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Living In a World That Reacts as Fast as You

Living In a World That Reacts as Fast as You

via PSFK
via PSFK
Networked objects are learning to anticipate our needs and orchestrate responses that deliver safety, efficiency and convenience

Ever had one of those days where everything goes wrong right from the start? Maybe you accidentally turned your alarm off instead of hitting snooze, and now you have to rush out the door for work. Of course the city would be doing road work today and, in this traffic, 15 minutes late is suddenly looking more like 40.

Compounding problems like these may be avoided as the world becomes more connected.

Sensor-embedded technologies interpret real-time data about their surroundings, which enables them to activate at just the right moment (or even before) with increasingly relevant responses. Sensors are in just about everything now – put them all together and you’ve got a coordinated network of objects delivering safety and efficiency. As they continue to collect data over time, these sensors will evolve from reactionary to anticipatory. Working together, they have the potential to save us a lot of grief.

To learn more about this trend, we talked with Jennifer Healey, research scientist at Intel, and Tim Plowman, embedded user experience lead with Intel Labs’ Experience Design team.

Where can we expect to see changes as a result of this trend, and what would that look like?

Jen: We’ve been looking a lot at anticipatory technology in the transportation space. In particular we developed a Concierge System, which was designed to anticipate when you needed to get up to get to work. For example, if traffic or weather was going to bad, or if there was some sort of indication that your commute might take longer than expected, the system was could wake you up a bit earlier so that you would have the additional time you needed.

This anticipatory alarm received information from the cloud regarding weather and traffic, but also from the car itself. The car could also push a message to the cloud that its gas level was low. The system would then anticipate that the driver might have to stop for gas and add that to the expected commute time.

We’re also looking at real-time anticipatory interaction between cars and smart infrastructure. A smart traffic light could let you know it’s about to turn red, and your car could tell the traffic light, “Look, I’m approaching.” With that, the traffic light could look both ways and, if if the coast is clear, change green for you so you could go through.

Tim: We started out primarily focusing on the in-vehicle context. We were asking, what are the anticipatory experiences that could be delivered within the vehicle itself?

 

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