We’ve all met someone at a party or meetup and forgotten their name just minutes after shaking their hand and making an introduction. It’s difficult to remember the names and faces of everyone you meet, but what if the wearable technology you have on you can help you out with that?

With the growing trend of wearables and IoT technologies, one thing is for certain, the ability for these devices to detect and communicate with one-another is remarkable. Now, imagine that technology that already tracks our steps, heartbeat, and location and use it to remember the names of people you meet throughout the day. That would be extraordinary.

Even more impressive would be using these technologies to identify someone in a crowded room and have that person’s name and information available to you when you need it.

Researchers at Rice University have been looking to achieve just that by overcoming the challenges that come with having the camera on your phone running 24/7. Phone cameras are great, but they’re battery hogs. Having your camera on to shoot videos at a party is hard enough on battery life, but having it running from the moment you arrive to the moment you leave would be detrimental.

RedEye is a technology being developed by Rice’s Efficient Computing Group. It uses some clever software and hardware tricks to dramatically reduce the amount of energy it takes for a system to identify images being captured by image sensors and determine what is, and isn’t important enough to keep.

A virtual photographic memory?

“Real-world signals are analog, and converting them to digital signals is expensive in terms of energy,” said Robert LiKamWa, a member of the project. “There’s a physical limit to how much energy savings you can achieve for that conversion. We decided a better option might be to analyze the signals while they were still analog.”

Your phone’s camera captures analog images and converts them into digital data whenever it’s running. This data conversion is expensive in both processing and battery power. By changing the software so that it analyzes the analog data rather than the digital conversion, this cuts out a lot of the effort required by the device.

There are a bunch of technical bits and pieces, including system architecture that is designed to work much like the human brain, but the end result is clear. RedEye is on the path to make wearable, IoT, and other battery-powered devices significantly more efficient when it comes to receiving and analyzing visual data.

Back to the party, your phone (and one day other wearables) would constantly be running its camera, identifying specific objects and even people’s faces and, upon being triggered by a specific pattern it recognizes, would make information about them available to you. This technology would have to be able to be switched off, as there are obviously times and places where having photographic record is inappropriate.

At this stage, RedEye and similar technologies are in early development, but in a world where we are already using Google in place of our own memories for hard facts, phone numbers, and directions, this evolution is inevitable.

One day, we could all have photographic memories.

Ryan Matthew Pierson