Is the hype about IoT justified?

With so many use cases benefitting nearly every industry, IoT’s momentum is accelerating. That makes IoT more than just the buzzword du jour: it is here to stay.

Four converging technology and economic forces are driving IoT’s growth:


The rapid decline in sensor prices over the past few years has made IoT-connected, condition-monitoring projects increasingly affordable. As shown in Table 1, the average price per device has declined nearly 20% from 2014 thru the end of 2017 and is expected to drop another 7% or so again this year; by 2020, average sensor prices will have dropped 42% compared to 2014, according to Gartner.

For industry, the decline has been particularly precipitous: sensor costs have already come down 31% in the past three years; and, through 2020, they’re predicted to drop another 38% — resulting in a price decline of more than 57% in just five years.

With lower prices comes increased demand. By the end of 2017, Gartner reports there were 8.4 billion IoT-connected devices, up 31% from 2016; and by 2020, Gartner predicts the internet will connect more than 20 billion “things”  [see Table 1].

TABLE 1 Actual and projected growth in the IoT sector, 2014 to 2020


We’ve all become so dependent on our smartphones that it’s hard to believe the iPhone only celebrated its tenth birthday last year. Since 2007, smart mobile devices — i.e., phones and tablets — have put information at our fingertips, enabling each of us to access, view, and respond anywhere, anytime.

Smart mobile devices may have made it easy and affordable for us to access the internet; however, until recently, getting data from your things (i.e., assets) to the internet remained difficult and expensive. Ten years ago, uploading sensor data to the internet required linking the sensor either to your LAN, or to a wireless- or cellular-connected gateway device. Connecting by LAN almost certainly involved running ethernet cables, integrating the sensors into SCADA, passing the measurements off to either middleware or a DMZ server, and finally posting your data online — often at great expense. Wireless, radio-frequency, and cellular connections reduced the cost of running wire, but required additional gateway devices capable of calling home with their data. In addition to the cost of the gateway device, many gateway devices required 120-Volt power — which may require adding new circuits. And to call home, these gateway devices required traditional cellular services, such as 3G, 4G, and LTE, that are energy hogs on a bits-transmitted-per-Watt basis — not to mention, the monthly service fee.

But today, advances in mobile technology, machine-to-machine (M2M) cellular services, and sensors themselves facilitate less expensive and more efficient IoT access. Today, many sensors come with embedded SIM cards, enabling them to call home without a gateway device.[1] Meanwhile, new cellular technologies and services have made phoning home much cheaper: Here in the United States, the predominant technology is LTE-M, or a low-powered version of 4G-LTE coverage designed specifically for M2M communications.[2] In addition to providing lower service fees and wider coverage, LTE-M’s power-saving (PSM) and extended discontinuous (eDRX) data reporting modes greatly extend battery life for those devices that only transmit data a few times a day[3] — enabling some IoT sensors to go up to 10 years without recharge.[4] Currently, AT&T and Verizon offer LTE-M service nationwide.[5]


Easy-to-connect, affordable sensors have — and will continue to — vastly increased data availability. According to Cisco, M2M data transmission reached two exabytes (EB; one billion gigabytes) per month in 2016 and is projected to grow seven-fold — to 14 EBs per month — by the end of the decade [see figure below].[6]

Not only is there a greater volume of data, but that data is more useful. IoT-connected sensors and mobile devices generate real-time data, providing insight into what happened between formerly interval-based inspections and transactions.

However, as Daniel Burrus put it in his 2014 wired article, “All the information gathered by all the sensors in the world isn’t worth very much if there isn’t an infrastructure in place to analyze it in real time.”[7] Cloud-based computing applications fill the gaps.

These cloud-based applications transform transmitted data into intelligence. By combining real-time, historical interval-based, and external data sources, IoT-connected, cloud-based applications analyze larger and more complete volumes of data than was previously possible—enabling you to understand and explore your assets in greater detail. Then, these applications integrate this valuable business information into your business processes — getting the right information to the right person, at the right time, right where they need it.

This connection between big data and cloud computing has initiated a virtuous cycle: cloud computing shows the usefulness — and therefore, value — in collecting data; and volumes of data create the need for more advanced cloud computing algorithms.


One-third of all workers are over age 50, with 2.7 million highly skilled Baby Boomers expected to retire by 2020.[8] However, there aren’t enough Gen X-ers, like me, waiting in the wings to fill all these positions, and that’s creating a large skills gap.

Many of these skilled positions took years to train the Boomer incumbents; for example, most electric utility linesmen apprenticed for seven years before reaching journeyman status.[9] We simply don’t have that much time to train Millennials to fill these vacancies — and that’s forcing innovation. Once again, IoT fills the gap.

IoT helps fill the skills gap in three ways: First, by continuously monitoring the health of your assets, condition-based maintenance helps asset-intensive firms extend their staff’s reach, enabling better maintenance outcomes with fewer workers.

Second, IoT’s anywhere, anytime connectivity enables young workers to connect with experts — whether senior engineers or maintenance staff at another site, or your retired predecessor on the golf course — in real time. Rather than just a phone call, IoT connectivity allows these experts to view performance data, webcams, and even a feed from your Google Glasses, to help troubleshoot issues and develop solutions.[10] Then, IoT-connected augmented reality enables these remote experts to guide the onsite worker through the procedure.[11]

Finally, IoT enables organizations to preserve critical operational and experiential knowledge before it walks out the door, then present that historical, scenario-specific, and experiential information in front of younger workers right when they need it. Cataloging the often-myriad forms of information that comprise “institutional knowledge” can be difficult — but IoT-enabled advanced analytics platforms, such as IBM Watson, make it easy to find the information and advice you need.[12] Some platforms will even connect this institutional knowledge directly to your work order;[13] for example, IBM reports Watson helped Woodside Energy reduce the time spent locating knowledge by 75%.[14]

These forces are creating virtuous cycles that will continue to drive us towards a more ubiquitous IoT future. The bottom line: embrace IoT or get left behind.

How will IoT benefit your organization? For more practical ways to use IoT to make smarter asset management decisions, email us at

[1] Sierra Wireless, “LTE-M & -NB: What you need to know before you start development,” 26 January 2018.

[2] Link Labs, “LTE-M & two other 3GPP IoT technologies to get familiar with,” 29 November 2017.

[3] Sierra Wireless, “LTE-M & -NB: What you need to know before you start development,” 26 January 2018.

[4] Sierra Wireless, “LTE-M & -NB: What you need to know before you start development,” 26 January 2018.

[5] GSMA “Deployment map: Internet of Things,” accessed 7 May 2018.

[6] Cisco, “The zettabyte era: trends & analysis,” June 2017.

[7] D. Burrus, “The Internet of Things is far bigger than anyone realizes,” Wired (November 2014).

[8] K. Lewis, “Cognitive solutions and surviving the crew change,” 12 May 2017.

[9] K. Lewis, “Cognitive solutions and surviving the crew change,” 12 May 2017.

[10] D. Newman, “Hyper-training and the future augmented-reality workplace,” Forbes, 20 September 2016.

[11] D. Newman, “Hyper-training and the future augmented-reality workplace,” Forbes, 20 September 2016.

[12] K. Lewis, “Cognitive solutions and surviving the crew change,” 12 May 2017.

[13] K. Lewis, “Cognitive solutions and surviving the crew change,” 12 May 2017.

[14] K. Lewis, “Cognitive energy with Woodside,” 27 April 2017.

Share This!