Recently, as a busy lifestyle of the office workers, we can witness that majority of them spend a long waiting time in lines of the restaurants and take-out coffee shops. As modern people should solve many problems in a limited time, systems that takes the pre-orders at the restaurants and take-out coffee shops are becoming popular. We believe that the need and utilization of such systems will become even more important in the future. However, currently there is a small number of services, which efficiently support the pre-order systems. In this paper, taking into consideration that smart services have become an integral part of the modern people’s life, we propose a mobile based pre-order system. The proposed system effectively uses the customer’s history and efficiently handles the pre-orders. Specifically, in this paper we propose a method to predict the customer’s arrival time based on customer’s past experience. We developed a mobile content that predicts the client’s arrival time using the take-out coffee shop example. By using our system, modern people can reduce the wasting of unnecessary time and use it more efficiently. Further, we can easily expand the proposed system to various other costumer services.
Recently, as a busy lifestyle of the office workers, we can witness that majority of them spend a long waiting time in lines of the restaurants and take-out coffee shops. As modern people should solve many problems in a limited time, systems that takes the pre-orders at the restaurants and take-out coffee shops are becoming popular. We believe that the need and utilization of such systems will become even more important in the future. However, currently there is a small number of services, which efficiently support the pre-order systems. In this paper, taking into consideration that smart services have become an integral part of the modern people’s life, we propose a mobile based pre-order system. The proposed system effectively uses the customer’s history and efficiently handles the pre-orders. Specifically, in this paper we propose a method to predict the customer’s arrival time based on customer’s past experience. We developed a mobile content that predicts the client’s arrival time using the take-out coffee shop example. By using our system, modern people can reduce the wasting of unnecessary time and use it more efficiently. Further, we can easily expand the proposed system to various other costumer services.
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