IoT Adoption Barriers and Accelerators at MIT Connected Things

MIT Enterprise Forum of Cambridge hosted their annual Connected Things forum this past Monday at the MIT Media Lab.  This symposium was focused on how to accelerate the adoption and impact of IoT by identifying headwinds and discussing ways to overcome them.  Cybersecurity and connectivity remain universal hurdles, but the presentations, panels and personal discussions also revolved around many other obstacles, including; exponential data volume growth, data cleansing speed, the need to go from cloud to distributed edge architectures, quantifying results, interoperability, bureaucratic red-tape, human fears and resistance to transformational change such as AI.  Two of the keynotes resonated with me: IBM and GE presenters shared how their companies have achieved successful results with IoT, and how they are solving some key market adoption challenges.

IBM – “Perfect Storm” is Coming

Mac Devine, VP & CTO, Emerging Technology & Advanced Innovation at IBM Cloud Division presented some easily relatable stories in overcoming hurdles in IoT and how technology can provide solutions to everyday problems.  The first involved the story of Weather Underground, an IBM company with a continuously expanding network of connected weather stations that has grown to over 180,000 worldwide.  WU crowd sourced its weather data, and spent its efforts and capital developing advanced algorithms to interpret that data and improve/expand forecasting.  It now has supplanted the National Weather Service as the premier source for weather information for the consumer and meteorological markets here in the US and abroad.  He also shared how when he first heard about autonomous cars, his first thoughts were that that it would never happen.  A trip overseas and a cab ride from hell led to a moment of enlightenment.  Is getting into a car driven by someone you do not know, who does not speak your language, and sometimes in places where road laws and licensing procedures are not robust a smarter decision than trusting analytics?

Devine also shared his theory called “The Perform Storm,” which forecasts the impact of big data, cloud, and IoT associated with the exponential growth in number of devices, data, and geographic distribution of assets.  To “Surthrive,” as Devine puts it, requires new innovative solutions such as decentralized autonomous edge computing, which is the focus of IBM’s Project MTN.

GE’s Predix – Ecosystems and Smart Data Governance Key Market Accelerators

Harel Kodesh, the Vice President of Predix and CTO of GE Digital, offered an overview of Predix and its answers to some of the issues associated with broader market adoption of IoT.  GE invested in building the Predix platform because the value for connecting large rotating industrial machinery and assets such as locomotives and jet engines was easily quantifiable.  For many other industries and emerging industrial IoT markets, the capital to build and maintain a similar platform may not exist or be an efficient use of resources.  GE sees its investment as a foundation for a broader industrial IoT ecosystem which can rapidly accelerate application development.  Ecosystems are a critical component of rapid acceleration of broader IoT market adoption.

GE also has a market proven solution to another major concern, data privacy and governance.  Predix has a common framework that enables the customer to map their governance policies in varied use-cases, and it was designed to work in conservative and highly regulated industries.  Kodesh shared a real scenario from GE Aviation, where an airline was concerned that if their pilots, during a flight, pushed their engines enough, they could be violating their maintenance contracts and worried about GE Aviation having access to this information.  Predix data governance policies and its architecture were designed to alleviate these fears, as GE would also own the maintenance service contracts for many of the airlines as well.