Google Predicts Waiting Times Using Crowdsourced DataGoogle Predicts Waiting Times Using Crowdsourced Data /wp-content/uploads/Google-predicts-waiting-times-using-crowdsourced-data.jpg 700 411 Gravitate Gravitate /wp-content/uploads/Google-predicts-waiting-times-using-crowdsourced-data.jpg
Ever wanted to know exactly how long a visit to the shops will take? Do you pop out at lunch hoping you don’t get stuck in that 30 minute queue at Starbucks and miss your afternoon meeting?
Google’s new waiting times feature may not be able to predict your exact trip time, but it goes a long way towards helping time-strapped individuals plan their excursions with increased precision.
Crowdsourced location data has proven extremely useful here by allowing Google to provide a timeframe showing approximate wait times for specific stores or venues.
This new feature can be found on Google Maps’ local listing page under the ‘popular times’ section – which already shows the times and days when businesses draw in the largest crowds.
To gather the data, participants travelled regularly to targeted businesses and recorded how long they spent in the building, including minutes waiting to be served and time spent entertained at leisure centres.
Google are yet to confirm whether the timeframe given will be a singular number e.g. 30 minutes, or a more flexible estimate, 1 – 2 hours – but it seems when fine tuned this could prove an extremely useful tool for those always on the go.