The Internet of Things (IoT) will be everywhere. According to Gartner, by 2020 the IoT will be more than a $300 billion market, with over 26 billion devices installed. In contrast, today we use 7.3 billion smartphones, tablets and PCs.
Naturally, the IoT will run up against today's other disruptive technologies, including social, mobile, analytics and the cloud. Let's take a look at how the IoT is affecting and leveraging each of these areas, as well as its impact on cybersecurity.
Social
Many IoT applications have already gone social. Most prominent so far has been the "quantified self" arena, with countless runners, cyclists and triathletes sharing details of their routes and times with friends in their social communities. But we are also seeing other ways that social networking can interact with the IoT. In the "connected home" space, for example, Internet-connected, remotely operated door locks offer the ability to share access to your home with other family members and approved house guests. This represents a fundamental change for social; you're sharing not just information and photos, but the ability to interact with physical things.
As socially enabled business processes are integrated with enterprise functions, the ability to remotely monitor and control IoT devices will extend social collaboration among knowledge workers to support actual business operations in addition to making business decisions. An example might be hospital caregivers collaboratively deciding, over an enterprise social network, to provision more smart mobile robots to autonomously deliver medications, meals, supplies and materials based on real-time needs.
Mobile
IoT applications will further advance the status of the smartphone as a remote control for everything. Smartphones will provide access to IoT applications allowing information access and sharing, command and control of specific IoT devices or groups of devices, and intelligent analytics to help guide decisions. The smartphone therefore becomes a key part of IoT application design and the architectural ecosystem.
According to Gartner, by 2017, mobile users will provide personalized data streams to more than 100 apps and services every day. We can expect many of these 100 apps and services to be directly related to, and integrated with, IoT technologies and processes. This connectivity into IoT devices will apply not only to personally owned devices, but to enterprise-owned devices as well, and I expect both knowledge and operational workers to have similar sets of personalized data streams that connect them to essential enterprise IoT devices specific to their roles and responsibilities.
In coming years, as wearables take hold, they will also be used in concert with the IoT. In fact, a wearable device such as smart glasses coupled with augmented reality applications may well become a highly convenient platform for surveying the landscape (in the home or in business scenarios such as manufacturing, inspection, maintenance and repair), as users visually locate IoT devices and check their digital status. While the smartphone may be the remote control, the wearable devices will provide instant information and collaboration with hands-free convenience and efficiency.
The Cloud
The cloud will be a key enabler of the IoT model, allowing IoT ecosystem components and participants to both provide and consume services in an agile, scalable and efficient manner. Data can be transmitted from various devices and then stored, processed and analyzed in the cloud.
The cloud also provides a scalable platform for data collection and aggregation from myriad IoT devices and for data storage and information sharing to any number of players in the IoT ecosystem. It can support collaboration, with many people consuming IoT raw data or the more refined results of analysis.
As an example, in a hospital, not only could data about patient needs, caregiver schedules, ER wait times, availability of beds and rooms, location of assets, and consumption of supplies be optimized to improve patient throughput and levels of care, but it could also be shared with other hospitals in the network, insurance companies, suppliers and manufacturers. Insights and intelligence would all flow back into the system for continual optimization.
Cloud computing providers and data centers will have to be prepared for how the IoT will affect the volume of data, associated storage capacity, network bandwidth and backup issues. Real-time processing will have to be beefed up to respond within appropriate time frames to dynamically changing operational and environmental variables flooding in from IoT devices.
Analytics
The IoT clearly increases the volume, variety and velocity of data that will need to be collected, managed and analyzed by the enterprise in real time. It will be a major driver toward big data, whereby intelligent analytics can be utilized to optimize business performance, enhance the digital customer experience, and drive competitive advantage.
The challenge will be for enterprises to transform their existing, and sometimes aging, information infrastructures quickly and effectively enough to be able to deal with these huge volumes of data in real time.
Hybrid approaches will be required to support information infrastructure requirements. Traditional relational databases and data management techniques will still be required for highly structured and transactional data, but will need to seamlessly co-exist and integrate with big data tools and techniques for dealing with highly unstructured data. The IoT will likely feed both of these environments, since it will be high-volume and high-velocity, but will contain structured and unstructured data based on the specific device, such as a temperature sensor versus a video camera.
Certainly, the IoT has significant business value related to further automation and process efficiencies, but it's the intelligent analytics of the data coming from the IoT, and the resulting feedback loop back into these assets and devices, that will really help to optimize utilization and drive financial results and overall business performance. In addition, intelligent analytics from data coming from the IoT will add to the ability of organizations to deliver highly personalized experiences to their customers, not only based on their online interactions and preferences, but now based on their actual physical behaviors and usage patterns of their IoT devices as well.
Complicating these analytics for the CIO will be the diverse nature of the information as it comes from things, whether it's collections of identical things or broader collections of totally different things. A typical example of this diversity might be the data from one aircraft compared to that from a fleet of aircraft and then compared to that from an entire airport operation.
Cybersecurity
Cybersecurity operations are already seeing greater threat levels from an increase in the sophistication, frequency and scale of cybercrime, as evidenced by recent attacks, such as point-of-sale malware attacks on retailers, and due to the rapid adoption of new, disruptive IT technologies that effectively eliminate the idea of a defensible technology perimeter. According to the Ponemon Institute, the average cost of remediating a successful data breach in the U.S. is $5.4 million.
In coming years, threat levels will rise further as the IoT comes online and opens up even more ways for cybercriminals to exploit the weakest links in the ecosystem to move around on the network and seek financial gain.
Some of the cyber risks involved with the IoT include more attack surfaces, as things that couldn't be hacked into before such as smoke detectors and thermostats become connected; theft of sensitive data; more lost, stolen or compromised mobile devices that have transformed into remote controls for IoT devices; and more devices and things to remotely control or even sabotage.
McKinsey forecasts three scenarios for how the increasing cybersecurity pressures may play out. Organizations will either "muddle along into the future" (if there's a gradual increase in threat intensity and a gradual increase in the quality of the response), experience a "backlash which threatens digitization" (if there's a dramatic increase in threat intensity and only a gradual increase in the quality of the response), or achieve "frictionless security which accelerates cyber-resilience and digitization" (if there's a dramatic increase in threat intensity, but also a dramatic increase in the quality of the response).
Takeaways
Perhaps the key takeaway from the impact of the IoT on existing trends such as social, mobile, analytics and cloud is the powerful combination and convergence of these trends and the way they mutually reinforce one another to create even higher levels of business value and differentiation.
As organizations plan their IT-enabled business strategies over the next three years, it will be important to account for this combination of trends, including the IoT, in both the master IT architecture and in the various digital transformation efforts that aim to redesign business processes and business models to take advantage of these trends in compelling new ways for customers, citizens and employees.
Successful execution will also require new cybersecurity capabilities to be built into the new master IT architecture, and the quality of cybersecurity responses to increase steadily with increases in threat intensity as IoT applications come online. The time to start planning is now.
Nicholas D. Evans leads the Strategic Innovation Program for Unisys and was one of Computerworld's Premier 100 IT Leaders for 2009. He can be reached at nicholas.evans@unisys.com.