The term IoT can most likely be attributed to Kevin Ashton in 1997 with his work at Proctor and Gamble using RFID tags to manage supply chains. The work brought him to MIT in 1999 where he and a group of like-minded individuals started the Auto-ID center research consortium (for more information, visit http://www.smithsonianmag.com/innovation/kevin-ashton-describes-the-internet-of-things-180953749/). The concept of things being connected to the Internet up through 2012 was primarily connected smartphones, tablets, PCs, and laptops. Essentially, things that first functioned in all respects as a computer. Since the Internet starting with ARPANET in 1969, most of the technologies surrounding the IoT didn't exist. Up to the year 2000, most devices that were associated with the Internet were, as stated, computers of various sizes. Certainly, the term IoT has generated a lot of interest and hype. One can easily see that from a buzzword standpoint, the number of patents issued (https://www.uspto.gov) has grown exponentially since 2010. The number of Google searches (https://trends.google.com/trends/) and Picture 1, we can see IEEE peer-reviewed paper publications hit the knee of the curve in 2015.
Picture 1. Analysis of keyword searches for IoT, patents, and technical publications
You wake up Tuesday, September 17, 2030, around 6:30 AM, as you always do. Immediately after, your eyes open to a fantastic sunny morning as it's approaching 34 C outside. You will take part in a day that will be completely different than the morning of Wednesday, Septemper 17, 2020. 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 another 5 A.M. flight you would set it again, controlled by a cloud agent using 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 computer and a smartphone as your central device, but your world is based on using VR/AR Goggles since the screen is so much better and larger. You do have a fog 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 if there's been a fall or an accident in the house. The security system is being scanned for anomalies, such as 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 uses printable sensors, and monitors your heart rate and temperature. That data is streamed over Bluetooth Low Energy, BLE, to your smartphone simultaneously while you listen to Bluetooth audio streamed from your phone to your Bluetooth earphones. 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 mandated policies on a zero-emission office space. Each room has proximity sensors to detect not only if a room is occupied, but 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 automated shades, ceiling fans, even digital signage is 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 even 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 they also host a number of small-cell gateways internally to focus signals within the confines of the building. The internal 5G or 6G 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, NB-IoT, LoRaWAN or some else. 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 called the owner 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 than four 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 mid-day 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 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, such as 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 logs and trend analysis didn't pick up any abnormal behavior, and 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 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, and at first it was difficult to justify, but you think it may have paid for itself a thousandfold. 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.
While this fictional case may or may not be true, it's pretty close to reality today. The IoT is defined by wikipedia as 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. IBM tells that The Internet of Things, IoT, represents the whole way from collecting data, processing it, taking an action corresponding to the signification of this data to storing everything in the cloud. All this is made possible by the internet. Let's take sensors as an example, they collect data and send it to a processing device, which will perform the convenient actions. Then, the data will be stored locally and, by using the internet, it is subsequently sent out to the cloud. The problem here is that the data stored in the cloud is sometimes not useful. There is not enough local processing happening before data is saved in the cloud.
In a nutshell, the Internet of Things is the concept of connecting any device to the Internet and to other connected devices. The IoT is a giant network of connected things and people – all of which collect and share data about the way they are used and about the environment around them.
That includes an extraordinary number of objects of all shapes and sizes – from smart microwaves, which automatically cook your food for the right length of time, to self-driving cars, whose complex sensors detect objects in their path, to wearable fitness devices that measure your heart rate and the number of steps you’ve taken that day, then use that information to suggest exercise plans tailored to you. There are even connected footballs that can track how far and fast they are thrown and record those statistics via an app for future training purposes. How does it work?
Devices and objects with built in sensors are connected to an Internet of Things platform, which integrates data from the different devices and applies analytics to share the most valuable information with applications built to address specific needs.
These powerful IoT platforms can pinpoint exactly what information is useful and what can safely be ignored. This information can be used to detect patterns, make recommendations, and detect possible problems before they occur.
Let’s look at some examples and business areas to see what IoT, Internet of Things looks like in real life.
The industrial segment is one of the fastest-growing markets. Industrial IoT (IIoT) is one of the fastest and largest segments in the overall IoT space by the number of connected things and the value those services bring to manufacturing and factory automation. This makes hardware and software tools to monitor physical devices. Traditional information technology roles have been administered differently. The IT role will concentrate on security, groupings, data delivery, and services. As the IoT becomes prevalent in industry and manufacturing, these worlds will combine especially with predictive maintenance from thousands of factory and production machines to deliver an unprecedented amount of data to private and public cloud infrastructure.
Some of the characteristics of this segment include the need to provide near real-time or at real-time decisions for operations technology. This means latency is a major issue for IoT on a factory floor. Additionally, downtime and security are a top concern. This implies the need for redundancy, and possibly private cloud networks and data storage. Following are the main industrial and manufacturing IoT use cases and their impact:
Consumer-based devices were one of the first segments to adopt things being connected on the internet. Consumer IoT came into form as a connected coffee pot at a university in the 1990s. It flourished with the adoption of Bluetooth for consumer use in the early 2000s. Now millions of homes that have smart thermostats, smart lightbulbs, living assistants and smart door locking system . People too are connected e.g. with Apple Fitbits and other wearable technologies. The consumer market is usually first to adopt these new technologies. We can also think of these as gadgets. All are neatly packaged and wrapped devices that are essentially plug and play. Ecosystems have often emerged or grown around wearable technology, enabling more diverse services and applications for customers. The following are some of the main consumer IoT use cases:
This segment also has common traits in the healthcare market, with wearable devices and home health monitors. Here in Finland we have a lot of companies who develop smart home care and smart Iot system to health care need. One example is 9Solution Home care solution. Please visit this web-site https://9solutions.com/en/solutions/home-care-solution/ and watch this 3 minute video clip. https://9solutions.com/en/solutions/home-care-solution/
This category refers to any space where consumer-based commerce transacts. Additionally, this category refers to why we include financial institutions and marketing fields in this area. These include traditional banking services and insurers, but also leisure and hospitality services. Retail IoT impact is already in process, with the goal of lowering sales costs and improving customer experience. This is done with a countless amount of IoT tools.
This segment measures value in immediate financial transactions. If the IoT solution is not providing that response, its investment must be scrutinized. This drives constraints on finding new ways to either save costs, or drive revenue. Allowing customers to be more efficient allows retailers and service industries to move customers quickly, and to do so with less staffing resources.
Some of the retail IoT use cases are as follows:
Farming and environmental IoT includes elements of livestock health, land and soil analysis, micro-climate predictions, efficient water usage, and even disaster predictions in the case of geological and weather-related disasters. Even as the world population growth slows down, world economies are becoming more affluent. Hunger and starvation crises are rare. Food and Agriculture Organizatio (FAO) said, that the demand for food production is set to double by 2035. Significant efficiencies in agriculture can be achieved through IoT. Using smart lighting to adjust the spectrum frequency based on poultry age can increase growth rates and decrease stress on chicken farms. Other uses include detecting livestock health based on sensor movement and positioning. A cattle farm could find animals with the propensity of sickness before a bacterial or viral infection were to spread. Edge analysis systems could find, locate, and isolate heads of cattle in real time, using data analytics or machine learning approaches. Intelligent fertilization and irrigation systems increase grain yield and productivity.
Some of the agricultural and environmental IoT use cases are as follows:
The energy segment includes the monitoring of energy production at source to and through the usage energy at the client. A significant amount of research and development has focused on consumer and commercial energy monitors such as smart electric meters that communicate over low-power and e.g. LoRaWan long-range protocols to real-time energy usage.
Many energy production facilities are in remote or hostile environments such as desert regions for solar arrays, steep hillsides for wind farms, and hazardous facilities for nuclear reactors. Additionally, data may need real-time or near real-time response for critical response to energy production control systems. The following are some of the use cases for energy IoT:
Smart city is a phrase used to imply connecting intelligence to what had been an unconnected world. Smart cities are one of the fastest growing segments, and show substantial cost or benefit ratios especially when we consider tax revenues. Smart cities also touch citizens' lives through safety, security, and ease of use. For example, several cities are fully connected and monitor trash containers and bins for pickup based on the current capacity, but also the time since the last pickup. Smart cities are also impacted by government mandates and regulations, therefore there are ties to the government segment. One of the characteristics of smart city deployment may be the number of sensors used.
Some of the smart city IoT use cases are as follows:
Students, welcome to the world of the IoT. As an architect in this new field, we have to understand what the customer is building, and what the use cases require. IoT systems are not a fire-and-forget type of design. A customer expects several things from jumping on the IoT train.
First, there must be a positive reward. That is dependent on your business, and your customer's intent. Second, IoT design is, by nature, a plurality of devices. The value of IoT is not a single device or a single location broadcasting data to a server. It's a set of things broadcasting information and understanding the value the information in aggregate is trying to tell you. Whatever is designed must scale or will scale, therefore that needs attention in upfront design.
We now start exploring the topology of an IoT system and how to collect data, how to use data and how it is possible to make business using data. Remember, data is the new oil.