IoT-Based Smart Home System Integrated with Deep Learning on the FPGA Development Board

This study proposes an Internet of Things (IoT)-based smart home system that sends and receives packets through the RS232 protocol and processes them using deep learning. A Field-Programmable Gate Array (FPGA) development board serves as a transceiver, operating a universal serial bus (USB) interface and a Wi-Fi module. The proposed system comprises a built-in wireless transceiver, a set of sensors, a development board running a deep learning algorithm, an MQTT communication protocol, and a terminal device controller. The objective is to implement an IoT -based smart home system with wireless data transmission. Node-RED is used to develop a comprehensive smart home system on the server side for IoT applications, facilitating data access, data processing, and terminal device control. The aim is to achieve automatic regulation and ensure comfortable indoor temperatures. In experiments, the root mean squared error difference between actual and predicted temperatures was approximately 0.4426 °C. After evaluation experiments with the FPGA development board, an application-specific integrated circuit (ASIC) based on the TSMC 0.18-μm CMOS process was used. Simulation results indicate that the chip area is approximately 1.186 × 1.188 mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>, and the dynamic power consumption is approximately 8.1674 mW at a power supply of 1.8 V and operating frequencies of 50 and 5 MHz.