Module 1, IoT and Edge Computing Definition and Use Cases.

We begin this training course with an overall understanding of the IoT and edge market and separate hype from reality. We define IoT and edge computing and then uncover various use cases for enterprise, commercial, and industrial IoT solutions. We end the Module with a case study to provide a full system architectural understanding and breakdown of a typical IoT system, from hardware to software to cloud

 

Module 2, IoT Architecture and Core IoT Modules.

 

This Module provides a high-level view and the breadth of the components and interconnects required to build an IoT or edge system. It will illustrate how the various components are interconnected and what roles they play. Additionally, this Module will uncover how IoT deployments should be modelled from a value and monetization point of view.

 

 Module 3, Sensors, Endpoints, and Power Systems.

 

Data begins its journey in IoT and edge computing at the sensors and physical devices. Here, we teach the various types of sensors and the physics that govern their abilities. We will show how sensors capture data and images and how they are powered when constant power sources are not available.

 

 Module 4, Communications and Information Theory.

 

To understand many of the constraints and capabilities of wireless communication, we begin with the theory of communication and wireless radio signaling. We explore concepts such as path loss, RF interference, the Shannon-Hartley theorem, and bit-rate limits. We also look at RF spectrum governance and distribution.

 

 Module 5, Non-IP Based WPAN.

 

Personal area networks include devices and systems that are near-range and have short distances between transmitters and receivers. This Module goes into the breadth and depth of various protocols such as Bluetooth 5.1, Bluetooth beaconing, direction-finding technologies, and Bluetooth 5.0 mesh networking. We also explore other 802.15.4 protocols such as Zigbee and end with a treatment of Z-Wave.

 

 Module 6, IP-Based WPAN and WLAN.

 

This Module explores the use of TCP/IPbased communication for near-range and long-range communication. We explore architectures such as 6LoWPAN, Thread, and various 802.11 Wi-Fi protocols such as 802.11ac, 802.11p, and 802.11ah.

  

Module 7, Long-Range Communication Systems and Protocols (WAN).

 

Long-range communication is a prerequisite for moving data from the remote edge to where data centers, customers, and consumers are located. This Module presents a thorough knowledge of long-range protocols, including the 4G LTE cellular and the new 5G cellular standards. We also explore alternative long-rang technologies such as CBRS, LoRa, Sigfox, and Multefire. We dive deep into how the technologies work and the features they offer in building a system.

  

Module 8, Edge Computing.

 

This Module analyzes the hardware and software components needed to build edge-level computing infrastructures. This includes a deep understanding of hardware resources: processor architecture, memory, storage, physical enclosures, environmental hardening, and interconnects. It also examines software frameworks, operating systems, and middleware. Additionally, we study the use of virtualization and containers for edge management (including examples of Microsoft Azure IoT Edge).

 

Module 9, Edge Routing and Networking.

 

A common use of an edge system is to provide gateway, routing, and network security functions. This Module teaches the methods of PAN-to-WAN bridging, cellular gateway functions, routing and traffic shaping, as well as security aspects such as software-defined networking and VPNs.

  

Module 10, Edge to Cloud Protocols.

 

This Module explores the various methods and features of edge to cloud protocols over wide area networks such as MQTT 5, CoAP, AMQP, and HTTP as standard methods for data transport.

  

Module 11, Cloud and Fog Topologies.

 

There are many ways to architect and partition a problem between cloud systems and edge systems. This Module presents the reader with various edge frameworks such as EdgeX and OpenFog, as well as lambda architectures, to build a more robust system.

 

 Module 12, Data Analytics and Machine Learning in the Cloud and Edge.

 

This Module provides the architect with an understanding of how to extract meaningful data from sensors and IoT systems. Data without understanding is useless. Here, we explore edge and cloud-based analytics using rules engines, statistical analysis, and various artificial intelligence and machine learning techniques. We explore where the correct analytics apply to the problem and dive deep into the mechanics of these tools.

 

 Module 13, IoT and Edge Security.

 

Security is paramount to a robust enterprise and industrial IoT and edge solution. We examine security from a holistic point of view in this Module. We look at physical, network, and data security from sensor to cloud.

 

 Module 14, Consortiums and Communities.

 

Industry consortiums and professional societies provide many of the standards and guidelines that are necessary to bridge IoT and edge systems together. This Module captures many relevant industry groups to consider following and joining when designing a system. We also present a list of recommended and commercially deployed sensor, hardware, and software systems that have proven to meet the requirements of commercial, enterprise, and industrial IoT.