Computer Science and Information Technologies Vol. 6, No. 2, July 2025, pp. 122~135 ISSN: 2722-3221, DOI: 10.11591/csit.v6i2.pp122-135  122 Journal homepage: http://iaesprime.com/index.php/csit Smart brake pad early warning system: enhancing vehicle safety through real-time monitoring Afif Syam Fauzi 1 , Giva Andriana Mutiara 1 , Muhammad Rizqy Alfarisi 1 , Tedi Gunawan 2 , Muhammad Aulia Rifqi Zain 1 1 Computer Technology Study Program, Faculty of Applied Science, Telkom University, Bandung, Indonesia 2 Information System Study Program, Faculty of Applied Science, Telkom University, Bandung, Indonesia Article Info ABSTRACT Article history: Received Jan 25, 2025 Revised Mar 24, 2025 Accepted May 23, 2025 A contributing factor to traffic accidents is brake pad failure, which diminishes braking system performance and extends braking distance. This work develops a prototype utilizing internet of things (IoT) to measure brake pad thickness, hence enhancing driver awareness through real-time monitoring. The system establishes the thickness detection threshold at 75% (3-4 mm) and 50% (5–6 mm) as a cautionary parameter. The thickness parameter employs an American wire gauge (AWG) 18 cable to connect to the ESP32 microcontroller. The web-based IoT monitoring interface employs Laravel. This method enables drivers to get prompt notifications regarding the decrease in brake pad thickness, hence permitting urgent preventative maintenance to mitigate the risk of accidents. The system underwent testing through friction at a rotational speed of 600 to 6,000 rpm. The test findings indicated that the sensor precisely measured the brake pad thickness with a prototype response time of a second. This system is suitable for implementation on old model vehicles that do not have an early warning system. The installation of this technology is anticipated to enhance driver knowledge of the state of the brake pads, hence potentially diminishing the danger of brake system failure caused by unmonitored pad wear. Keywords: Brake pad Brake pad thickness Early warning system ESP-32 Internet of things This is an open access article under the CC BY-SA license. Corresponding Author: Giva Andriana Mutiara Computer Technology Study Program, Faculty of Applied Science, Telkom University Bandung, Indonesia Email: givamz@telkomuniversity.ac.id 1. INTRODUCTION Globally, there are 3,700 deaths due to traffic accidents every day [1]. The factors that cause accidents are due to human error, environmental conditions, vehicle or mechanical errors, and other factors. Although human error is still the biggest factor that causes accidents, mechanical vehicle factors also need to be considered to reduce human error against vehicle maintenance negligence factors. This is because referring to the high number of traffic accidents globally, there are also accidents caused by the failure of vehicle components due to lack of maintenance on some vital components in the vehicle itself. While vehicle-related issues contribute to a smaller percentage, they can have devastating consequences. Mechanical failures are brake failures (2-5%), tire blowouts (2-4%), engine and power loss (1-3%), and light issues (1-2%) [2]. To ensure passenger safety, today's vehicles are equipped with various sensors that are embedded in the vehicle system and can be monitored in real-time. To mitigate the risk of accidents and protect human lives, it is essential to enhance the deceleration mechanisms in vehicles through the integration of early warning system technology [3].