Down to the Device, Data Analytics as a Service AI as the Real Breakthrough
With the mass and moving parts that will define the IoT, can human beings really keep up? Or is it time to let the machines do the thinking?
There is no point in connecting things unless those things send information that help those who own and operate those things optimize their value.
Consider the difference between an office building before and after a full IoT installation. A legacy office building can operate with mechanical features: keys to unlock doors, switches to turn lights off and on, a network connecting phones and computers, a refrigerator and coffee maker in the kitchen. Multiply this by a dozen tenants, and this legacy office building can be rented and secured by the landlord just as that landlord and landlords before did so.
But a smart office building changes the experience and economics for the businesses who rent space, the property management company responsible for keeping the spaces filled, and the facilities management company responsible for ensuring operations and security, while also meeting quality of service and budget goals.
Here’s a short list of what can be instrumented in a smart building with a comprehensive IoT approach:
Multiply all these services across multiple locations, and you’ll soon figure out that making the smarter office even smart with AI makes sense.
Shamshad (Sam) Ansari, co-founder and CEO of Accure Analytics, looks at nearly everything from the perspective of AI when it comes to the IoT and especially the IIoT.
“To realize the full potential of IoT’s value, enterprises are combining IoT with AI technologies, which enable connected things to simulate intelligent behaviors and act, increasingly with little or no human intervention,” Ansari said. “Why spend tens or hundreds or even millions of dollars to instrument an environment, like a smart office, if you cannot maintain and control all those endpoints efficiently?”
Integrating AI into IoT networks is not new, but neither is it pervasive, as IoT itself is being continually redefined and refined. “Every IoT company out there must move rapidly to identify how they’ll drive value from combining AI and IoT, or they will find themselves extinct,” Ansari said, “and the same can be said for CIOs and others in enterprises who are undertaking IoT projects.
The personal computer was cool when it first came on the scene, but it wasn’t until software applications and connectivity to the Internet ramped up that the PC disrupted everything and forced businesses into the dawning of the digital era.
The same can be said for the IoT – only this time there are exponentially more endpoints and functions, and exponentially more innovation coming out of what we know is now digital enterprises on steroids.
“The profound impact that AI will have on every aspect of our personal and working lives is magnified when it is combined with sensors that allow things to communicate, and it is the coming era of real time IoT that making AI and machine learning absolutely critical, rather than an added feature,” Ansari said.
AI is forecast as a massive market; for example, Bank of America Merrill Lynch (BAML) estimated in December 2015 that the robot and AI solutions market will surge to $153 billion a year by 2020, with $70 billion of that spent on AI-based analytics. A primary driver? Cost savings.
Cost savings due to needing fewer humans to manage things, particularly the most mundane things that AI systems, for example in smart buildings, can manage very precisely, reliably and automatically.
“We’ve moved well beyond the early stages of AI and are now in the era of active intelligence—the ability to act in real time with little or no human intervention,” Ansari said. “For the IoT, scaling active intelligence makes solutions very attractive, with almost immediate returns on investments particularly when it comes to smart cities, smart buildings and smart homes.
