The Internet of Things is accelerating at rates the human brain cannot begin to comprehend — and it has the capability to solve humanity’s problems in ways we can only begin to conceive of.
That’s the message from Dave Evans, CTO and Co-Founder of Stringify, in his Opening Keynote at CEDIA 2017 in San Diego. Evans spoke Wednesday evening about not just the Internet of Things, but the Internet of Intelligent Things — the fast-approaching future where devices will be expected to have not just connectivity but also intelligence.
After a brief introduction from Intel’s Miles Kingston, who outlined how voice control is driving smart home technology adoption, Evans painted a picture of multiple trends converging to turn the smart home into an intelligent home.
Audience members’ minds were blown with stat after stat about the pace of technological advancement. Some highlights:
- In 1969, four things were connected to the Internet. (Yes, four.) Today, we add 100 new things every second.
- Human knowledge doubles every two to three years.
- The physical size of technology is rapidly shrinking. The processing power contained in the 1,800-square-foot ENIAC computer in 1946 is matched by today’s average musical greeting card.
In other words, technology is getting faster, cheaper, smaller, and more powerful. Add these trends together, and you get an exponential number of innovative solutions and applications: connected livestock, plants, trash cans, pills, diapers, all collecting and sending data. Evans posits that in the future, connectivity will be the default, and things that are not connected will be at a distinct competitive disadvantage.
And all these connected things are creating massive amounts of data. Humans generated more new data just in the year 2008 than they had in the preceding 5000 years. We take more than one trillion photos per year. We upload 576,000 years of video to YouTube annually.
More and more of this data is being stored in the cloud, which makes it a gold mine for machine learning. Machines consume and parse and synthesize this data and apply the resulting intelligence to increasingly complex problems. Machines have learned how to look at an image and describe what they see — not perfectly accurately, but improving all the time. What’s more, machines can see things humans cannot. They can identify a person’s pulse rate from a series of images or translate text in a photograph in real time.
So what does all of this mean for real people?
As the global population grows and places greater strain on cities and resources and food supplies, innovators are looking to the IoT to help solve these challenges. Sensors will gather data in places we have previously had no visibility into, all in service of goals such as minimizing food waste and water pollution.
Heard the adage “You can’t manage what you can’t measure?” Measuring things that have previously been out of reach, Evans says, will enable us to address some of humanity’s greatest social challenges.