Crowdsourcing is rapidly becoming a central means of generating accurate data. Israel’s most prominent example is Waze – a GPS navigation app which uses real-time reports from users on traffic, accidents and other data to calculate the fastest way to get from A to B. This crowdsourcing data also gives academics valuable information for research.
That is exactly what researchers from Telekom Innovation Laboratories and the Department of Information Systems Engineering at Ben Gurion University did. The research team used data from the Waze application to analyze police presence at problematic intersections. The team looked at how the new genre of geo-social mobile applications can provide useful data for location-specific analysis.
- Alcohoot: The World’s First Smartphone Breathalyzer
- New Waze Feature Helps You Navigate Your Way To Clean Water
The researchers, all members of the BGU Social Networks Security Research Group, trolled the Waze data and plotted traffic accident patterns. Using their data and Google Earth, they determined that 75 percent of the spots with the highest number of accidents were intersections. They then analyzed references to a police presence to determine if the police were present at the spots that had the worst traffic accidents.
“Our analysis could be used by the police to see if they are manning the busiest and most dangerous intersections,” says researcher Michael Fire. “According to the data, police response time was sometimes slow. There were also numerous instances where the police were manning quieter intersections, while busier intersections went unmonitored,” Fire explains.
The article, entitled “Data Mining Opportunities in Geosocial Networks for Improving Road Safety,” by Fire, a PhD student, scientific developer Dima Kagan, Dr. Rami Puzis, Prof. Lior Rokach and Prof. Yuval Elovici, was recently presented at the IEEE 27th Convention of Electrical and Electronics Engineers in Israel.
Photo by buzrael