This week’s list of data news highlights covers April 9-15, 2016 and includes articles about a real time analytics system for the Mars rover and a wearable blood pressure monitor that uses radar.
Researchers from open science nonprofit Sage Bionetworks and Mount Sinai Icahn School of Medicine analyzed 589,000 human genomes to identify people who have genetic markers for Mendelian disorders—genetic diseases caused by a single mutation, such as sickle-cell anemia and cystic fibrosis—yet do not show any signs of such diseases. The analysis found 13 people with mutations indicating they should show symptoms of one of the 583 disorders examined, but are nonetheless completely healthy, which could eventually help researchers develop new treatments for these conditions. The research was conducted as part of the Resilience Project, an initiative launched in 2014 to advance understanding of the genetic mechanisms that induce diseases, and the data was provided by consumer genomics company 23andMe.
Ford has successfully tested its self-driving car at night without the use of headlights, indicating that its lidar sensors, which map the nearby environment with bursts of laser light, are capable of navigating a self-driving car on their own. Self-driving cars typically rely on a combination of lidar, radar, and cameras, which require a light source to be effective, making dark environments without street lighting difficult to navigate.
The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory has integrated open source analytics software called Elasticsearch into its analytics systems for the Mars rover missions to improve mission planning. The Curiosity rover, which landed on Mars in 2012, transmits thousands of data points to NASA from its onboard sensors at regular intervals throughout the day, which NASA analyzes to plan Curiosity’s actions for the next day. With Elasticsearch, NASA will be able to detect anomalies or other mission-critical data as it arrives, allowing it to adjust Curiosity’s actions in much shorter intervals. NASA is also designing the analytics systems for the next Mars mission, scheduled to launch in 2020, around Elasticsearch from the ground up.
London-based startup Plumis has developed a system called Automist Smartscan that relies on infrared sensors and specialized sprinklers to put out fires in a building using 90 percent less water than traditional methods, which can cause expensive water damage. When a room reaches 134.6 degrees Fahrenheit (57 degrees Celsius), which means there is a high likelihood of a fire, the system triggers an infrared pyrometer to detect the hottest location in the room. Then, a specialized sprinkler will target that area with a jet of high-pressure mist to put out the flames using much less water than normal sprinklers.
U.K.-based startup Magic Pony Technology has developed machine learning software that can increase the quality of low-resolution images or videos in real time and generate entirely new graphical elements that can augment the original image. Magic Pony Technology trained its software by exposing it to examples of high- and low-resolution images, teaching it to identify patterns such as blurred edges or pixelation and create a new higher quality image without these characteristics. For example, the software can automatically increase the quality of a low-resolution, live-streamed video game without delaying the video feed. The startup plans to develop additional applications of its technique, such as increasing the quality of low-light smartphone photos and generating realistic environments for virtual reality programs.
The American Cancer Society (ACS) and IBM have partnered to develop a virtual health advisor for cancer patients that relies on IBM’s Watson cognitive computing platform to connect patients with treatment information, information about the experiences of similar patients, and support services based on a patient’s unique preferences and condition. The advisor will have access to ACS’s cancer resources, such as lifestyle recommendations, educational materials, and de-identified patient data, and as patients engage with the advisor, it will learn their preferences and provide more tailored recommendations.
Google has released a new feature called Goals for its calendar app that uses machine learning techniques to help users accomplish desired activities by analyzing a user’s activities and scheduling tasks in a way that makes them less likely to be avoided. For example, a user can have Goals automatically populate his or her calendar with entries for exercise, and if the user defers this task, Goals will reschedule the activity for a time when the user is more likely to accomplish it based on analysis of his or her habits.
The city of Syracuse, New York has partnered with nonprofit ARGO Labs to map every pothole and rough patch of road in the city’s 388 miles of streets to help officials better prioritize street repair efforts. ARGO Labs developed a system that relies on a truck-mounted low-cost camera that takes one picture per second and an accelerometer that can detect when the truck drives over a rough portion of road. With this data, ARGO Labs will generate color-coded maps indicating the road conditions of every city street with pictures of any suspected damaged sections that the city can use to identify which areas are most in need of repair.
The European Parliament has voted to approve the General Data Protection Regulation (GDPR), a collection of new rules designed to increase the protection of personal data by implementing tight restrictions on how consumer data can be used and imposing harsh penalties for violations. Included in the GDPR is the controversial “right to be forgotten,” which forces Internet search companies to remove data about a person from the Internet upon request. The GDPR will go into effect in 2018.
Startup Blumio has developed a prototype blood pressure monitor that can track a wearer’s blood pressure using radar, which could allow users to monitor their blood pressure constantly throughout the day. Unlike traditional blood pressure monitors which require a bulky cuff that squeeze a wearer’s arm, Blumio’s device uses radar to measure subtle changes in electromagnetic waves caused by a wearer’s heartbeat and communicates this data to a smartphone app. Real-time data about blood pressure can be beneficial for people with high blood pressure or with a history of cardiovascular disease.