This week’s list of data news highlights covers June 5, 2021 – June 11, 2021 and includes articles about removing microplastics from the ocean and predicting space weather patterns.
1. Identifying Gun Traffickers
The Baltimore Police Department has adopted a data intelligence tool to identify people involved in gun trafficking. The tool links previously disconnected datasets, such as data on gun tracing, ballistics, and real-time data about gunfire in the city, to create a network of people who may be related to the trafficking of firearms. By identifying people related to firearm incidents, the tool helps officers and detectives pinpoint key witnesses.
2. Improving Road Safety for Cyclists
Australian telecommunications company Telstra and Sydney-based cycling company Arenberg have partnered to create a bike helmet that has video streaming capabilities, enabling users to share data with other cyclists. The sensors also share data to the cloud where an AI system can identify collisions and alert cyclists about road hazards.
3. Repurposing Drugs for Coronary Artery Disease
Researchers at Ohio State University have trained a machine learning model to identify drug repurposing candidates for coronary artery disease using historical data from existing treatments and patient outcomes. The team used the model to evaluate the effects of 55 drug candidates on over a million patients with coronary artery disease and found six drug candidates that doctors had not previously used to treat the disease.
4. Removing Microplastics from the Ocean
Scientists at the University of Chemistry and Technology in Prague have developed self-propelled microbot technology that can remove microplastics from the ocean. The microbots use solar power to swim through water and dismantle microplastics. Scientists can use the technology to prevent microplastics from further threatening marine ecosystems.
5. Monitoring Seabirds on the Falkland Islands
Scientists at Duke University and the Wildlife Conservation Society have trained neural networks to identify different species of seabirds from photographs. The team had drones take pictures of albatrosses and penguins that live on the Falkland Islands off of Argentina’s coast, and the neural network identified each species with 97 percent and 87 percent accuracy, respectively. The team will use this technology to monitor seabird populations and assess the effectiveness of conservation efforts.
6. Measuring Environmental Pollution
Two IoT companies, PlanetWatch and Emrit, have partnered to deploy thousands of air sensors in different cities. The sensors collect environmental data and measure air pollution in each city. Interested parties can then purchase the collected data using PlanetWatch’s cryptocurrency token.
Waycare, a traffic management company, has partnered with the North Carolina Department of Motor Vehicles to track roadway activity with AI. The company uses an AI system and data from existing sources, such as connected vehicles and weather apps, to predict traffic management issues and alert state agencies to roadway hazards and accidents.
8. Inventing Faster Microchips
Google researchers have created an AI system that can design microchips faster and more efficiently than humans. Their AI system maps placement for the microchip’s components, which affect the chip’s power consumption and processing speeds. Researchers can use this AI system to manufacture more powerful microchips.
9. Leveraging Data for Mental Health Treatment Plans
Researchers at the University of California, San Diego, School of Medicine have designed a new approach for personalizing depression treatments. The researchers collected lifestyle data from 14 patients via their smartphone applications and wearables. They matched the data with cognitive assessments and brain activity measurements to generate individualized health predictions and treatment plans for each patient. Clinicians can use the data to create more targeted treatment plans for patients.
10. Improving Space Weather Forecasts
Researchers at the University of Graz, Skoltech in Austria have developed a new AI system that can detect variations in the sun’s atmosphere known as coronal holes. The team trained the model with data on the intensity, shape, and magnetic field properties of various dark regions in the solar atmosphere, and identified the regions as coronal holes with a 98 percent accuracy rate. Researchers can use the AI system to better predict solar events and space weather forecasts.
