What the Internet of Things means for today and tomorrow

President, Sixth Sense Advisors Inc.

The first part of this series offers a glimpse of the ongoing changes around us that are driven by the Internet of Things. This installment looks at how enterprises are evolving around the Internet of Things and some of the important considerations that come with those changes.

From the enterprise perspective, the Internet of Things is defined as everything that can be connected in a digital universe. The core of this definition is that the availability of the application or thing and its data is in a connectable ecosystem, which today is a given expectation of any platform. A few key pieces of architecture need to be considered in this ecosystem for these reasons: 

  • Bandwidth constraints: Not all areas of the world are smart yet.
  • Reliability: Constant availability of infrastructure helps ensure reliable processing of data.
  • Infrastructure resources: Unless you are ready for cloud-driven infrastructure, which is digital transformation, there are limitations on availability of infrastructure to process data on a continuum.
  • Very high, scalable networks: A serious uplift needed for the mobile infrastructure is available, but are you already implementing the most recent infrastructure? And can it handle multichannel levels of usage?
  • Security: This component is the key to the castle—is it ready?
  • Privacy: We have moved into a new realm of data, security, privacy and protection. Are you ready with the latest privacy options, and have you implemented them? 

These considerations have become the key set of underlying requirements to implement a successful digital transformation program that can lead to an Internet of Things–ready enterprise. Consider some examples.

Mobile medical devices today’s world, medical devices used by patients in hospitals and at home or work have the ability to transmit data on demand. From a data security and privacy protection perspective, this on-demand data transmission is a good thing because of the availability of data and its usefulness in proactive patient health management. However, it can be a bad thing because the information can be hacked or incorrectly shared.

How does one address this problem? How can you prove to an audit and compliance team that this kind of data transmission is being guarded as an asset? And how can this protection still allow use of the data in the digital world for deriving the insights that can provide a foundation for improving machine learning, algorithms and models, visualization and interactive treatment in remote healthcare services situations?

In many hospitals today, the bed and all the associated equipment have radio-frequency identification (RFID) that makes them digital ready. Even the patient chart, which becomes digital following EHR regulations in the US, is expected to go digital. This digitization makes it easier to manage patients and provide comfort for patients’ families.

Digital medical devices raise other issues around regulations of data and its format, the protection of assets, issuing data to the patient at the time of services and after hospitalization, readmittance regulations and state and federal laws. As we develop the technology frontier in healthcare, several products and solutions that help address these considerations are available from vendors such as GE, Motorola, Siemens and other mobile device vendors. Along with the front end, there are several changes being adopted in the back end through big data technologies and data security algorithms, along with machine learning and other software implementations.

And in parallel with these changes, vendors such as Predixion have been working to bring analytics in visualization to the forefront, and this effort helps with managing key performance indicators (KPIs) across the spectrum. Into this mix of data and technologies we can implement an IBM Watson solution that provides an integrated stack of data and search analytics for helping improve the ways we use this data. The emergence of these technologies, their interfaces and their data requires that we strategize a solution architecture that enables digital transformation. Look for more information on this strategy in an upcoming installment of this series.

Smart buses

We are moving toward automation of information from all aspects of life, including smart cities, transportation and more. A key transformation in industry today is the connected bus, which is a program that was piloted by Cisco and the San Francisco Transportation department. The innovation underlying this concept is the integration and use of information and communications technology to allow knowledge, people, traffic and energy to flow efficiently. Increased efficiency enhances how people experience urban life, streamlines the management of cities and reduces the urban environmental footprint.

As a part of this program, which was tested in 2009 and has been incrementally improved, the Connected Public Transit incorporated various smart-traveler features that use real-time information to provide dynamic—changeable—guidance based on user profiles and context. This functionality is the key feature of an Internet of Things application, which creates powerful insights and outcomes. By implementing this system, the overall carbon footprint of the city of San Francisco was reduced as people began enjoying the feature-rich and user-friendly transportation system. Today, this hallmark case study has become a globally implementable platform that can enhance safety for women, children and senior citizens in many countries around the world. The smart bus demonstrates an effective use case and implementation of the Internet of Things and how simple solutions can become powerful influencers for society.

Stay tuned for the next installment in this series for more case studies on smart health and smart power programs, followed by implementation strategies, roadmaps and more. There are so many possibilities and so much to innovate in this new Internet of Things ecosystem.

Editor’s note: This article is offered for publication in association with the Big Data Seminar 2017, 16–17 November 2017, in New York City, at the Hotel Pennsylvania, and sponsored by Data Management Forum. Additional information is available in the Big Data Seminar flyer.