I'm preparing to return to a pastime that I gave up a few years ago: flying radio-controlled model airplanes by first-person view, or FPV. Telemetry to Go: My ground station for receiving video was a battery-powered Raspberry Pi connected to two Wi-Fi dongles [top]. On board the plane, I mounted a camera module attached to a Pi Zero [bottom]. The final nail in the coffin was that I discovered that the Raspberry Pi Zero's camera connector wasn't making a very solid connection to its ribbon cable.

More than 50 million Americans suffer from sleep disorders, and diseases including Parkinson's and Alzheimer's can also disrupt sleep. To make it easier to diagnose and study sleep problems, researchers at MIT and Massachusetts General Hospital have devised a new way to monitor sleep stages without sensors attached to the body. Their device uses an advanced artificial intelligence algorithm to analyze the radio signals around the person and translate those measurements into sleep stages: light, deep, or rapid eye movement (REM). Recent advances in artificial intelligence have made it possible to train computer algorithms known as deep neural networks to extract and analyze information from complex datasets, such as the radio signals obtained from the researchers' sensor.

Many rural Ugandans don't have Internet access, and the radio is a central source of news -- and platform for citizens' opinions. Many rural Ugandans don't have Internet access, and the radio is a central source of news -- and platform for citizens' opinions. The inspiration for the tool came from projects that use social media to identify citizens' concerns -- for instance, what concerns people have about an immunization drive, or how often they suffer power outages. But at the Global Pulse lab in Kampala, Uganda, social media analysis wouldn't work, says lab manager Paula Hidalgo-Sanchis -- especially if the U.N. wanted to listen to rural voices.

You can lie to your partner, your best friends and even your mom, but you can't lie to EQ-Radio. It's a device out of MIT"s Computer Science and Artificial Intelligence Lab (CSAIL) that can tell how you truly feel by bouncing wireless signals off your body. Yep, you don't need to be connected to the device with ECG patches and wires. EQ-Radio has algorithms that can extract your heartbeat from the signals your body reflects. It then analyzes each heartbeat and compares it to your previous measurements. According to the team, the device is 87 percent accurate with your measurements on file, but it's still up to 70 percent accurate without them.