Issue |
E3S Web Conf.
Volume 279, 2021
III International Conference “Energy Efficiency and Energy Saving in Technical Systems” (EEESTS-2021)
|
|
---|---|---|
Article Number | 01002 | |
Number of page(s) | 13 | |
Section | Modern Energy Efficient Automation Technology | |
DOI | https://doi.org/10.1051/e3sconf/202127901002 | |
Published online | 01 July 2021 |
Estimation of the carbon footprint of IoT devices based on ESP8266 microcontrollers
Don State Technical University, Rostov-on-Don, 344000, Russia
* Corresponding author: dand22@bk.ru
The development of the Internet of Things contributes to improving network protocols and increasing the requirements for energy efficiency of devices. In the field of the Internet of Things and automation systems, one of the most popular microcontrollers is the ESP8266. This article discusses the leading Internet of Things connection protocols based on ESP8266, such as ESP-NOW, HTTP, and ESP-MESH. The study of the power consumption of this microcontroller in various situations and describes the optimal applications of IoT based on ESP8266. The correct choice of communication means of the ESP8266 microcontroller allows you to reduce its power consumption by more than 10% relative to energyintensive communication algorithms. Compared to the power-intensive MESH network, the reduction in power consumption when using the HTTP protocol is 3.34%, and the percentage of energy-consuming events drops by 50.85%. When using ESP-NOW, energy efficiency increases by 5.35%, and the number of energy-consuming events decreases by 83.05%. The value of the carbon footprint generated by the device during the year was, for the three communication technologies used, 2 kg 500 g, 2 kg 320 g, and 2 kg 290 g of CO2, respectively.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.