5 Lessons From Early IoT Enterprise Adopters

At Untrite, we’re dealing with many midsize and big companies in retail, hospitality, telecom, wellness and property industries. All of them recognise the importance of implementing emerging technology to stay ahead, yet most are unsure how to prioritise and plan innovation strategy. Many businesses are still unclear on just how and to what extend current IoT solutions can help. They see some cool new technology but are unclear on how it fits their business goals. Also, because IOT represents a new class of machine-generated image and technical data, it isn’t clear to them what platforms are required to manage it. How will it be aggregated and then absorbed into existing applications and systems?  And, of course, universal questions arise around security, business rules, regulatory compliance and analytical tools.

We spoke to a number of IoT advocates and early IoT adopters, entities that have gotten their hands dirty in everything from manufacturing, retail and logistics to smart cities and agriculture. Almost all reported bumps along the way, but also say they have either achieved or anticipate significant payoffs from their investment. E.g. DeepMind (Google) — company well-known for its innovative technology said that they’ve implemented intelligent sensors and as result lowered ~15 percent of the power usage in the data centers, which is a huge saving in terms of cost but also great for the environment.That’s why we decided to make things a bit clearer for these company CTOs/heads of tech who don’t know where to start. With IoT at last becoming a force in the enterprise, here are five lessons to take into consideration:

Lesson №1: Prepare for a deluge of data

Even as consumers have been mostly skeptical of the value, industrial IOT has spread quickly. Although it’s in early stages, impacts are being made across multiple business sectors, and it’s big money. Gartner estimates IOT services spending in the range of $235 billion by the end of 2016. That means enormous and constant waves of new data. Initially, that data will be used to improve internal business efficiencies. But, going forward, it is quickly expected to help create new services and new revenues streams supported by all that data from IOT devices. So, where will all the data go? How will it be managed? How long must it be stored and where?

Our first example — ARI’s Powell, acknowledges that the technology his company used even as recently as five years ago was “very immature,” limited in some cases to GPS data.

“Originally, it was just bread crumbs. We could see on a map a vehicle’s movements for the previous five days. Now that data is collected every 30 seconds. “The amount of data has become more like a fire hydrant.”
In Powell’s opinion, data is perhaps the biggest issue that CIOs have to deal with.
“Don’t underestimate the volume of information,” he warns. “People think, ‘If I collect the info, I’ll have an epiphany of business value.’ That’s not the case. You may be able to do that with lower volumes of info, but you’ll drown if you try it with telematics. Don’t collect data just because you can. Push the business logic [as close to the sensor] as you can.”

Jon Dunsdon, CTO of Evendale, Ohio-based GE Aviation, concurs. His company has been monitoring data on jet engines for 20 years. One of the challenges is that very few aircraft stream data continuously.

“You do the initial analysis onboard, and then when you land, you transmit the information. Ten years ago, it might have been 3.2 kilobytes of information; today, hundreds of megabytes come in when the plane lands. At the same time it’s collecting information from the aircraft, GE Aviation is also compiling other data to create additional value for its customers, which include United Airlines and Southwest Airlines. We look at things like scheduling data, weather data, airport curfews. If there’s a storm in Chicago, how does that affect decisions? How can you reduce cost and disruption?”

GE Aviation deploys a data lake to accommodate the volume of analytics and increase performance and recommends fellow IT executives consider the same.

Another aviation company Virgin Atlantic are also investing in IoT with hopes for a significant increase in data creation — a new fleet of highly connected planes each is expected to create over half a terabyte of data per flight. IoT can help reporting the maintenance problems before they even arise. If there is a problem with one of the engines we will know before it lands to make sure that we have the parts there. It is getting to the point where each different part of the plane is telling the engineers what it is doing as the flight is going on.
The above projects would not have been possible without the ability to combine unstructured and structured data. It was not economically viable to do these kinds of calculations and analysis few years ago, but at the current times IoT technology is rapidly evolving.

Takeaway:
Understand where data is coming from, and determine how you’re going to analyse it. Don’t jump into technology without first defining the problem you want to solve. Once the potential business value is clear, you get to figure out how you’ll deal with management, security and value creation from all that new data.

Lesson №2: Start liking working with multiple vendors

Given the significant role that communications play in IoT, many companies form strategic partnerships e.g telecom firms often play a key role in making it real. A major airline partnered with the firm that already provided all the telecom services for their main national airport, and got a great deal coupled with faster implementation. It’s worth noting that the right partner may not always be obvious — a railway may have lots of spare “dark fibre” already laid in their right-of-ways, which may be a better deal for connecting to rural locations. Another very common form of partnership is seen with utilities: Bob Bennett, chief innovation officer for the City of Kansas City, is working with Sprint, Cisco and other vendors on a $20 million pilot projectalong a 3.2-mile downtown streetcar line.

“I need to know where people are flowing through the cityscape. I need to know where concentrations of people are located dynamically, so I can react with police resources or utility resources,” says Bennett. “If there’s a surge in water usage without a corresponding number of people, that may indicate a water leak.”

The project combines data from street sensors, streetlight cameras and even mobile phones, flowing into 328 access points along the route and as much as five blocks on either side of the streetcar tracks. In accommodating both technical and operational data, he cites the need to understand from a high level to a highly granular level.

Takeaway: Canvas the landscape, literally, to find the best solution, and carefully choose partners all up and down the stack, including cloud, containers, software frameworks, and implementation services.

Lesson №3: Watch for pitfalls & physical limitations

Don’t forget that things achieved with IoT always need to obey the laws of physics. Time and the details of making an IoT implementation work in the real world come down to experimenting with real devices and connectivity options in the physical environment context:

  • In the consumer or clinical context it requires working around human factors (a.ka. ergonomics).
  • In the industrial context it requires engineering around the properties of antennas, interference, access to power and communications, battery life, form factors, ruggedness, safety in explosive environments, and other constraints.

This brings us to the next major lesson: pitfalls resulting from technology fragmentation. Some early IoT adopters have reported reliability issues with either sensors or vendors or both, and others have struggled to reconcile competing protocols.

Ken Albert, founder of Shelburne Vineyard took advantage of a prototype sensor system to monitor temperature, humidity, soil temperature and leaf wetness, all of which would help his staff apply fungicides more efficiently. But then the company providing the sensors was acquired, and the new owner began to redesign its sensors and stopped supporting the ones in Shelburne’s 17-acre vineyard.

“Even before that, however, the system was less reliable than I thought it would be, in part due to wireless connectivity issues”.

Albert acknowledged that exposure to the environment probably contributed to the downtime, but that’s to be expected in agriculture. While practitioners like Albert are out in the field (literally), industry watchers are often behind a computer screen, lamenting the proliferation of communications protocols that are fragmenting the nascent market. Consider multiple subsets of Wi-Fi, such as 802.11ad (a.k.a Wi-Gig) and 802.11ah (sub-1GHz); Bluetooth Mesh; Zigbee (some versions of which aren’t backward compatible); Z-Wave; and LoRa (for long-range); as well as Sigfox, a proprietary protocol for IoT.

A lot of these products are double-enabled with Wi-Fi and Bluetooth, hence it’s possible to breach networks via a Bluetooth signal and then get into the Wi-Fi network.

Takeaway: Build time and resourcing into your project for working out these details enough up front, while being prepared to learn and iterate. If you’re pushing the boundaries of the possible (we are still waiting for the demo of uBeam, Meredith…) be sure to manage the risks explicitly as part of your Sprint schedule. Be prepared for setbacks in an immature market, and try to select a protocol that has long-term industry support and a sound security footprint.

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Lesson №4: Partner with the operations

IoT incorporates multiple technologies and work streams— wireless networks, sensors, analytics, security — that encompass not just IT but also operations, particularly factories, equipment and logistics. Hence, it’s crucial that IoT projects inherently reach communication alignment of business and IT.

In the past, operations technology was done by external team. Today, every piece of production equipment is usually designed and implemented by an engineering group — it’s not something you buy off-the-shelf. With IoT, to get the data from the equipment, business divisions have to work shoulder-to-shoulder with engineering.

“There has to be collaboration between technology and operations to make IoT work. That’s where you unlock the business value,” agrees Chris Howell, head of business systems at Gatwick Airport outside London. In addition, he says, you need people who can handle a deluge of data, whether internal data scientists or an external partner who understands big data and analytics.

Howell uses tools from Splunk and Amadeus to keep track of where planes are on the field.
Company’s goal? – operational efficiency.
Although it deployed a number of IoT-based systems, including self-service check-in and baggage tagging, in the last two years, Gatwick’s crown jewel is a laser-guided system on the field. It takes transponder data from the plane and tracks where it is on the ground, how long it takes to get to the gate and when it leaves again.
This helps Gatwick calculate how long planes really spend at the gate. Using the data, Gatwick has been able to increase slots on the runway from 53 to 55 an hour, which Howell says is a world record for a single-runway airport. Other benefits: there are no longer discrepancies in gate pull-backs caused by an airline employee listing one time and an airport employee listing another. Finally, on a practical level, the company is saving (at least) four person-hours per day because they no longer have to take data out of a spreadsheet.

Takeway: Determine how and when to engage operations with information technologies for maximum data insight.

Lesson №5: Don’t downplay the importance of data standards

I’ve already covered part of the problem in the previous article about B2B data standards and its protection in relation to the next year’s EU GDPR rules implementation, however, the importance of this subject can not be stressed enough.
Unfortunately, there are already too many standards in the IoT space for data formats and there is no easy way to prevent them from proliferating.

Over the last years we’ve seen cases where a firm was large enough to influence standards in a global industry body in a way that served its interests, but this is only possible for the largest firms, and takes years.Standards are already being developed for IoT. But the two biggest vendor organisations, the Open Interconnect Consortiumand AllSeen Alliance, are fighting over whose standards will prevail, and you can count on more standard organisations jumping in the argument. There’s going to be a lot of skirmishes before the market decides which should be the standard or if there should be one at all.
The best solutions offer a flexible, model-driven approach to semantic inter-operability that’s dynamic enough to handle evolution of standards and message contents.