Optimizing Security with an Iot: A Data-Driven Visitor Identification Framework
Abstract
Security is an important factor that must be considered. The properties, such as computers, sensor devices, teaching aids, and other equipment, must be monitored in the best possible condition to be used whenever needed. If these items are stolen, it will interfere with students' learning abilities so that Learning Outcomes are not met. Currently, visitor identification systems are evolving, initiated by the implementation of IoT devices, face recognition, voice recognition, and so on. When these systems were executed, several obstacles were still found, such as the identification process being slow, requiring large amounts of training data, and the application interface only running on smartphone devices. Therefore, a breakthrough is needed to recognize visitors quickly, easily, and to boost protection. In this research, the author proposes an Identification Information System (IIS) for room visitors using a Data-Driven Modeling method based on the Internet of Things (IoT). This system is equipped with an IoT driver module to interact with the Raspberry Pi and a magnetic lock. It aims to allow a room administrator to control and lock doors online via a computer or smartphone. Based on the experiments that have been carried out, the proposed system is adequate to run optimally from some testing cases that have been designed.
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