The Role of Recurrent Convolutional Neural Network in IoT for Building a Security Artificial Intelligence and Home Assistance System
Syahril Efendi, Fauzan Nurahmadi, Pauzi Ibrahim Nainggolan · International Journal of Safety and Security Engineering · 2023
Recurrent Convolutional Neural Network (RCNN) is the result of the development of the CNN architecture based on a recursive neural network on a neural network.The process with the development of RCNN is able to study data in moving images and images more optimally and accurately.With optimal accuracy, RCNN is of course not only limited to research, RCNN is able to play a role in models that are contained in hardware such as IoT technology so that it is used in everyday life.One of the benefits of this is to make the Smart Home System (SHS) concept and Energy Management System based on the concept of artificial intelligence.The development of IoT technology is caused by the large number of jobs or activities that cannot be carried out by humans on a regular basis so that it is combined with cloud technology which makes it easy to access from anywhere with connectivity.Cloud-based solar panel and IoT technology has proven to be able to provide convenience in the use of security in the smart home concept.Solar panels can replace electrical energy for smart home security devices for 24 hours.The Home Assistant system successfully detects and captures every object and distinguishes any movement in the area it sees so that the Cloud-based Home Assistant security system provides convenience and comfort for the smart home concept.Where the accuracy that results from RCCN as outlined in IoT devices on objects 0.5 meter to 1 meter is 100%, 1 meter to 2 meter is 95%.