Developing smart tire pressure monitoring system: A performance evaluation of ESP32-C3 with ESP-NOW communication

Reftito Indi  Muhammad; Giva Andriana  Mutiara; Muhammad Rizqy  Alfarisi; Lisda  Meisaroh; Abdul Rahman  Saleh

doi:10.18488/76.v12i2.4215

Authors

Reftito Indi Muhammad Faculty of Applied Science, Telkom University, Jl. Telekomunikasi No. 1, Bandung, West Java, Indonesia. https://orcid.org/0009-0008-4273-4981
Giva Andriana Mutiara Faculty of Applied Science, Telkom University, Jl. Telekomunikasi No. 1, Bandung, West Java, Indonesia. https://orcid.org/0000-0003-4387-6128
Muhammad Rizqy Alfarisi Faculty of Applied Science, Telkom University, Jl. Telekomunikasi No. 1, Bandung, West Java, Indonesia. https://orcid.org/0000-0002-6378-0062
Lisda Meisaroh Faculty of Applied Science, Telkom University, Jl. Telekomunikasi No. 1, Bandung, West Java, Indonesia. https://orcid.org/0009-0006-3346-2975
Abdul Rahman Saleh Faculty of Applied Science, Telkom University, Jl. Telekomunikasi No. 1, Bandung, West Java, Indonesia. https://orcid.org/0009-0009-8192-9631

DOI:

https://doi.org/10.18488/76.v12i2.4215

Keywords:

ESPNOW, Internet of Things, Microcontroller, Tire pressure monitoring system, Tire temperature.

Abstract

This study aims to develop a low-cost and energy-efficient Tire Pressure Monitoring System (TPMS) that provides real-time monitoring of tire pressure and temperature using IoT-based wireless communication. The system was built using the MS5803-14BA sensor, ESP32-C3 microcontroller, and ESP-NOW wireless protocol. Performance was tested through laboratory and real-world scenarios and compared to two commercial TPMS systems (Level A and B). The proposed TPMS achieved 95.91% accuracy, closely aligning with Level A (99.87%) and slightly outperforming Level B (95.35%). It showed the highest temperature sensitivity (10.00%) while maintaining stable pressure readings (6.45%). In contrast, Level B exhibited greater pressure fluctuation (9.68%). The ESP-NOW protocol enabled reliable, low-power data transmission without interference. The developed system delivers high accuracy in detecting tire conditions in real time and demonstrates superior power efficiency and environmental stability, making it a strong alternative to traditional RF-based TPMS solutions. This system can be integrated into smart vehicles or fleet management platforms, enhancing safety through real-time alerts and enabling predictive maintenance. Future enhancements will include broader IoT connectivity, improved calibration, and extended testing in extreme conditions.