Volumes of data are rising rapidly across the board, and no sector, vertical or market area is immune to the big data phenomenon. However, one area in particular was always going to create an exponential increase in volume, and that is the Internet of Things (IoT) sector.
A recent analyst report valued the global IoT data-management market at around $27.13 billion in 2017, and predicted that it would reach approximately $94.47 billion in 2024, growing at a CAGR of slightly above 19.51 percent between 2018 and 2024. The same report noted that Cisco Systems has predicted that by 2020, the IoT is anticipated to generate 600 zettabytes of data annually.
One clear area that is already beginning to benefit from IoT data flows is the insurance industry, in which better data means better risk management. There are already a range of business models operating, from the familiar discount on a home contents premium due to an approved alarm system being fitted, to more advanced options. Some buildings insurers already offer lower premiums on coverage if pressure, water and moisture sensors are fitted, and insurers such as Neos are bundling various packages of wireless smart-home sensors (including a wireless indoor camera) and the company’s app to detect problems sooner in policy holders’ homes.
Utility companies, especially in Europe, are also developing new business models based on the presence of IoT sensors, such as only providing the best green tariffs to customers with smart thermostats, because they are most likely to be able to use them efficiently. Some are offering subsidised packages of sensors to encourage adoption, too—a fact that is partly driven by regulatory pressures in Europe as well.
There is a significant challenge in the breadth of the data being generated by IoT devices, incorporating pure machine-to-machine data, but also an increasing volume of personal data—not personal in the sense of bank details, but (arguably more dangerous) in the form of precise data about individual’s behavior in their homes. The ability to build up a comprehensive picture of an individual’s preferences—and then target him or highly effectively—is both a “big brother” concern and a nirvana for marketers. Whichever side you fall on, it is a live issue; a survey found that 88 percent of U.S. consumers feel negatively about companies using their personal data to work out when they are likely to be home, potentially in order to time deliveries so they don’t miss their customers.
A rapidly growing factor in this data melange is the growth of artificial intelligence (AI)— not only because machine learning or a neural network requires vast amounts of realistic, live sensor input data for training purposes, but also that the finished article will receive and generate significant data flows. The enormous popularity of AI-powered voice control smart speakers is just one case in point. The overall market for AI-voice control cannot be easily overstated, as it not only delivers sales in the short term, but also provides a conduit for customer data in the longer term. That data can then be anonymized and used to improve the AI’s performance, as well as unearthing vital seasonal consumer patterns—and all this before you factor in the value of being the brand everyone is talking about: “Alexa, get me…,” “Siri, what time is…,” or “Hello Google…”
Of course, dealing with the incredible volume of data generated by speech-based query and answer sessions is no easy task. There are now more than 20,000 compatible Alexa devices, and 20 percent of the entire U.S. adult population has access to a voice-powered device—that’s 47.3 million U.S. adults. This is why the race to integrate these voice-control AIs into cars is such a hot ticket. Lexus, Toyota, SEAT, Skoda and Volkswagen are all either launching or have pledged to imminently launch Amazon Alexa integration. The ability to capture data on the road, as well as in the home, will provide the retail giant with powerful leverage in targeting new products and services—leverage that both Google and Apple have made efforts to gain also, with various flavors of in-car systems.
This is not to say that the entire future of IoT data is locked up and held by a handful of corporations, as there are potent APIs available for startups and partners to experiment with. Daniel Rausch, Amazon’s smart-home VP, used his IFA 2018 keynote to make just this point, citing data showing that companies which launched an Alexa-enabled device saw 43 percent business growth during the following nine months. Moreover, products with Amazon’s Works With Alexa certification quickly realized an average jump in business of 53 percent.
While the future may hold significant benefits for those companies and enterprises that can handle big data and, most importantly, interrogate it effectively, data can be a double-edged sword. Data breaches are on the rise, year on year, and considerable fines can be levied (especially under GDPR) for companies that are lackadaisical regarding personal data security. In many ways, the challenge is only just beginning.
Martin Keenan is the technical director at Avnet Abacus, which assists and informs design engineers in the latest technological advances and provides guidance through the challenges of bringing new products to life. This includes navigating evolving market conditions, such as the current MLCC shortage, and avoiding manufacturing pitfalls before they occur.