Customer check-in feature development and optimization for real-time order pickup systems using GPS tracking

The dynamic increase of curbside pickup, drive-thru, and contactless retail services have peaked the demand to identify more efficiently and timely the arrival of the customers. Manual check-in procedure is slow, bringing a lot of inefficiencies as far as staff usage and lengthy wait times are concerned. The paper is designed to explain the procedure or rather the development and perfection of a customer check-in feature using the Global Positioning System (GPS) connected to a real-time order pickup system. The suggested solution utilizes the use of adaptive geofencing, dynamic GPS ping periods, and Kalman filtering to make the location more accurate and take the least possible amount of battery. Location data of customers is processed using cloud architecture to give an estimate of arrival time with automatic alerts to the store personnel to stage the order. Field tests in an urban, suburban and a rural setting show up to 35 percent average wait-time savings and an increase in the efficiency of operations, and user feedback has been positive when it comes to convenience and ease of use. The results indicate that automated check-in fueled by GPS is a scalable and cost-efficient modification to the contemporary pickup processes.