Simplifying Complex IoT Solutions
This is the second article in the Precision Construction series, which explores the application of the internet of things to digitally transform the construction industry, ultimately with the objective to improve labor productivity, reduce costs and enhance safety. Articles generally follow a five-layer framework, described in this article, that makes it easier to understand digital transformation solutions. The series began with Exploring Digital Transformation for Construction. Other articles in the series are: United Rentals Drives Efficiency & Excellence with IoT, United Rentals Helps Customers Optimize Equipment Rental, Robotic Masonry, Mixed Reality for Construction: Applicability and Reality, Taking Environmental Monitoring to a New Level and Digital Transformation – Enabling New Business Models for Construction. Articles generally follow a five-layer framework, described in Simplifying Complex IoT Solutions, that makes it easier to understand digital transformation solutions. To learn more about the various technologies described in this series, visit PrecisionStory.com.
No matter what it is called (digital transformation, telematics or the internet of things), the digitalization of traditional industries such as construction is much more than just the latest muse of marketing hype. IoT solutions deployed for business can lead to real improved business outcomes both for the builders of machines (e.g., scissor lifts), as well as the people who deploy these machines (e.g., contractors), for instance in terms of increased worker productivity, reduced costs and enhanced safety.
The first Precision Construction episode Exploring Digital Transformation for Construction discussed why digital transformation is so important for the construction industry.
That said, digital transformation or IoT solutions can be quite complex. The second episode outlines the Precision IoT Framework with the objective of simplifying the different components to these complex solutions. Then in later episodes, this framework is referenced as a number of real-world deployed solutions are explored.
Things are NOT People
A vast majority of the enterprise or consumer applications developed to date are for people—the Internet of People (IoP). Whether it’s CRM, ERP, HR, e-commerce or Facebook applications, they are all IoP applications. But Things are NOT people, so could it be that enterprise software developed for an Internet of People might not work as desired for an Internet of Things? There are a few important differences to consider.
Things can tell you more than people
People talk to applications primarily though a keyboard. Likewise, many applications use some kind of form to collect simple amounts of data from each of us. Things, on the other hand, can be equipped with many sensors, each generating data. A wind turbine, for instance, can have 200 sensors, delivering information such as wind speed and direction, blade-rotation, speed, power generated, component temperature, vibration, noise levels and more. Even a smart cellphone can have more than 10 sensors.
Things share data faster than people
The average person can type at 200 characters per minute. A coal-mining machine called a Longwall Shearer has artificial roof sensors that send data at 10,000 times per second. A phase measurement unit in a power grid can send data at 60 times per second without ever needing to take a coffee break.
Things can be programmed
Unlike People, Things can be programmed to do precisely what they are supposed to do under precise circumstances. This means that not only are Things generating a lot more data, but also this data might be something to collect and learn from en route to doing new behavior.
Things can exist in places where people don't
Whether deep in a coal mine shaft, in the ocean attached to an oil platform, or sitting in the desert, Things can exist on a 24x7 basis where people cannot. Things can generate data about entirely new environments, whereas IoP enterprise applications are stuck receiving human-entered data typed in one character at a time.
The potential ramification for these distinctions is that when considering which technologies to deploy in an IoT solution, understand whether the technology being deployed is built for IoT—and not IoP—applications.
Precision IoT Framework
At a high level, the Precision IoT Framework has five layers: Things, Connect, Collect, Learn and Do. First, there is the Thing or machine that is now Connected and providing data on both the machine itself and the environment around the machine. Then the data being provided has to be Collected somewhere (such as in the cloud) and this data analyzed so the buyer (e.g., digital contractor) can Learn insights and ultimately Do things differently than the status quo before deploying the digital transformation technology.
Enterprise Things, whether that’s a scissor lift, locomotive or water chiller, are becoming smarter and more connected. When building or buying next-generation machines, consider sensors, CPU architectures, operating systems, packaging and security. Sensors are beginning to follow Moore’s Law, becoming dramatically lower in cost every year. These sensors are increasingly attached to low-cost computers, which can range from simple microcontrollers to fully featured CPUs supporting either the ARM or Intel instruction set architecture. Moving to more powerful processors, more powerful software can be supported, and that software becomes the point of vulnerability in an increasingly hostile world.
Things can be connected to the Internet in a variety of ways, and doing so requires a diverse set of technologies based on the amount of data that needs to be transmitted, how far it needs to go, and how much power there is. Furthermore, there are many choices at a higher level on how to manage this connection and how it’s protected and secured.
Things aren’t people. The sheer volume of data that can be generated by Things will be exponentially larger than that of Internet of People (IoP) applications. Data might be collected and stored using SQL, NoSQL, traditional time-series, and next-generation, time-series collection architectures.
With an increasing amount of data coming from Things, it will be necessary to apply technology to learn from that data. Unlike in the world of IoP applications that had to entice users to type something, IoT applications will get data constantly, enabling users to learn from Things for the first time.
Learning and analysis products will include query technology and both supervised and unsupervised machine-learning technologies. Because the industry has mostly focused on IoP applications, much of the existing available technology was developed to learn from data streams about people. As a consequence, there is room for future innovation.
As it was with IoP applications, there will be both packaged applications (e.g., ERP, CRM) and middleware to build IoT applications. Of course, these applications—whether bought or built—have to ultimately drive business outcomes. As machines become increasingly complex and enabled by software, many of the lessons learned in software maintenance and service will also apply to a machine service. And as many in software already know, the movement to delivering software as a service has revolutionized the industry. So why not anticipate the opportunity for construction as a service offering to soon hit the market?
The next Precision Construction episodes will apply this Precision IoT Framework—Things, Connect, Collect, Learn and Do—to help discuss real world digital transformation solutions being applied for construction. For a deeper dive into the subject, check out Precision Construction, which is for business and technology oriented people who are truly interested in how to digitally transform their companies. To access hundreds of Digital Construction stories, subscribe to PrecisionStory.com. The application is scheduled to launch by March 2019 and is free to subscribe.
Vince Vasquez has more than 30 years of experience in enterprise sales, marketing and engineering. Working with 20 industry leaders, he is the co-author of Precision Construction, which teaches the fundamentals of IoT with a focus on the construction industry. He is also the co-founder and CEO of PrecisionStory, which brings Precision Storytelling—a new and innovative approach to enterprise storytelling—to market. Vince has an MBA from Stanford University, an MS in Computer Engineering from Carnegie-Mellon University and a BS in Electrical Engineering and Computer Science from the University of California, Berkeley.