It’s the most popular game of the season, and you’re so pumped about scoring a ticket that you arrive early to the stadium. Apparently, everyone else in the city had the same idea, and outside the stadium fans begin to form massive crowds in anticipation. Behind you, rowdy latecomers from nearby restaurants and bars lengthen the queues so far you can no longer see the last person in line. The security team is caught off guard by the number of early-bird fans and a bottleneck begins to form, causing massive delays.

Ok, let’s stop the story at this point. Before this situation becomes more dangerous, let’s evaluate what data we can utilize to prevent and minimize risk.

  • Wifi Data
  • Access Control Data
  • Video Surveillance Data
  • Stadium Game
    • Game Start & End Time
  • Third Party Data
    • Weather
    • Traffic

Keeping all of this data siloed won’t help us discover a solution to the bottleneck. However, by integrating a variety of these data sources into a single platform, we can provide a holistic and real-time view of your physical assets to quickly respond to security risks imposed by the bottleneck.

Machine Learning, a branch of artificial intelligence, enables us to take a step further in preventing the bottlenecks from occurring again. In our game-day scenario, machine learning would have enabled us to detect, respond, and manage the bottleneck faster and earlier.

By using machine learning in your operations you have the power to uncover patterns and trends that help you make better business decisions, optimize operations, and increase profits. With security operations tools that integrate machine learning, you’ll never have to regret being early to the game again.

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