Despite the fact that there are many well-publicized problems with the Internet of Things (IoT) and enterprise efforts to use it to achieve better business results, the fact is as IoT apps, devices and infrastructure matures, IoT will drive digital innovation in the coming years.
Make no mistake, the problems hindering IoT development that we have identified previously are still problematic — what enterprise can ignore the threat that unsecured endpoints pose — but at the recent Gartner Symposium/ITxpo 2018 in Barcelona in Spain, Gartner identified a number of emerging trends and technologies that will go a long way to solving IoT related problems.
Emerging IoT Trends
The result is that the IoT will continue to deliver new opportunities for digital business innovation as well as give CIOs that can master these trends, the push they need to drive digital transformation and development initiatives in their businesses. The trends and tech include:
1. Artificial Intelligence (AI)
As data drives the IoT, AI will be applied to a wide range of IoT information, including video, still images, speech, network traffic activity and sensor data.
2. Social, Legal and Ethical IoT
A wide range of social, legal and ethical issues will grow in importance around ownership and use of data.
3. Infonomics and Data Broking
Thirty-five percent of respondents were selling or planning to sell data collected by their products and services.
4. Move From Intelligent Edge to Intelligent Mesh
Edge architecture will evolve to a more unstructured architecture comprising of a wide range of “things” and services connected in a dynamic mesh.
5. IoT Governance
Appropriate behavior in the creation, storage, use and deletion of information related to IoT projects will become increasingly important.
6. Sensor Innovation
New sensors will enable a wider range of situations and events to be detected, current sensors will fall in price.
7. Trusted Hardware and Operating System
By 2023, we expect to see the deployment of hardware and software combinations that together create more trustworthy and secure IoT systems.
8. Novel IoT User Experiences
UX designers will be required to use new technologies and adopt new perspectives if they want to create a superior and frictionless IoT experience.
9. Silicon Chip Innovation
By 2023, it is expected that new special-purpose chips will reduce the power consumption required for chips enabling new edge architectures in low-power IoT endpoints.
10. Wireless Networking Technologies for IoT
Several, new networking technologies will emerge to optimize IoT networking.
How M2M Solves Problems
At the heart of all this is the ability to automate and gather data using technologies that connect thousands of devices as well as provide ways to produce insights from that data. Recent developments in machine-to-machine (M2M) communication is making this easier according to Steve Smith, VP of strategic industries at ClickSoftware.
The benefits to organizations are numerous. Remote monitoring applications already save billions in transport and human capital management costs. Add the potential positive impact on customer engagement and its associated business value, and the call to action becomes clear. “A complete IoT strategy leads to better and faster decisions throughout the service delivery lifecycle,” he said.
While it may sound simple, monitoring thousands or even millions of pieces of equipment and identifying errors before they occur is a complex science that can quickly become overwhelming. To help simplify the process, Smith has broken it up into two distinct phases: data collection and data analysis.
1. Data Collection - IoT sensors allow for large volumes of data to be collected and stored, providing companies with insight into equipment health, performance and failures. Every unit can generate hundreds of thousands of data points every minute. The challenge at this stage is figuring out how to organize and prioritize all this data.
Performing data analytics on all this information is not feasible nor is it an efficient use of resources since some of the data being collected holds little value in determining asset health. Companies need to consider what data to prioritize so that they can more quickly identify maintenance needs.
2. Data Analysis - Once data is collected and the key monitoring metrics are defined, analytics are applied in order to convert the data into actionable, useful information. Analyzing historical data, particularly around equipment failures and past service activities, allows service companies to identify patterns that might indicate a future error.
“IoT represents transformative technology, but a successful IoT strategy for industrial and/or consumer applications must work today and be flexible enough to accommodate whatever comes next,” Smith added. “With the right goals, plans and tools, IoT can go well beyond an inflated buzzword. It’s likely it will grow into a tool that provides practical value every day for both customers and service organizations.”
IoT is Moving to Digital Workplace
Gerry Widmer, CEO of Zesty.io, a SaaS decoupled content management system, points out that the push into digital business is already taking place from developing a Alexa skills to connecting content in multiple mobile and smart device applications, it would only make sense that as IoT devices begin to proliferate, so too will the business innovations.
“The biggest roadblock we see today in CIO's resisting new channels in IoT is the time and dedication required to create applications for each platform and manage them. The need for specialized development seems to be increasing. Perhaps the most important [thing for] CIOs [is to have the ability to] enable their teams to develop for these new IoT applications [by] having a single content repository,” Widmer said.
Simply put, a content repository is one place where all of your content for omnichannel initiatives is stored. Each program your brand builds (Google Assistant, Amazon Alexa, Amazon Fire TV, Apple Watch, Fitbit ) are able to pull content through an API from one content repository. That way, when content is modified, that change is syndicated across all of the platforms workers are building experiences for, rather than asking for a developer to make that one change multiple times in multiple systems.
Many corporate decision-makers today are still analyzing batch data, gathering information from disparate systems to come to a conclusion. IoT enables those disparate systems to come together, talk to each other, and deliver real-time analytics to empower smarter, faster decisions.
Using IoT-Harvested Data
There are a number of use cases for the data that comes from this batch data in the digital workplace and the way employees work. The most obvious emerging trend here is the incorporation of ‘wearables’ in the digital workplace, according to Ash Turner, CEO of online retailer BankMyCell. Three examples include:
1. Disney Magic Band - Disney has recently implemented the Magic Band 2 that uses big data, IoT and machine learning to focus on boosting customer experience. The bands act as hotel keys, fast passes, credit cards, tickets and more. The band records the consumer's park navigation patterns, knows what they want, where they are and what activity they're doing.
The goal was to remove any friction from the general park experience, essentially, they can see where queues are big and re-route customers with alerts to minimize wait times on rides and increase their time in the park where they can spend more money.
2. Carnival Cruises Customers’ Wearables - Carnival Cruises have wearables that allow it to gain deep insights into what its customers want. For example, a customer can navigate the cruise ship while opening doors and getting directions to general activities. This data is all amalgamated and analyzed to improve the experience, tracking the customers’ typical navigation patterns around the ship and the activities they engage in.
3. Cincinnati Customer Experience App - Cincinnati / North Kentucky airport (CVG) implemented a Samsung solution working with smartwatches and Hipaax task management software to help maintain positive customer experience. Sensors were fitted in baggage and arrival restrooms that can send alerts to airport staff, once the restroom has received usage of 150 or more costumers, housekeeping staff get smartwatch alerts to inspect them. The data they received let them know which restrooms are busiest and how long it takes to clean them on average, which is used to monitor and motivate staff performance.
The push to become “real-time businesses” is what is driving organizations to adopt IoT and this has forced a reality that organizations are starting to realize is nearly insurmountable.
Developing a successful IoT strategy requires understanding technology requirements unique to the business and an understanding of where IoT data fits into the digital workplace. In the case of industrial IoT (IIoT) in manufacturing, for example, companies should not only aim for optimized production and machine monitoring, their IoT strategy must also plan for new business models as more companies and industries digitally transform.
Combining expertise of the CTO and CIO will give IIoT strategies a balanced approach. CIOs determine current and anticipated digital needs of the manufacturers, and CTOs manage new technologies brought into the factory supporting these needs. This cross-functional partnership between CTOs and CIOs sets a framework for success