosystems through ultra-fast connectivity, advanced sensing, and integrated AI capabilities. This instructor-led, live training (online or onsite) is designed for advanced-level participants who wish to understand and leverage the emerging intersection of 6G technologies and IoT applications for government and other sectors. 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 organizational technology roadmap, please contact us to arrange.

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals who wish to apply Federated Learning to enhance IoT and edge computing solutions for government. By the end of this training, participants will be able to: - Understand the principles and benefits of Federated Learning in IoT and edge computing environments. - Implement Federated Learning models on IoT devices to enable decentralized AI processing. - Reduce latency and improve real-time decision-making capabilities in edge computing scenarios. - Address challenges related to data privacy and network constraints in government IoT systems.

This instructor-led, live training (online or onsite) is designed for intermediate-level developers, system architects, and industry professionals who aim to leverage Edge AI to enhance IoT applications with advanced data processing and analytics capabilities.

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

• Comprehend the core principles of Edge AI and its application in IoT systems.
• Establish and configure Edge AI environments for IoT devices.
• Create and deploy AI models on edge devices to support IoT applications.
• Execute real-time data processing and decision-making within IoT frameworks.
• Integrate Edge AI with a variety of IoT protocols and platforms.
• Address ethical considerations and best practices in the deployment of Edge AI for government and industry use cases.

This instructor-led, live training in San Francisco (online or onsite) is aimed at intermediate-level IoT developers, embedded engineers, and AI practitioners who wish to implement TinyML for government applications such as predictive maintenance, anomaly detection, and smart sensor deployments. By the end of this training, participants will be able to: - Understand the fundamentals of TinyML and its applications in IoT. - Set up a TinyML development environment suitable for IoT projects. - Develop and deploy machine learning models on low-power microcontrollers. - Implement predictive maintenance and anomaly detection using TinyML. - Optimize TinyML models for efficient power and memory usage, ensuring they meet the stringent requirements of government operations.

This instructor-led, live training in San Francisco (online or onsite) is designed for intermediate-level IT professionals and business managers who seek to understand the potential of IoT and edge computing for enhancing efficiency, enabling real-time processing, and fostering 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 significance in digital transformation for government and private sectors.
• Identify use cases for IoT and edge computing in manufacturing, logistics, and energy sectors, including applications for government operations.
• Differentiate between edge and cloud computing architectures and deployment scenarios suitable for government and enterprise environments.
• Implement edge computing solutions to support predictive maintenance and real-time decision-making in both public and private sector contexts.

Embedded systems are specialized computing devices designed to perform specific functions within larger systems. The Internet of Things (IoT) is a network of interconnected physical devices equipped with sensors and software that communicate and exchange data over the internet. This instructor-led, live training (available online or onsite) is tailored for beginner-level technical professionals who wish to understand and apply embedded systems and IoT concepts using C programming and microcontroller architectures. By the end of this training, participants will be able to: - Understand the architecture and components of embedded systems. - Write and compile C code for interacting with embedded hardware. - Work with microcontroller peripherals such as timers and analog-to-digital converters (ADCs). - Understand how embedded systems contribute to IoT architectures. **Format of the Course** - Interactive lecture and discussion - Numerous exercises and practice sessions - Hands-on implementation in a live-lab environment **Course Customization Options for Government** To request a customized training program for government use, please contact us to arrange.

The objective of the training is to provide an introduction to the realm of the Internet of Things (IoT) and blockchain technologies, highlighting both the benefits and challenges associated with these innovative solutions for government. Participants will gain a comprehensive understanding of how these technologies can be integrated into public sector workflows while maintaining governance and accountability standards.

The objective of this training is to provide a comprehensive understanding of 5G networks and their impact on smart technologies. We will explore both the benefits and challenges associated with the integration of 5G and Internet of Things (IoT) systems, as well as highlight the future directions of network development. From its inception, 5G has been tailored for government and the broader smart world, aiming to enhance connectivity and efficiency in various sectors.

The objective of this training is to clarify what constitutes smart solutions—such as the Internet of Things, Artificial Intelligence, Blockchain, Virtual Reality, and the Metaverse—and to distinguish them from non-smart technologies. The training will also highlight the benefits and drawbacks associated with these advanced technological domains, ensuring that participants are well-informed for government applications and decision-making processes.

This advanced course delves into the innovative realm of edge computing, providing a comprehensive exploration of sophisticated architectures and addressing integration challenges. Participants will gain the necessary skills to leverage the full potential of edge computing in various government environments. The curriculum focuses on developing expertise in cutting-edge tools and methodologies to deploy, manage, and optimize edge computing solutions that meet specific public sector needs for government.

Advances in technology and the proliferation of information are transforming how business is conducted across various industries, including operations for government. The rate of data generation and digital archiving within government agencies is increasing due to the rapid adoption of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As the volume and complexity of digital information grow, the challenges related to information management, processing, storage, security, and disposition also become more intricate. New capture, search, discovery, and analysis tools are enabling organizations to derive valuable insights from their unstructured data. The government market is at a critical juncture, recognizing that information is a strategic asset. Government entities need to protect, leverage, and analyze both structured and unstructured information to better serve the public and meet mission requirements. As leaders in government strive to evolve into data-driven organizations, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value solutions for government will be created through 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 to make better decisions by acting on patterns revealed through the analysis of large volumes of data—whether related or unrelated, structured or unstructured.

Achieving these outcomes requires more than just accumulating vast amounts of data. "Making sense of these volumes of Big Data necessitates cutting-edge tools and technologies that can analyze and extract useful knowledge from diverse streams of information," according to Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy.

The White House took a significant step in 2012 by establishing the National Big Data Research and Development Initiative. This initiative allocated more than $200 million to capitalize on the explosion of Big Data and the tools needed for its analysis.

The challenges posed by Big Data are as formidable as its promise is encouraging. Efficient data storage is one such challenge. Budget constraints require agencies to minimize per-megabyte storage costs while ensuring easy access to data for users. Backing up massive quantities of data further complicates this issue.

Effective data analysis presents another major challenge. Many agencies use commercial tools to sift through large datasets, identifying trends that can enhance operational efficiency. 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 enabling agencies to analyze their data effectively. For example, 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 aided medical researchers in identifying a link that can alert doctors to aortic aneurysms before they occur. It is also used for more routine tasks, such as filtering through resumes to connect job candidates with hiring managers.

Insurtech, also known as Digital Insurance, represents the integration of insurance with emerging technologies. In the realm of Insurtech, "digital insurers" leverage technological advancements to optimize their business and operational models, thereby reducing costs, enhancing customer experiences, and increasing operational agility.

This instructor-led training is designed to provide participants with a comprehensive understanding of the technologies, methodologies, and strategic mindset necessary for driving digital transformation within their organizations and across the industry. The training is specifically aimed at managers who need to grasp the broader implications, dispel common misconceptions, and initiate the development of an Insurtech strategy for government.

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

• Articulate the concept of Insurtech and its various components with clarity and precision
• Clearly define the role of each key technology within the Insurtech framework
• Develop a strategic plan for implementing Insurtech within their organization

Audience

• Insurance providers
• Technologists in the insurance sector
• Stakeholders in the insurance industry
• Consultants and business analysts

Format of the Course

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

This comprehensive course integrates the transformative power of artificial intelligence (AI) with the agility of edge computing. Participants will learn to deploy AI models directly on edge devices, covering topics from understanding convolutional neural network (CNN) architectures to mastering knowledge distillation and federated learning. This hands-on training is designed to equip professionals with the skills necessary to optimize AI performance for real-time processing and decision-making at the edge, ensuring alignment with public sector workflows and governance for government applications.

This instructor-led, live training (online or onsite) is aimed at product managers and developers who wish to utilize Edge Computing to decentralize data management for enhanced performance, leveraging smart devices located at the source network. This training aligns with public sector workflows and governance practices for government. By the end of this training, participants will be able to: - Understand the fundamental concepts and benefits of Edge Computing. - Identify use cases and examples where Edge Computing can be effectively applied. - Design and implement Edge Computing solutions to accelerate data processing and reduce operational costs.

Establish a robust foundation in designing and managing a resilient edge computing infrastructure for government. Gain insights into open hybrid cloud infrastructures, the management of workloads across multiple clouds, and the importance of flexibility and redundancy. This training offers critical knowledge on developing a scalable and secure infrastructure that supports the evolving needs of modern applications through edge computing.

This instructor-led, live training in [location] (onsite or remote) is aimed at engineers who wish to set up, deploy, and manage a secure IoT application for government. By the end of this training, participants will be able to: - Develop and deploy applications to securely manage IoT devices. - Integrate IoT devices with the Cloud in a secure manner. - Seamlessly integrate an IoT application with existing government infrastructure.

The 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) enhances user experience by integrating virtual, computer-generated elements with the real-world environment, providing users with a real-time view of information. These technologies have seen rapid adoption across various industries.

In this instructor-led, live training, participants will gain an understanding of the fundamentals of IoT and AR and explore how these technologies can be applied to enhance operations and strategies within their organizations for government.

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

• Understand the core principles of IoT and AR
• Learn how IoT and AR technologies function
• Apply IoT and AR technologies to their organization's strategic goals
• Make informed decisions regarding the implementation of IoT and AR in their business

Audience

• Managers
• Entrepreneurs

Format of the Course

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

Note

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

In this instructor-led, live training for government participants in [location], attendees will gain a foundational understanding of the Internet of Things (IoT) as they work through the development of an Arduino-based IoT sensor system. By the end of this training, participants will be able to: - Comprehend the core principles of IoT, including its components and communication methods. - Utilize various Arduino communication modules suitable for different IoT applications. - Develop and program a mobile application to control Arduino devices. - Integrate a Wi-Fi module to establish connectivity between Arduino and other devices. - Construct and deploy their own IoT Sensor System tailored for government use.

The Internet of Things (IoT) is a network infrastructure that connects physical devices and software applications wirelessly, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Azure provides a comprehensive set of cloud services, including an IoT Suite with preconfigured solutions designed to help developers accelerate the development of IoT projects for government. In this instructor-led, live training, participants will learn how to develop IoT applications using Azure for government. 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 for government. - 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 for government. **Audience** - Developers - Engineers **Format of the Course** - Part lecture, part discussion, exercises, and extensive hands-on practice **Note** To request a customized training for this course, please contact us to arrange.

The Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, 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 due to its widespread use and low-level programming capabilities. In this instructor-led, live training, participants will learn how to program 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** - Part lecture, part discussion, exercises, and extensive hands-on practice **Note** To request a customized training for government or other organizations, please contact us to arrange.

This practical, hands-on course offers a comprehensive introduction to the Internet of Things (IoT), covering device-level programming to cloud-based data processing and visualization. Participants will delve into the full IoT architecture—sensors, communication protocols, microcontrollers, and cloud integration—through guided exercises using development boards such as ESP32 and Raspberry Pi. By the end of the course, learners will be equipped to construct a complete IoT pipeline: collecting sensor data, transmitting it via MQTT/HTTP, processing it on cloud platforms like Azure IoT Hub, AWS IoT Core, or Google Cloud IoT, and visualizing it with tools such as Grafana or Power BI. The curriculum also emphasizes security best practices and simulates cyber threats to ensure robust and secure deployments for government and other critical sectors.

Unlike other technologies, the Internet of Things (IoT) is far more complex, encompassing a broad range of core engineering disciplines, including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each layer of IoT engineering involves various aspects of economics, standards, regulations, and the evolving state of the art. For government and other sectors, this advanced course offers a comprehensive overview of these critical IoT engineering aspects.

Summary

An advanced training program covering the current state of the art in Internet of Things (IoT) technology. This program cuts across multiple technology domains to develop awareness of an IoT system and its components, highlighting how it can benefit businesses and organizations.

The course includes live demonstrations of model IoT applications, showcasing practical IoT deployments across different industry sectors such as Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases involving connected devices and things.

Target Audience

This training is designed for managers responsible for business and operational processes within their respective organizations who want to understand how to leverage IoT to enhance system and process efficiency. It is also suitable for entrepreneurs and investors looking to build new ventures and seeking a better understanding of the IoT technology landscape to effectively utilize it.

Estimates for the value of the Internet of Things (IoT) market are substantial, given that 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 expected to grow from 1.9 billion today to 9 billion by 2018, roughly equaling the combined total 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 systems, lighting and heating products, and various applications in the Industrial Internet. While the underlying technologies of IoT are not new, as machine-to-machine (M2M) communication has existed since the birth of the internet, recent advancements include the emergence of inexpensive wireless technologies and widespread adoption of smartphones and tablets. The explosive growth of mobile devices has driven the current demand for IoT.

Due to the vast opportunities in the IoT business, a significant number of small and medium-sized enterprises have entered the market. The availability of open-source electronics and IoT platforms has made the development and management of IoT systems more affordable. Existing electronic product owners are also under pressure to integrate their devices with the internet or mobile apps.

The primary objective of this training is to provide a technology and business review of the emerging IoT industry, enabling enthusiasts and entrepreneurs to grasp the basics of IoT technology and its business applications.

Course Objective

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

Key topics covered include:

• 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.
• M2M wireless protocols for IoT, including WiFi, Zigbee/Zwave, Bluetooth, ANT+: Understanding when and where to use each protocol.
• Mobile/Desktop/Web app development for registration, data acquisition, and control, along with available M2M data acquisition platforms like Xively, Omega, and NovoTech.
• Security issues and solutions specific to IoT.
• Open-source and commercial electronics platforms for IoT, such as Raspberry Pi, Arduino, and ArmMbedLPC.
• Open-source and commercial enterprise cloud platforms for IoT, including AWS-IoT apps, Azure-IOT, Watson-IOT cloud, and other minor IoT clouds.
• Case studies of business and technology in common IoT devices like home automation systems, smoke alarms, vehicles, military applications, and home health solutions.

The Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Java, a general-purpose language known for its "write once, run anywhere" capability, is highly recommended for IoT due to its portability and efficiency. This instructor-led, live training aims to equip participants with the skills necessary to program IoT solutions using Java. By the end of this training, participants will be able to: - Install and configure tools and frameworks (Eclipse Open IoT Stack) for programming IoT systems with Java. - Understand the fundamentals of IoT architecture. - Utilize the Eclipse Open IoT Stack for Java to connect and manage devices in an IoT solution. - Build, test, and deploy an IoT system using Java. **Audience** - Developers - Engineers **Format of the Course** - Part lecture, part discussion, exercises, and extensive hands-on practice. **Note** To request a customized training for government or other specific needs, please contact us to arrange.

Unlike other technologies, the Internet of Things (IoT) is notably more complex, encompassing a wide range of engineering disciplines such as Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each layer of IoT engineering involves aspects of economics, standards, regulations, and the evolving state of the art. For government and other sectors, this course provides a comprehensive overview of these critical aspects of IoT Engineering.

For professionals in manufacturing, understanding advancements in the Industrial Internet of Things (IIoT) is crucial. This includes predictive and preventative 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 covering the latest advancements in IoT for smart factories.
• Crosses multiple technology domains to develop awareness of an IoT system and its components, and how it 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 wish to understand how to leverage IoT to enhance system and process efficiency.

Duration 3 Days (8 hours/day)

Estimates of the market value for Internet of Things (IoT) are substantial, as by definition, 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 IoT connections was projected to reach 9 billion, roughly equivalent 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 the IoT domain, including kitchen and home appliances, parking solutions, RFID systems, lighting and heating controls, and various Industrial Internet applications.

While the underlying technologies of IoT are not new—machine-to-machine (M2M) communication has existed since the inception of the internet—the recent surge in inexpensive wireless technologies and the widespread adoption of smartphones and tablets have driven current demand for IoT. The rapid growth of mobile devices has significantly contributed to the present demand for IoT.

Industrial IoT, or IIoT for manufacturing, has been widely adopted since 2014, with numerous innovations occurring in this field. This course will introduce all important aspects of these innovations in the Industrial IoT area.

The training aims to provide a technology and business overview of an emerging industry, enabling IoT enthusiasts and entrepreneurs to grasp the basics 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. Analysis of the business and technology aspects of common IIoT platforms like Siemens MindSphere and Azure IoT.
2. Exploration of open-source and commercial enterprise cloud platforms such as AWS-IoT, Azure-IoT, Watson-IoT, Mindsphere IIoT cloud, and other minor IoT clouds.
3. Overview of open-source and commercial electronics platforms for IoT, including Raspberry Pi, Arduino, and ArmMbedLPC.
4. Discussion of security issues and solutions for IIoT.
5. Development of mobile/desktop/web applications for registration, data acquisition, and control.
6. Examination of M2M wireless protocols for IoT, including WiFi, LoPan, BLE, Ethernet, Ethercat, PLC, with guidance on their appropriate use.
7. Basic introduction to all elements of IoT, covering 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 and exchange data through network communications, cloud computing, and data capture. Blockchain is a decentralized database system that stores information in ledgers distributed across multiple nodes. When blockchain technology is integrated with IoT, it facilitates the accessibility and supply of IoT data without the need for central control. This combination offers numerous new possibilities and significant benefits for business organizations. In this instructor-led, live training (remote), participants will learn how to leverage blockchain and IoT together as they engage in a series of hands-on, live-lab exercises. By the end of this training, participants will be able to: - Understand how blockchain and IoT can work together to provide solutions for their organization. - Explore various tools and resources to implement a blockchain-based IoT solution for government and other organizations. **Audience** - Developers - Managers **Format of the Course** - Part lecture, part discussion, exercises, and extensive hands-on practice. **Note** - To request a customized training for this course, please contact us to arrange.

Connected devices are transforming various sectors, and the power utility industry is no exception. Power utility companies face several challenges due to the growth of Internet of Things (IoT) technology.

1. Machines, controllers, Human-Machine Interfaces (HMIs), and Supervisory Control and Data Acquisition (SCADA) systems are increasingly becoming cloud-connected by vendors who promise enhanced analytics and insights for predictive and preventive maintenance. However, the quarantine policy for critical assets means that power companies cannot fully utilize these new IoT features offered by machine and controller vendors.
2. As the cost of solar and wind power continues to decline, utility companies will likely see a reduction in revenue from traditional power generation. To compensate for this loss, they must explore new revenue streams such as energy management services for homes, energy storage services, grid services for electric vehicle (EV) charging, and peer-to-peer (P2P) energy trading between homes, microgrids, and batteries. These services require smart metering, smart grids, and secure transactions facilitated by distributed ledger technology (DLT), such as IOTA. Additionally, utilities are investigating the provision of 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 detect and warn of any potential dangers, such as dam collapses or rockslides, in advance to ensure the safety of affected populations.
4. Another emerging revenue area is EV charging in parking facilities. IoT can facilitate smart charging and smart parking solutions, enhancing convenience and efficiency for users.

Over the past three years, significant advancements in IoT engineering have been driven by major technology companies like Microsoft, Google, and Amazon. These corporations have invested heavily to develop more manageable and secure IoT platforms. The rise of edge computing and the promise of 5G are transforming the IoT landscape, leading to substantial new research funding in this field. For practicing engineers, it is essential to understand the IoT platforms developed by major players such as AWS, Google, and especially Microsoft.

However, none of these platforms offer a comprehensive solution for scalable IoT deployments. Implementing smart metering across millions of homes, for example, requires additional technologies to secure meters, radio networks, and IoT management systems. The strategy, cost, and security of any IoT deployment must be optimized and acceptable. Given the interdisciplinary knowledge required, it is challenging for companies to assemble a team that can meet all these needs.

This course aims to educate key decision-makers, developers, and security experts about the challenges, risks, and practical approaches to deploying IoT for their next-generation power utility business.

Additionally, managing IoT services for thousands of sensors and connections is emerging as a distinct engineering discipline. Known as managed IoT services, this field is experiencing rapid growth due to the significant challenges associated with scalable IoT deployments, including over-the-top firmware/software updates, sensor calibration management, automated diagnosis of connection issues, root cause analysis of API failures, and tracking the health of distributed systems.

Course Objectives

The primary 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, structural health monitoring (SHM), power quality diagnosis, and smart contracts. It will also 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 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 Applications 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: 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 Standards for Smart Meters—IEC 62056
9. Distributed Ledger Technology (DLT) such as Blockchain, HyperLedger, and Directed Acyclic Graph (DAG) for smart contracts, P2P transactions, and smart car charging
10. IoT for Critical Infrastructure: Dams, Transformers, Substations, High Tension Wires

This course is designed to provide a comprehensive overview of the technological landscape and practical considerations for implementing IoT solutions in the power utility sector for government and industry stakeholders.

The Internet of Things (IoT) is a network infrastructure that connects physical devices and software applications through wireless communication, enabling them to exchange data via 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.

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:

• Comprehend the foundational principles of IoT architecture
• Familiarize themselves with the basics of using Raspberry Pi
• Install and configure Python on a Raspberry Pi device
• Understand the advantages of using Python in programming IoT systems for government applications
• Develop, 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 extensive hands-on practice

Note

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

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

In this instructor-led, live training, participants will gain a foundational understanding of IoT as they work through the process of creating an IoT sensor system using the Raspberry Pi.

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

• Understand the principles of IoT, including its components and communication techniques
• Learn how to configure the Raspberry Pi for IoT applications
• Design and deploy their own IoT Sensor System

Audience

• Hobbyists
• Hardware and software engineers and technicians
• Technical professionals from various industries
• Beginner developers

Format of the Course

• Part lecture, part discussion, with 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 as the programming language. To request a different setup, please contact us to arrange.
• Participants are responsible for purchasing the necessary Raspberry Pi hardware and components.

This training is designed to enhance technical skills and align with the needs of public sector workflows, governance, and accountability for government applications.

Over the past three years, engineering in the Internet of Things (IoT) has undergone significant changes, primarily driven by major technology companies such as Microsoft, Google, and Amazon. These corporations have invested substantial resources to develop more manageable and secure IoT platforms. Additionally, IoT edge computing has gained considerable traction in both research and deployment, becoming a critical component for practical IoT implementation. The advent of 5G technology is also poised to revolutionize the business landscape of IoT. This has resulted in a wide range of new areas of research funding in IoT.

However, the widespread adoption of IoT remains slow due to various security concerns. Securing firmware and gateways continues to be far from optimal. One significant issue is the lack of agreement among major IoT vendors on security standards. While Microsoft Azure and Amazon AWS have advanced their own security frameworks, NIST has proposed a more comprehensive approach. The OWASP model of 10 layers of IoT security had some impact but failed to gain widespread adoption due to resistance from major IoT platforms like Azure or Google.

Another critical area of concern is the security of firmware. Most firmware remains vulnerable to patching, whether through over-the-air (OTA) updates or via local hardware ports.

Course Objective

1. Provide an introduction to all technology stacks, data models, and vulnerabilities in IoT for government applications.
2. Illustrate the layers of vulnerability at each stack and between stacks.
3. Address vulnerabilities introduced by vendors and third-party devices.
4. Examine the NIST standard for IoT security.

In this instructor-led, live training for government, participants will gain a comprehensive understanding of Internet of Things (IoT) architectures and learn about the various IoT security solutions applicable to their organization. By the end of this training, participants will be able to: - Understand IoT architectures. - Identify emerging IoT security threats and solutions. - Implement appropriate technologies for IoT security within their organization.

This instructor-led, live training in San Francisco (online or onsite) is aimed at developers and programmers who wish to install, configure, and manage the Kaa platform to build IoT applications for government. By the end of this training, participants will be able to build, develop, manage, and implement IoT applications for smart devices and machines using Kaa, ensuring alignment with public sector workflows, governance, and accountability.

Machine-to-Machine (M2M) communication involves the automated exchange of data between interconnected mechanical and electronic devices. This technology is essential for government operations, enhancing efficiency and accuracy in various public sector workflows.

In this instructor-led, live training, participants will gain a comprehensive understanding of NB-IoT (also known as LTE Cat NB1) and develop and deploy a sample NB-IoT-based application. This training is designed to align with the needs and standards for government. By the end of this training, participants will be able to: - Identify the various components of NB-IoT and understand how they integrate to form an ecosystem. - Understand and articulate the security features inherent in NB-IoT devices. - Develop a simple application to track NB-IoT devices, enhancing operational efficiency and accountability for government.

In this instructor-led, live training in San Francisco, participants will learn how to optimize the performance of Nginx as they set up, configure, monitor, and troubleshoot Nginx for handling various forms of HTTP / TCP traffic. The course covers essential topics such as configuring key parameters in Nginx, optimizing the operating system, and fine-tuning virtual machine settings to achieve maximum efficiency and reliability for government use.

ThingsBoard is an open-source IoT platform designed to offer comprehensive device management, data collection, processing, and visualization capabilities for your IoT solutions.

In this instructor-led, live training, participants will learn how to integrate ThingsBoard into their IoT projects for government use.

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

• Install and configure ThingsBoard
• Understand the core features and architecture of ThingsBoard
• Develop IoT applications using ThingsBoard
• Integrate ThingsBoard with Kafka for efficient telemetry data routing from devices
• Integrate ThingsBoard with Apache Spark to aggregate and analyze data from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the Course

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

Note

• To request a customized training for government use, please contact us to arrange.