Book Image

IoT and Edge Computing for Architects - Second Edition

By : Perry Lea
Book Image

IoT and Edge Computing for Architects - Second Edition

By: Perry Lea

Overview of this book

Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is needed if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of IoT devices. IoT and Edge Computing for Architects, Second Edition encompasses the entire spectrum of IoT solutions, from IoT sensors to the cloud. It examines modern sensor systems, focusing on their power and functionality. It also looks at communication theory, paying close attention to near-range PAN, including the new Bluetooth® 5.0 specification and mesh networks. Then, the book explores IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, Sigfox, and LoRaWAN. It also explains edge computing, routing and gateways, and their role in fog computing, as well as the messaging protocols of MQTT 5.0 and CoAP. With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. The book wraps up the analytics portion with the application of statistical analysis, complex event processing, and deep learning models. The book then concludes by providing a holistic view of IoT security, cryptography, and shell security in addition to software-defined perimeters and blockchains.
Table of Contents (17 chapters)
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IoT and Edge Computing Definition and Use Cases

You wake up Tuesday, May 17, 2022, around 6:30 A.M. PST, as you always do. You never really needed an alarm clock. You are one of those types with some form of physiological clock. Your eyes open to a fantastic sunny morning as it's approaching 70°F outside. You will take part in a day that will be completely different than the morning of Wednesday, May 17, 2017. Everything about your day, your lifestyle, your health, your finances, your work, your commute, even your parking spot will be different. Everything about the world you live in will be different: energy, healthcare, farming, manufacturing, logistics, mass transit, environment, security, shopping, and even clothing. This is the impact of connecting ordinary objects to the Internet, or the Internet of Things (IoT). I think a better analogy is the Internet of Everything.

Before you even awakened, a lot has happened in the IoT that surrounds you. Your sleep behavior has been monitored by a sleep sensor or smart pillow. Data was sent to an IoT gateway and then streamed to a cloud service you use for free that reports to a dashboard on your phone. You don't need an alarm clock, but if you had a 5 A.M. flight, you would set it—again, controlled by a cloud agent using the if this, then that (IFTTT) protocol. Your dual-zone furnace is connected to a different cloud provider and is on your home 802.11 Wi-Fi, as are your smoke alarms, doorbell, irrigation systems, garage door, surveillance cameras, and security system. Your dog is chipped with a proximity sensor using an energy harvesting source that lets him open the doggy door and tell you where he is.

You don't really have a PC anymore. You certainly have a tablet-style computer and a smartphone as your central creation device, but your world is based on using a VR/AR headset since the screen is so much better and larger. You do have an edge computing gateway in your closet. It's connected to a 5G service provider to get you on the Internet and WAN because wired connections don't work for your lifestyle—you are mobile, connected, and online no matter where you are, and 5G and your favorite carrier make sure your experience is great in a hotel room in Miami or your home in Boise, Idaho. The gateway also performs a lot of actions in your home for you, such as processing video streams from those webcams to detect whether there's been a fall or an accident in the house. The security system is being scanned for anomalies (strange noises, possible water leaks, lights being left on, your dog chewing on the furniture again). The edge node also acts as your home hub, backing up your phone daily because you have a tendency to break them, and serves as your private cloud even though you know nothing about cloud services.

You ride your bike to the office. Your bike jersey uses printable sensors and monitors your heart rate and temperature. That data is streamed over Bluetooth Low Energy to your smartphone simultaneously while you listen to Bluetooth audio streamed from your phone to your Bluetooth earphones. On the way there, you pass several billboards all displaying video and real-time ads. You stop at your local coffee shop, and there is a digital signage display out front calling you out by name and asking if you want the last thing you ordered yesterday: a 12 oz Americano with room for cream. It did this by a beacon and gateway recognizing your presence within five feet and approaching the display. You select yes, of course. Most people arrive at work via their car and are directed to the optimal parking space via smart sensors in each parking slot. You, of course, get the optimal parking space right out front with the rest of the cyclists.

Your office is part of a green energy program. Corporate policies mandate a zero-emission office space. Each room has proximity sensors to detect not only whether a room is occupied, but also who is in the room. Your name badge to get in the office is a beaconing device on a 10-year battery. Your presence is known once you enter the door. Lights, HVAC, automated shades, ceiling fans, even digital signage are connected. A central fog node monitors all the building information and syncs it to a cloud host. A rules engine has been implemented to make real-time decisions based on occupancy, time of day, and the season of the year, as well as inside and outside temperatures. Environmental conditions are ramped up or down to maximize energy utilization. There are sensors on the main breakers listening to the patterns of energy and making a decision on the fog nodes if there are strange patterns of energy usage that need examination.

It does all this with several real-time streaming edge analytics and machine learning algorithms that have been trained on the cloud and pushed to the edge.

The office hosts a 5G small cell to communicate externally to the upstream carrier, but it also hosts a number of small-cell gateways internally to focus signals within the confines of the building. The internal 5G acts as a LAN as well.

Your phone and tablet have switched to the internal 5G signal, and you switch on your software-defined network overlay and are instantly on the corporate LAN. Your smartphone does a lot of work for you; it is essentially your personal gateway to your own personal area network surrounding your body. You drop into your first meeting today, but your co-worker isn't there and arrives a few minutes late. He apologizes but explains his drive to work was eventful.

His newer car informed the manufacturer of a pattern of anomalies in the compressor and turbocharger. The manufacturer was immediately informed of this, and a representative called your co-worker to inform him that the vehicle has a 70 percent chance of having a failed turbo within two days of his typical commute. They scheduled an appointment with the dealership and have the new parts arriving to fix the compressor. This saved him considerable cost in replacing the turbo and a lot of aggravation.

For lunch, the team decides to go out to a new fish taco place downtown. A group of four of you manage your way into a coupe more comfortable for two and make your way. Unfortunately, you'll have to park in one of the more expensive parking structures.

Parking rates are dynamic and follow a supply-and-demand basis. Because of some events and how full the lots are, the rates doubled even for midday Tuesday. On the bright side, the same systems raising the parking fees also inform your car and smartphone exactly which lots and which space to drive to. You punch in the fish taco address, the lot and capacity pop up, and you reserve a spot before you arrive. The car approaches the gate, which identifies your phone signature, license plate, or a combination of multiple factors and opens up. You drive to the spot, and the application registers with the parking cloud that you are in the right spot over the correct sensor.

That afternoon, you need to go to the manufacturing site on the other side of town. It's a typical factory environment: several injection molding machines, pick-and-place devices, packaging machines, and all the supporting infrastructure. Recently, the quality of the product has been slipping. The final product has joint connection problems and is cosmetically inferior to last month's lot. After arriving at the site, you talk to the manager and inspect the site. Everything appears normal, but the quality certainly has been marginalized. The two of you meet and bring up the dashboards of the factory floor.

The system uses a number of sensors (vibration, temperature, speed, vision, and tracking beacons) to monitor the floor. The data is accumulated and visualized in real time. There are a number of predictive maintenance algorithms watching the various devices for signs of wear and error. That information is streamed to the equipment manufacturer and your team as well. The manufacturing automation and diagnostics logs didn't pick up any abnormal patterns, as they had been trained by your best experts. This looks like the type of problem that would turn hours into weeks and force the best and brightest in your organization to attend expensive daily SWOT (strengths, weaknesses, opportunities, and threats) team meetings. However, you have a lot of data. All the data from the factory floor is preserved in a long-term storage database. There was a cost to that service. At first, the cost was difficult to justify, but now you believe it may have paid for itself a thousand-fold. Taking all that historical data through a complex event processor and analytics package, you quickly develop a set of rules that model the quality of your failing parts. Working backward to the events that led to the failures, you realize it is not a point failure, but has several aspects:

  • The internal temperature of the working space rose 2°C to conserve energy for the summer months.
  • The assembly slowed down output by 1.5 percent due to supply issues.
  • One of the molding machines was nearing a predictive maintenance period, and the temperature and assembly speed pushed its failing case over the predicted value.

You found the issue and retrained the predictive maintenance models with the new parameters to catch this case in the future. Overall, not a bad day at work.

While this fictional case may or may not be true, it's pretty close to reality today. Wikipedia defines the IoT this way: The Internet of things (IoT) is the inter-networking of physical devices, vehicles (also referred to as "connected devices" and "smart devices"), buildings, and other items embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data. (