Out of sheer necessity, sports security has been evolving rapidly since the Boston Marathon bombing, and most sports security professionals refer to that particular event as a turning point. Metal detectors have become commonplace in major league stadiums, new security policies have been formed, and even tailgating was banned at this year’s Super Bowl.
One year after the events in Boston, it is important that our nation’s law enforcement and homeland security leaders take a hard look at the lessons learned from that day and make some needed changes.
Now, new security protocols and a full year of planning and training guard the athletes, spectators and race course for the 2014 Boston Marathon. What did industry leaders take away from the incident?
Researchers at the University of North Carolina – Wilmington are helping law enforcement groups find real-world uses for facial recognition technology. One specific example is “MIDO” or “Multiple Image Dataset Organizer,” which researchers believe could have helped law enforcement compile that mass amount of information and images that flooded in after the Boston Marathon bombings. After the data is compiled, facial recognition technology could takes effect.
After more than 10 months of careful planning for the 118th running of the Boston Marathon, Boston's hotels are gearing up for record occupancy and larger-than-ever crowds of spectators both in the city and along the 26.2 mile route. This year’s Boston Marathon will be held on April 21st.
The lessons learned following the Boston Marathon bombings were many, but one lesson that was learned rather quickly was that Twitter was going to become the go-to platform for gathering timely and accurate information from city, state and federal officials regarding the rapidly unfolding events of that week.
Over the last several months, police in Pasadena, Calif., have been negotiating with local businesses to gain the use of their private surveillance cameras to monitor the Rose Parade route.
Facial biometric recognition works well on clear images with a good view of the face, but much additional data is often discarded due to the fact that the face, or the full face, is not clearly visible. The discarded data contains “soft” biometrics, such as height, gait and other features, such as ears.