Smart EV Navigation and Data Collection System for Tree Based Data Modeling Using IoT

DOI

10.2991/978-94-6463-084-8_13How to use a DOI?

Keywords

Internet of Things; Smart Electrical Vehicle; Genetic Programming

Abstract

Machine learning for autonomous can be done by recording the displacement and condition of the vehicle through manual control by humans and modeling the data. The research proposes designing a data collection system for tree-based data modeling on Internet of Things (IoT) based autonomous electrical vehicles (EV). The system consists of four ESP32 cameras with servos mounted on the left, right side of the car mirror, front (dashcam), and rear. The system is also equipped with an Arduino Nano connected to GPS, a gyroscope, and four proximity sensors. Arduino nano is connected via serial software to the Wemos D1 mini, which is connected to a relay module to control lights and wipers and is equipped with an LDR sensor. Data collected via the internet (wifi) will be formed in tree-based data modeling for future genetic programming machine learning algorithms. System evaluation includes Quality of Service (QoS) data communication, statistical data collected, and electrical IoT devices built. Based on testing using an intelligent car chassis in an environment still affordable by wifi, it produces an average delay of 0.02 s and a PDR of 99.87%. The highest correlation matrix archived as 0.872 for longitude, latitude, and gyro data in detecting vehicle turns. The electricity evaluation result consists of average power consumption of 0.344 W for the ESP32 camera, 0.663 W for the Arduino nano, and 0.291 W for the Wemos d1 mini. In the future, testing will be carried out using an actual EV on a real track and in data communication outside of wifi.

Copyright

© 2022 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Wirarama Wedashwara
AU  - Heri Wijayanto
AU  - Andy Hidayat Jatmika
AU  - I Wayan Agus Arimbawa
PY  - 2022
DA  - 2022/12/26
TI  - Smart EV Navigation and Data Collection System for Tree Based Data Modeling Using IoT
BT  - Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
PB  - Atlantis Press
SP  - 130
EP  - 141
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-084-8_13
DO  - 10.2991/978-94-6463-084-8_13
ID  - Wedashwara2022
ER  -