Every day, we use a variety of smart devices – desktops, laptops, smartphones, and tablets – to communicate with the Internet. When you extend the Internet to [formerly] dumb devices, we call this the Internet of Things (IoT). First came smart TVs, then smart home thermostats and doorbells, and now a broad range of industrial devices are embedded with software, sensors, actuators, and connectivity.
On September 10, 2018, the future of IoT was on display at the IoT Converge Conference at the Georgia Tech Hotel in Atlanta. In addition to the typical IoT topics – Data Acquisition, Predictive Analytics, and Automated Response – a striking addition took center stage this year: Artificial Intelligence (AI).
As IoT matures, AI has emerged as a complementary technology. Many of the sessions discussed AI with IoT in a complementary role.
One of the speakers, Cameron Clayton, from IBM Watson Media and Weather, presented a case study about world-record ocean speedboat racing. Silverhook, the speedboat builder, set out to engineer the fastest, most efficient mono-hull racer of all time. Clayton explained how the Internet of Things captured real-time data from the Silverhook boats, including from the environment (temperature, wind, etc.), mechanical systems (oil pressure, fuel pressure, horsepower, acceleration, etc.), and navigations (GPS location).
Capturing data from complex mechanical systems isn’t new. Consider the telemetry, biomedical, and engineering data that was transmitted by Apollo 11 – 50 years ago from the moon! The real breakthrough was how the boats used that information via AI algorithms that optimized the boat’s performance. The IBM Watson IoT Platform analyzed data from the boat’s many sensors, weather forecasts, and other real-time data sources, along with volumes of maintenance histories and service notes. The platform used this data to optimize nearly every system to drive the boat faster, safer, and more reliably than ever before.
A curious question arose: Did the winner have better driving skills or better AI algorithms?
Another personal observation was that IBM and Microsoft are taking two very different paths with Artificial Intelligence. IBM is looking to dominate an emerging industry and becoming a direct solution provider for medical, aviation, energy, agriculture, retail, and ground transportation applications. For example, a hospital would contract with IBM to implement a telemedicine platform. In contrast, Microsoft is developing AI tools to its partner network to allow its partners to build the industry solutions. TwinEngines is a Microsoft partner.
I also attended a panel discussion on the IoT.ATL AgTech Challenge (iot-atlanta.com) to identify smart AgTech solutions for the future. The Challenge is soliciting ideas for a 12-month study of urban farms along the Atlanta Beltline. They hope to build 40-foot container farms that leverage IoT, hydroponics, led lighting, etc. to produce economically viable, local food production.
It’s an exciting time for IoT/AI – and TwinEngines is proud to be part of it.