Streamlining the Passenger Experience with Human Flow Analytics by iinside
It’s a question that’s baffled many a traveller: Why can you get an accurate picture of the traffic you’ll face on the way to the airport, yet you have no idea how long you’ll stand in line at the security checkpoint – or how long it will take you to get to your gate?
Until recently, this type of data has been very difficult to accurately and efficiently capture at scale and share with multiple travellers in real time.
While the TSA has wrestled with potential crowd-sourced solutions, coverage is very light and it’s still only able to offer average wait times based on a very limited set of historical data. And while others have tinkered with crowdsourcing solutions, they ultimately rely on travellers taking the time to stop and post – at a time when most people are feeling the stress of getting to their gate on time.
iinside, a company based in Anaheim, California (USA), has ushered in a platform that harnesses the power of sensor analytics to help airports act on data-driven insights that improve efficiency and increase traveller satisfaction. Utilizing iinside’s cutting-edge analytics platform to observe traveller movements, airports such as the San Jose International Airport in San Jose, California (USA) and McCarran International Airport in Las Vegas, Nevada (USA) are now able to make intelligent changes to human traffic flows that can improve the passenger journey and minimize “time-to-gate” for travellers.
iinside utilizes LiDAR-enabled sensors (the same object-detecting technology Mercedes-Benz uses for its auto-breaking systems) and IOT devices placed at strategic points throughout airport terminals to capture the visual and spatial data necessary for analysis. Based on the data, airports can issue alerts for projected wait-times at security checkpoints, helping travelers select the best check point or departure time for the airport.
Additionally, airports can begin to discover new opportunities for generating non-aeronautical revenue such as increased retail sales. Through the analysis of traveler behaviors, airport operators can intelligently manage crowd flows and optimize vendor merchandising opportunities.
Using iinside’s empirical data, airport operators can also validate passenger drop-off reports for invoicing third-party ground transportation providers such as Uber.
The data also enables airports to measure throughput at TSA checkpoints, giving operators valuable feedback for TSA management on queueing, or other issues impacting the passenger experience. This type of data is particularly useful if TSA decides to test new procedures or alter their operations in any way.
Utilizing iinside technology, airports around the world are making the passenger experience more seamless and efficient. It’s also brought a new level of customer-focused innovation that can have a positive impact on the airport balance sheet.