This week’s list of data news highlights covers June 6-12, 2020, and includes articles about using the International Space Station to track animal movements and using ground penetrating radar to map a Roman city.
The International Cooperation for Animal Research Using Space (ICARUS), a collection of researchers from around the world, is using small sensors and the International Space Station to track animal movements. ICARUS is attaching fingernail-sized sensors to animals that transmit data to the International Space Station, which can detect sensor signals from almost anywhere on the planet. The sensors allow the researchers to track the movements of animals such as songbirds, baby tortoises, and insects. The sensors will also provide data about an animal’s body temperature, body position, and weather metrics about its environment.
Coral Detection Systems, a startup based in Israel, has created a system that uses AI to detect if someone is drowning in a pool. The system uses an underwater camera and computer vision to track all movements in a pool. It sounds an alarm and can send text messages to alert other individuals when it detects an individual drowning.
Researchers led by an individual from the University of California, Davis, have found that only 20 percent of ice-free land is free of human influence. The researchers analyzed maps from 2009 to 2015 and found that most of the unused land is either arid, extremely cold, or at high elevations. Only four biomes—boreal forests, deserts, temperate coniferous forests, and tundra—showed humans having little influence over half their area on the data the researchers examined.
The U.S. Defense Advanced Research Projects Agency has created a program called AtmoSense (Atmosphere as a Sensor) to detect the effects of storms, volcanic eruptions, and earthquakes on the atmosphere. These events cause changes in the movements of electrons and ions in the ionosphere, a layer of the atmosphere 75 kilometers above Earth’s surface. The project aims to see if measuring changes in the ionosphere can outperform existing measures of detection for events such as earthquakes.
Researchers from the University of Cambridge and the University of Ghent in Belgium have mapped a Roman city using ground-penetrating radar. The highly-detailed map of Falerii Novi, a town 30 miles north of Rome, reveals shops, temples, a theater, and the layout of the city’s water system. The system ran underneath buildings, suggesting individuals planned the third century BCE city’s layout.
Tokyo’s Haneda Airport is using an autonomous mobility device to help passengers with limited mobility arrive at their gate. WHILL, a Japan-based company that creates electric vehicles, developed the wheelchair-resembling device. Users choose their gate on a touch screen and the device drives itself back to its docking station after taking the passenger to their gate.
Nearmap, an Australian firm that provides high resolution aerial imagery, has created an AI tool that allows governments to automatically identify changes in imagery. The tool analyzes regularly updated images to identify changes such as growing building footprints, increased tree overhangs, and the installation of solar panels.
The city of Miyakonojo, Japan, is using IoT to help local care managers track the health of elderly individuals. Japan has a lack of caregivers to support its aging population, and Miyakonojo has used sensors attached to places such as the bedroom, the refrigerator, and doors to track how often a patient is eating, sleeping, and using the bathroom.
Researchers from Intel, the University of Zurich, and ETH Zurich, a university in Switzerland, have developed an AI system that allows drones to perform flips, rolls, and loops autonomously. Performing the tasks is difficult even for human-piloted drones, and the researchers trained the system in simulation. The system takes in camera images, trajectory data, and inertial measurements and outputs the appropriate thrusts and angular velocities for a maneuver.
NASA has created a program for volunteers to improve a classification algorithm that the Mars rover Curiosity uses to navigate the planet. Curiosity has been on Mars for eight years and uses an algorithm to detect objects such as rocks, sand dunes, and soil. NASA has asked the public to help it classify objects in 9,000 images to help train the algorithm. An improved algorithm can help the rover better predict the likelihood of losing traction while traveling on a particular surface.