IoT Based Smart Staff Allocator in Quick Service Restaurants

Abstract

Internet of Things (IoT) term has been a trend topic for a long time, and takes over many jobs from human controlled domains and makes the things easier, quicker and remotely controllable with smart automations. Quick service restaurants include many parts that human intervention is involved, and burns so much effort that must be well organized and automated. It is such an era that an effort must be passed to loT-brains where possible, and human should pay the gained effort to any other areas. Quick service restaurants have many staffs, especially at the back office, created by kitchen, storage etc. These staffs must be well and efficiently organized so that there must not be a waste of effort. A human brain might not be sufficient for this duty and also it will be costly. So, it will be controlled by an loT brain which is fed by many sensors within restaurant and distribute the jobs to them fairly, efficiently and less-costly. In this paper, we present an architecture for allocating jobs to staffs and tracking their performance for various tasks. We also propose and evaluate a genetic algorithm with novel selection method in order to solve the task assignment problem.