Comparative Bandwidth Analysis of Low-Power Wireless IoT-Switches

TL;DR

This study compares the bandwidth and energy consumption of low-power IoT switches like Raspberry Pi models, analyzing how temperature and electrical factors influence data transmission speeds and device autonomy.

Contribution

It introduces an automated measurement system using Python for accurate, synchronized data collection of network and electrical parameters in IoT devices.

Findings

Temperature affects Wi-Fi data transmission speed.

Sensors with GPIO interfaces provide more accurate measurements.

Automation reduces human error in data collection.

Abstract

The article presents the research and comparative analysis of the bandwidth of low-power wireless IoT devices as wireless switches. The following IoT devices were investigated: Raspberry Pi 3 Model B and Raspberry Pi Zero W. The DS18B20 and INA219 sensors investigated and analyzed the dependence of FTP multimedia data transmission speed on wireless Wi-Fi network on the temperature of the switch processor, temperature. The environment and the current and voltage consumed by the switch. Advantages of sensors with GPIO interface over analog meters for this experiment are revealed. Much of the work is devoted to the development of automation of results from GPIO interfaces, which helped eliminate human error and get more accurate metrics. Measurement automation was developed using Python 3.7 programming language. Using the INA219 library we were able to obtain current and voltage indicators from the ina219 board. To get temperature indicators sufficiently built into Python libraries to read temperature files in Raspbian. The article focuses on the synchronicity of measurement results records for more accurate analysis. Therefore, an FTP client was developed that measures the download speed of the file from the FTP server and records the results simultaneously with temperature, current and voltage measurements. To this end, attention is drawn to the multithreading in Python programming language and the transmission of commands using TCP sockets in that language. As a result, the dependence of the measured factors was calculated using the Pearson correlation formula. These measurement factors affect the autonomy and energy consumption, which is very important for IoT devices, and therefore, among the devices tested, recommendations were made regarding their choice when used depending on the conditions.