Wait times in Orlando International Airport drop 53% with SITA technology | SITA

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Wait times in Orlando International Airport drop with SITA technology

Location: Orlando
07 September 2016

Passengers at Orlando International Airport (MCO) have enjoyed shorter wait times in recent months with 53% fewer passengers spending more than 15 minutes in line. This is in large part the result of the introduction of sophisticated queue management technology from global IT provider SITA. The new system has resulted in the double benefit of reducing stress for travelers and enabling more accurate resource planning by the airport.

John Newsome, IT Director for MCO, said: “This is a great example of how measuring performance improves performance. The technology has helped us to better inform checkpoint resources and process management, reducing wait times; as well as better inform our passengers, reducing the stress of uncertain wait times.” 

Orlando International Airport introduced the intelligent queue management technology from SITA, and its partner iinside, at the airport’s East and West Checkpoints nine months ago. SITA QueueAnalyzer provides the airport with a real-time view of the TSA checkpoints, enabling rapid response to unexpected conditions. It also provides historical wait-time data to establish wait-time profiles for different times of the day, days of the week and seasons.

Matthys Serfontein, Vice President, SITA Airport Solutions, said: “It is great to see these results from Orlando International airport. They show that using smart technology can really improve the passenger experience. Our technology not only monitors but predicts queue times at key airport chokepoints and is proven to increase the efficiency at security checkpoints. Airports across the USA are looking at every way they can to reduce wait times and we are in the process of rolling out our technology in a number of high-volume airports before the end of the year.”

SITA QueueAnalyzer combines historical and real-time data and flight information with powerful algorithms to deliver highly accurate wait-time predictions, perform open lane detection and give ideal lane recommendations. The results can be displayed in real-time to passengers on screens, website, and mobile applications. It also provides automated metrics for performance, trending, and service level reporting and supports the integration of cameras and Wi-Fi sensors for passenger throughput figures and input into wait-time algorithms.

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