Location Based Mobile App for Manager’s Appointment in Russia with Supervised Learning Prediction in Supply Chain Management

Abstract

Abstract- Large waiting times at enterprisesmeeting rooms are a cause of dissatisfaction to employees, because additional stress to enterprises staff, increase the risk of contagion and add complications for employees with working conditions based on the supply chain management. Reducing waiting times and improving the quality of service and efficiency of a small and medium sized enterprises: this is a recently growing focus onmeeting. Small and medium sized enterprises in Russia wants to identify and reduce large waiting times at their meeting room. For the past few years, the meeting rooms have used a self-service system whereby employees register for arrival and enterprises staff use anemployee call-in system. The past schedules are analyzed using this data: information visualizations and performance measures are provided. The worst performing meeting room sessions are the subject of the scheduling optimization prototype system. Users are involved in many activities that are planned, unplanned, routine and emergency in nature. The ability to manage all these activities without conflict is desired by all persons because time management is one of the attributes of successful people. With the proliferation of mobile devices in our society, this work seeks to develop an appointment management application for mobile devices using the Android platform. The developed application utilized two application programming interfaces (APIs) from Google for the map and calendar. Other parts of the application were developed inthe server-side process. The results show a functional mobile application for appointment management.