TY - GEN
T1 - An IoT-Based Measurement Device for E-bike Tracking Performance Analysis
AU - Ochoa, Joel Guaman
AU - Mendieta, Jarni Flores
AU - Astudillo-Salinas, Fabian
AU - Ochoa-Correa, Danny
AU - Iñiguez-Morán, Vinicio
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Electric bicycles (e-bikes) have emerged as a promising solution to meet urban mobility needs efficiently and sustainably. However, for e-bikes to fulfill their role in sustainable mobility, it is essential to analyze and understand their energy consumption. This work aims to address this issue by developing an IoT device for data acquisition and processing from e-bike sensors. The methodology employed in this study involves the selection and integration of sensors, as well as the integration of the bike's intrinsic network, software development for Iot devices (ESP32, Thingsboard, and Android), PCB design for component interconnection, and the configuration of Wi-Fi, Bluetooth, and GPS communications for data collection, storage, and transmission. The obtained results were validated through comparisons with reference measurement instruments and commercial devices, demonstrating accuracy and consistency in the measurements. The study highlights the viability and benefits of e-bikes in terms of energy efficiency, reduced operating costs, and lower environmental impact compared to conventional motor vehicles. This work lays the groundwork for future research and improvements in the field of e-bikes and the optimization of their energy consumption.
AB - Electric bicycles (e-bikes) have emerged as a promising solution to meet urban mobility needs efficiently and sustainably. However, for e-bikes to fulfill their role in sustainable mobility, it is essential to analyze and understand their energy consumption. This work aims to address this issue by developing an IoT device for data acquisition and processing from e-bike sensors. The methodology employed in this study involves the selection and integration of sensors, as well as the integration of the bike's intrinsic network, software development for Iot devices (ESP32, Thingsboard, and Android), PCB design for component interconnection, and the configuration of Wi-Fi, Bluetooth, and GPS communications for data collection, storage, and transmission. The obtained results were validated through comparisons with reference measurement instruments and commercial devices, demonstrating accuracy and consistency in the measurements. The study highlights the viability and benefits of e-bikes in terms of energy efficiency, reduced operating costs, and lower environmental impact compared to conventional motor vehicles. This work lays the groundwork for future research and improvements in the field of e-bikes and the optimization of their energy consumption.
KW - device
KW - e-bike
KW - ESP32
KW - IoT
KW - measurement
UR - https://www.scopus.com/pages/publications/85211801512
U2 - 10.1109/ETCM63562.2024.10746019
DO - 10.1109/ETCM63562.2024.10746019
M3 - Contribución a la conferencia
AN - SCOPUS:85211801512
T3 - ETCM 2024 - 8th Ecuador Technical Chapters Meeting
BT - ETCM 2024 - 8th Ecuador Technical Chapters Meeting
A2 - Rivas-Lalaleo, David
A2 - Maita, Soraya Lucia Sinche
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE Ecuador Technical Chapters Meeting, ETCM 2024
Y2 - 15 October 2024 through 18 October 2024
ER -