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Journal articles on the topic 'OBD II Diagnostics'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

Luo, Feng, Hui Yan Feng, and Chu Liu. "Automotive CAN Bus Diagnostic Device Development." Applied Mechanics and Materials 457-458 (October 2013): 1303–9. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.1303.

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This paper presents a universal CAN Bus diagnostic device that is developed based on the Freescale 32-bit microcontroller MCF51JM128, which complies with OBD-II standard. Specific OBD-II diagnostic services can be performed through the USB request commands from PC software, which is built by Embarcadero Delphi XE; the diagnostic data are collected by the diagnostic device hardware and transferred to the PC for diagnostic result display. Besides, wireless and remote OBD diagnostics can be achieved through the serial interface connection with other communication devices.

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Manalu, Sonya Rapinta, Jurike Moniaga, Dionisius Andrian Hadipurnawan, and Firda Sahidi. "OBD-II and raspberry Pi technology to diagnose car’s machine current condition: study literature." Library Hi Tech News 34, no. 10 (2017): 15–21. http://dx.doi.org/10.1108/lhtn-06-2017-0041.

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Purpose Low-cost microcomputers such as the Raspberry Pi are common in library makerspaces. This paper aims to create an OBD-II technology to diagnose a vehicle’s condition. Design/methodology/approach An OBD-II scanner plugged into the OBD-II port or usually called the data link connector (DLC), sends diagnostics to the Raspberry Pi. Findings Compared with other microcontrollers such as Arduino, the Raspberry Pi was chosen because it sustains the application to receive real-time diagnostics, process the diagnostics and send commands to automobiles at the same time, rather than Arduino that mu

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Sahana H S, Ms. "Onboard Vehicle Diagnosis Fault Monitoring System Using IoT for Electric Vehicle." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47828.

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Abstract— The paper proposes a user-friendly cloud-based data acquisition and analytics system for vehicle diagnostic monitoring in real time. The vehicle's condition is assessed using the Onboard diagnostics (OBD) framework and the report is sent to the mobile of the driver via wifi on detection of unsafe and anomalous events in real time. Vehicle parameter values are instantaneously uploaded to the server. The smartphone app also visualizes data from the sensor and also generates warnings in real time. Keywords: Internet of Vehicles, On-board diagnostics (OBD), Vehicle self-diagnosing system

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Hnatov, Andrii, Shchasiana Arhun, Pavlo Sokhin, and Natalia Hryhorenko. "Using the Car Scanner ELM OBD-II program for diagnosing Hyundai Kona Electric." Vehicle and electronics. Innovative technologies, no. 27 (May 28, 2025): 48–59. https://doi.org/10.30977/veit.2025.27.0.6.

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Problem. The increasing popularity of electric vehicles (EVs) necessitates effective diagnostic methods tailored to their specific components, such as high-voltage batteries, inverters, and traction motors. Traditional diagnostic approaches designed for internal combustion engine (ICE) vehicles are not always suitable for EVs. Goal. To investigate the effectiveness of the Car Scanner ELM OBD-II application for diagnosing electric vehicles, particularly the Hyundai Kona Electric, and to assess its capabilities in monitoring key operational parameters. Methodology. The study involved real-time d

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Michailidis, Emmanouel T., Antigoni Panagiotopoulou, and Andreas Papadakis. "A Review of OBD-II-Based Machine Learning Applications for Sustainable, Efficient, Secure, and Safe Vehicle Driving." Sensors 25, no. 13 (2025): 4057. https://doi.org/10.3390/s25134057.

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The On-Board Diagnostics II (OBD-II) system, driven by a wide range of embedded sensors, has revolutionized the automotive industry by enabling real-time monitoring of key vehicle parameters such as engine load, vehicle speed, throttle position, and diagnostic trouble codes. Concurrently, recent advancements in machine learning (ML) have further expanded the capabilities of OBD-II applications, unlocking advanced, intelligent, and data-centric functionalities that significantly surpass those of conventional methodologies. This paper presents a comprehensive investigation into ML-based applicat

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NIKITIN, DMYTRO, and OLEKSANDR RYBITSKYI. "INTEGRATION OF OBD-II VEHICLE DIAGNOSTICS WITH FINITE STATE MACHINE SOFTWARE DESIGN." Herald of Khmelnytskyi National University. Technical sciences 349, no. 2 (2025): 293–300. https://doi.org/10.31891/2307-5732-2025-349-43.

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This research presents an innovative approach to integrating On-Board Diagnostics II (OBD-II) vehicle diagnostic systems with finite state machine (FSM) software design methodologies. The study addresses the growing complexity of modern vehicle diagnostic systems and proposes a novel framework that combines real-time vehicle diagnostics with automated software control systems. By leveraging FSM-based architectures, this research seeks to enhance diagnostic accuracy, reduce false detections, and provide a scalable solution adaptable to various vehicle models and driving conditions. The integrat

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Kumar Singh, Siddhanta, and Anand Sharma. "Revving up insights: machine learning-based classification of OBD II data and driving behavior analysis using g-force metrics." Bulletin of Electrical Engineering and Informatics 14, no. 3 (2025): 2188–97. https://doi.org/10.11591/eei.v14i3.9398.

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This research work uses machine learning (ML) approaches to classify on-board diagnostics II (OBD II) data and g-force measures to provide a thorough analysis of driving behavior. The research paper effectively demonstrates the classification of driving behaviours using OBD II and g-force data. Driving behaviours are analyzed by using ML algorithms such as random forest (RF), AdaBoost, and K-nearest neighbors (KNN). The analysis goes beyond a summary by discussing how OBD II data, g-force metrics, and the algorithms interrelate to classify ten distinct driving behaviors (e.g., weaving, swervin

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Iskandar, Karto, Alfred Tambayong, Muhammad Rafif Fawwaz Mulya, Steven Cendra Elfanlie, and Maria Grace Herlina. "Mobile-Based Car Diagnostic Application Using Onboard Diagnostic-II Scanner." ComTech: Computer, Mathematics and Engineering Applications 14, no. 2 (2023): 129–41. http://dx.doi.org/10.21512/comtech.v14i2.9138.

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Mobile applications today serve as versatile tools across diverse sectors, enhancing human productivity through specialized software on electronic devices. Implementation of the mobile application can also be applied to vehicles, with inspection and checking functions assisted by the Onboard Diagnostic-II (OBD-II) scanner. The research aimed to develop an integrated mobile application that utilized the OBD-II scanner and Data Acquisition System (DAS) to monitor vehicle health and provide timely service reminders. Vehicle information was taken by the DAS process into a Diagnostic Trouble Code (

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Lim, JoonHoo, Won Yoo, La Kim, You Lee, and Hyung Lee. "Augmentation of GNSS by Low-Cost MEMS IMU, OBD-II, and Digital Altimeter for Improved Positioning in Urban Area." Sensors 18, no. 11 (2018): 3830. http://dx.doi.org/10.3390/s18113830.

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This paper proposes an efficient multi-sensor system to complement GNSS (Global Navigation Satellite System) for improved positioning in urban area. The proposed system augments GNSS by low-cost MEMS IMU (Micro Electro Mechanical Systems Inertial Measurement Unit), OBD (On-Board Diagnostics)-II, and digital altimeter modules. For improved availability of time synchronization in urban area, an adaptive synchronization method is proposed to combine the external PPS (Pulse Per Second) signal and the internal onboard clock. For improved positioning accuracy and availability, a 17-state Kalman filt

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Rimpas, Dimitrios, Andreas Papadakis, and Maria Samarakou. "OBD-II sensor diagnostics for monitoring vehicle operation and consumption." Energy Reports 6 (February 2020): 55–63. http://dx.doi.org/10.1016/j.egyr.2019.10.018.

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Dr, Porag Kalita PhD*1 &. Mr Alakesh Kalita2. "POWER TRAIN AND EMISSION CONTROLS IN PASSENGER VEHICLES: STUDY OF EXHAUST GAS RECIRCULATION ( EGR)." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 2 (2018): 258–71. https://doi.org/10.5281/zenodo.1173460.

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The goal of the On Board Diagnostics is to alert the driver to the presence of a malfunction of the emission control system, and to identify the location of the problem in order to assist mechanics in properly performing repairs. In addition, the On Board Diagnostics ( OBD-II) system should illuminate the malfunction indicator light ( MIL) and store the trouble code in the computer memory for all malfunction that will contribute to increased HC emissions.    Therefore, the power train is controlled by the power train control module (PCM) computer to deliver the required torque to the

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Ramai, Clarence, Veeresh Ramnarine, Shankar Ramharack, Sanjay Bahadoorsingh, and Chandrabhan Sharma. "Framework for Building Low-Cost OBD-II Data-Logging Systems for Battery Electric Vehicles." Vehicles 4, no. 4 (2022): 1209–22. http://dx.doi.org/10.3390/vehicles4040064.

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With the electrification of transport (BEVs) and the growing benefits of smart vehicles, there is a need for a simple solution to perform real-time monitoring of the BEV and its battery for diagnostics and coordinated charging. The On-Board Diagnostics (OBD) system, originally designed for internal combustion engine cars (ICE), can be used to extract the necessary BEV data. This paper presents a developed framework for a low-cost solution to online monitoring of BEVs. A Raspberry Pi Zero W, along with other auxiliary components, was installed in two Hyundai Ioniq Battery Electric cars to commu

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Phophongviwat, Teeraphon, Piyawong Poopanya, and Kanchana Sivalertporn. "Quantitative Assessment of EV Energy Consumption: Applying Coast Down Testing to WLTP and EPA Protocols." World Electric Vehicle Journal 16, no. 7 (2025): 360. https://doi.org/10.3390/wevj16070360.

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This study presents a comprehensive methodology for evaluating electric vehicle (EV) energy consumption by integrating coast down testing with standardized chassis dynamometer protocols under WLTP Class 3b and EPA driving cycles. Coast down tests were conducted to determine road load coefficients—critical for replicating real-world resistance profiles on a dynamometer. Energy usage data were measured using On-Board Diagnostics II (OBD-II) and dynamometer measurements to assess power flow from the battery to the wheels. The results reveal that OBD-II consistently recorded higher cumulative ener

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Yen, Meng-Hua, Shang-Lin Tian, Yan-Ting Lin, Cheng-Wei Yang, and Chi-Chun Chen. "Combining a Universal OBD-II Module with Deep Learning to Develop an Eco-Driving Analysis System." Applied Sciences 11, no. 10 (2021): 4481. http://dx.doi.org/10.3390/app11104481.

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Vehicle technology development drives economic development but also causes severe mobile pollution sources. Eco-driving is an effective driving strategy for solving air pollution and achieving driving safety. The on-board diagnostics II (OBD-II) module is a common monitoring tool used to acquire sensing data from in-vehicle electronic control units. However, different vehicle models use different controller area network (CAN) standards, resulting in communication difficulties; however, relevant literature has not discussed compatibility problems. The present study researched and developed the

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Moniaga, J. V., S. R. Manalu, D. A. Hadipurnawan, and F. Sahidi. "Diagnostics vehicle’s condition using obd-ii and raspberry pi technology: study literature." Journal of Physics: Conference Series 978 (March 2018): 012011. http://dx.doi.org/10.1088/1742-6596/978/1/012011.

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Yousuf, Chilonga, and Mkandawire Mtende. "Vehicle health inspection with enhanced auto diagnostics and maintenance." i-manager's Journal on Mechanical Engineering 14, no. 1 (2024): 34. http://dx.doi.org/10.26634/jme.14.1.20758.

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This paper provides a comprehensive and cost-effective solution for automotive health maintenance and diagnostics. The software performs checks and analyses of key vehicle parameters through the use of the OBD-II (On-Board Diagnostics-II) port on the car. The port has to be physically connected to an interface called the ELM327 Bluetooth or Wi-Fi module that connects to the Android device running the software through Bluetooth or Wi-Fi. On a successful connection, the user can use the software to check the status of electronic control units (ECUs) throughout the vehicle to point out malfunctio

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Bysani, Chaitanya, T. S. Rama Krishna Prasad, and Sridhar Chundi. "Raspberry Pi for Commercial Applications." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 2 (2013): 2250–55. http://dx.doi.org/10.24297/ijct.v11i2.1179.

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The objective of this paper is to create a low cost commercial off the shelf data analyzer for improving automotive safety and design a user interface infotainment system by using Raspberry Pi.Â In this paper we propose Raspberry pi based application that monitor the vehicle ECUs through an OBD-II(On Board Diagnostics) interface, perform Diagnostics with DTCs (Diagnostics trouble codes). Infotainment system having functions such as audio and video playback, games, internet connectivity through either USB Wi-Fi dongles or USB Modems and dashboard camera operation. Raspberry Pi will transmit the

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Putra, Dwi Sudarno, Joe Vane N. Antifuesto, Budi Utomo Wisesa, Zainul Hamidi, and Mutiara Vinta. "Design and development of a portable diagnostic tester for fault detection in EFI vehicle control systems." BIS Energy and Engineering 2 (May 31, 2025): V225043. https://doi.org/10.31603/biseeng.368.

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The evolution of automotive technology has significantly advanced with the adoption of Electronic Fuel Injection (EFI) systems, which offer superior fuel efficiency, environmental friendliness, and enhanced vehicle performance compared to traditional carburetor systems. However, the complexity of EFI systems necessitates sophisticated diagnostic tools, often inaccessible to small-scale workshops due to high costs and proprietary limitations. This study presents the design and development of a Portable Diagnostic Tester as an affordable and effective alternative for diagnosing faults in EFI con

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Rosenberger, Nico, Nikolai Hoffmann, Alexander Mitscherlich, and Markus Lienkamp. "Holistic Approach for Automated Reverse Engineering of Unified Diagnostics Service Data." World Electric Vehicle Journal 16, no. 7 (2025): 384. https://doi.org/10.3390/wevj16070384.

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Reverse engineering of internal vehicle communication is a crucial discipline in vehicle benchmarking. The process presents a time-consuming procedure associated with high manual effort. Car manufacturers use unique signal addresses and encodings for their internal data. Accessing this data requires either expensive tools suitable for the respective vehicles or experienced engineers who have developed individual approaches to identify specific signals. Access to the internal data enables reading the vehicle’s status, and thus, reducing the need for additional test equipment. This results in ve

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Khandakar, Amith, Muhammad E. H. Chowdhury, Rashid Ahmed, et al. "Portable System for Monitoring and Controlling Driver Behavior and the Use of a Mobile Phone While Driving." Sensors 19, no. 7 (2019): 1563. http://dx.doi.org/10.3390/s19071563.

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There is an utmost requirement for technology to control a driver’s phone while driving, which will prevent the driver from being distracted and thus saving the driver’s and passenger’s lives. Information from recent studies has shown that 70% of the young and aware drivers are used to texting while driving. There are many different technologies used to control mobile phones while driving, including electronic device control, global positioning system (GPS), on-board diagnostics (OBD)-II-based devices, mobile phone applications or apps, etc. These devices acquire the vehicle information such a

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Sparis, P. D., P. Botsaris, A. Karkanis, and J. Tatsios. "Three-way catalyst assessment via outlet—inlet temperature measurements: Driving tests." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 211, no. 6 (1997): 445–54. http://dx.doi.org/10.1243/0954407971526579.

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This paper presents and discusses experimental data obtained during driving tests simulating the test cycle, ECE 15, and relates exhaust gas levels of hydrocarbon (HC) and carbon monoxide (CO) to catalyst outlet—inlet temperature differences. It also presents the preliminary results from the operation of a microcontrolled on-board diagnostics (OBD) II catalyst efficiency assessment system based on a statistical analysis of the catalyst outlet—inlet temperature difference thermocouple signal. There are indications that this system performs satisfactorily after an adequate warm-up period, if a s

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Ameen, Hussein Ali, Abd Kadir Mahamad, Sharifah Saon, et al. "Identification of Driving Safety Profiles in Vehicle to Vehicle Communication System Based on Vehicle OBD Information." Information 12, no. 5 (2021): 194. http://dx.doi.org/10.3390/info12050194.

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Driver behavior is a determining factor in more than 90% of road accidents. Previous research regarding the relationship between speeding behavior and crashes suggests that drivers who engage in frequent and extreme speeding behavior are overinvolved in crashes. Consequently, there is a significant benefit in identifying drivers who engage in unsafe driving practices to enhance road safety. The proposed method uses continuously logged driving data to collect vehicle operation information, including vehicle speed, engine revolutions per minute (RPM), throttle position, and calculated engine loa

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Thatipamula, Sai, Muhammad Aadil Khan, and Simona Onori. "On-Board Diagnostics for Li-Ion Batteries Using Electrochemical Impedance Spectroscopy (EIS)-Based Health Estimation Models." ECS Meeting Abstracts MA2024-01, no. 53 (2024): 2802. http://dx.doi.org/10.1149/ma2024-01532802mtgabs.

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There exists a growing need for standardized On-Board Diagnostics (OBD) for electric vehicles [1] to provide accurate health metrics and guarantees to both consumers and manufacturers. Previous work has shown the powerful LIB capacity-based State-of-Health (SoH) estimation capability of Electrochemical Impedance Spectroscopy (EIS) measurements and data-driven models [2] [3]. Since EIS measurements are dependent not only on SoH but also State-of-Charge (SoC) and temperature [4], it is important that the measurements are conducted after the cell reaches an equilibrium, and that these other varia

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Yamashita, Rei-Jo, Hsiu-Hsen Yao, Hiroki Yamashita, and Lo Chi. "Developing a Driver Alert and Alarm System for High Quality Driving Supports." International Journal of Advanced Research in Engineering 3, no. 1 (2017): 16. http://dx.doi.org/10.24178/ijare.2017.3.1.16.

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Abstract—Prevention and vigilance plays a key role in preventing threatening risks and potential dangers when one is driving. In other to achieve the goal of averting danger when driving, people need valid and up to date information about: driving behavior, driving environment and vehicle status. There are a lot of factors that needs to be considered in order to keep a driver safe. Drunk driving, blind spots, bad driving habits, fatigue driving, and vehicle status are all factors that needs to be taken into account if safety is to be improved. Driving comfortability greatly depends on vehicle’

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Rocha, David, Gil Teixeira, Emanuel Vieira, João Almeida, and Joaquim Ferreira. "A Modular In-Vehicle C-ITS Architecture for Sensor Data Collection, Vehicular Communications and Cloud Connectivity." Sensors 23, no. 3 (2023): 1724. http://dx.doi.org/10.3390/s23031724.

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The growth of the automobile industry in recent decades and the overuse of personal vehicles have amplified problems directly related to road safety, such as the increase in traffic congestion and number of accidents, as well as the degradation of the quality of roads. At the same time, and with the contribution of climate change effects, dangerous weather events have become more common on road infrastructure. In this context, Cooperative Intelligent Transport Systems (C-ITS) and Internet of Things (IoT) solutions emerge to overcome the limitations of human and local sensory systems, through t

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Santa, José, Ramon Sanchez-Iborra, Pablo Rodriguez-Rey, Luis Bernal-Escobedo, and Antonio Skarmeta. "LPWAN-Based Vehicular Monitoring Platform with a Generic IP Network Interface." Sensors 19, no. 2 (2019): 264. http://dx.doi.org/10.3390/s19020264.

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Remote vehicle monitoring is a field that has recently attracted the attention of both academia and industry. With the dawn of the Internet of Things (IoT) paradigm, the possibilities for performing this task have multiplied, due to the emergence of low-cost and multi-purpose monitoring devices and the evolution of wireless transmission technologies. Low Power-Wide Area Network (LPWAN) encompasses a set of IoT communication technologies that are gaining momentum, due to their highly valued features regarding transmission distance and end-device energy consumption. For that reason, in this work

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Hong, Seokjoon, Hoyeon Hwang, Daniel Kim, Shengmin Cui, and Inwhee Joe. "Real Driving Cycle-Based State of Charge Prediction for EV Batteries Using Deep Learning Methods." Applied Sciences 11, no. 23 (2021): 11285. http://dx.doi.org/10.3390/app112311285.

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An accurate prediction of the State of Charge (SOC) of an Electric Vehicle (EV) battery is important when determining the driving range of an EV. However, the majority of the studies in this field have either been focused on the standard driving cycle (SDC) or the internal parameters of the battery itself to predict the SOC results. Due to the significant difference between the real driving cycle (RDC) and SDC, a proper method of predicting the SOC results with RDCs is required. In this paper, RDCs and deep learning methods are used to accurately estimate the SOC of an EV battery. RDC data for

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Roman, Adrian-Silviu, Béla Genge, Adrian-Vasile Duka, and Piroska Haller. "Privacy-Preserving Tampering Detection in Automotive Systems." Electronics 10, no. 24 (2021): 3161. http://dx.doi.org/10.3390/electronics10243161.

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Modern auto-vehicles are built upon a vast collection of sensors that provide large amounts of data processed by dozens of Electronic Control Units (ECUs). These, in turn, monitor and control advanced technological systems providing a large palette of features to the vehicle’s end-users (e.g., automated parking, autonomous vehicles). As modern cars become more and more interconnected with external systems (e.g., cloud-based services), enforcing privacy on data originating from vehicle sensors is becoming a challenging research topic. In contrast, deliberate manipulations of vehicle components,

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Lokman Mohd Fadzil, Et al. "Proposal For 6LoWPAN Wireless Network Protocol-Based Street-Light-As-A-Service (SLaaS) Framework To Power Campus Parking Services." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 3974–82. http://dx.doi.org/10.17762/ijritcc.v11i9.9739.

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A novel IPv6 Over Low Power Wireless Personal Area Network (6LoWPAN) protocol-based Street-Light-As-A-Service (SLaaS) research framework for an integrated cloud-based smart university campus parking platform is being proposed. The Intelligent Connected Street Light infrastructure currently in existence at University Sains Malaysia (USM) is being redesigned. As part of overall parking proposal, approaching object image and video data are being acquired using a range of sensors, including the passive infrared (PIR) and 3-D Light Detection and Ranging (LIDAR) motion sensors. To acquire and transm

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Silva, Marianne, Elton Vieira, Gabriel Signoretti, Ivanovitch Silva, Diego Silva, and Paolo Ferrari. "A Customer Feedback Platform for Vehicle Manufacturing Compliant with Industry 4.0 Vision." Sensors 18, no. 10 (2018): 3298. http://dx.doi.org/10.3390/s18103298.

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In the last decade, the growth of the automotive market with the aid of technologies has been notable for the economic, automotive and technological sectors. Alongside this growing recognition, the so called Internet of Intelligent Vehicles (IoIV) emerges as an evolution of the Internet of Things (IoT) applied to the automotive sector. Closely related to IoIV, emerges the concept of Industrial Internet of Things (IIoT), which is the current revolution seen in industrial automation. IIoT, in its turn, relates to the concept of Industry 4.0, that is used to represent the current Industrial Revol

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Moshynska, Alina, and Oleksandr Khrokalo. "REMOTE VEHICLE DIAGNOSTIC SYSTEM DEVELOPMENT BASED ON THE INTERNET OF THINGS TECHNOLOGY." Information and Telecommunication Sciences, no. 1 (June 28, 2024): 28–32. http://dx.doi.org/10.20535/2411-2976.12024.28-32.

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Background. Advanced artificial intelligence and IoT gateways are working together in the automotive industry to predict potential vehicle problems by analysing sensor data and optimizing quality control processes. Manufacturers can detect anomalies, improve product reliability, and eliminate manufacturing defects or malfunctions in advance. Predictive analytics also lead to improved fuel efficiency, performance and overall vehicle reliability. Objective. The purpose of this work is to develop a model for remote diagnosis of vehicle faults using a Raspberry Pi model B microcomputer and a SIM76

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Kumar Singh, Siddhanta, and Ajay Kumar Singh. "Vehicular impact analysis of driving for accidents using on board diagnostic II." Bulletin of Electrical Engineering and Informatics 11, no. 5 (2022): 2696–704. http://dx.doi.org/10.11591/eei.v11i5.3864.

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A large number of people meet with an accident everyday around the world. One of the leading causes of death is traffic accidents. The reasons behind India's rising number of road accidents contribute to bad driving behavior, poor road design and infrastructure, lack of enforcement of traffic laws. The post accidental investigation report is very important to know the actual reason of collision for the concerned parties and the insurance company and the police. The proposed work effectively extracts interpretable features describing complex driving patterns. It will provide analytical report o

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Muhamad Fadzil, Nur Farisya Aqilah, Hilda Mohd Fadzir, Hafizah Mansor, and Untung Rahardja. "Driver Behaviour Classification: A Research using OBD-II Data and Machine Learning." Journal of Advanced Research in Applied Sciences and Engineering Technology 56, no. 3 (2024): 147–57. https://doi.org/10.37934/araset.56.3.147157.

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Classification of driver behaviour has gained much attention due to its potential in a variety of applications, and On-Board Diagnostic (OBD) real-time data is often under-utilised. Hence, using On-board Diagnostic-II (OBD-II) data by categorising drivers based on their driving behaviour can be an efficient method. The objective of this study is to identify groups of drivers based on their driving styles using the collected OBD-II data. This study uses a Kaggle-obtained online dataset of OBD-II. The suggested model in this study analyses driving behaviour using both supervised and unsupervised

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Wang, Zhao Hai, and Bing Hua Huang. "The Research and Development of an Automotive Fault Real-Time Alarming System." Applied Mechanics and Materials 184-185 (June 2012): 1578–83. http://dx.doi.org/10.4028/www.scientific.net/amm.184-185.1578.

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The authors have researched on the communication protocols and the diagnostic modes used by the second generation of On-Board-Diagnosis (OBD-II) system and put forward a project scheme of automotive fault real-time alarming system based on OBD-II system. The Total Control Unit (TCU) of the alarming system, the signal conversion module between TCU and OBD-II system, the preliminary expert system of automotive fault diagnosis, LCD display system and phonic broadcast system have been developed. Test results on sample machines prove that the alarming system can successfully acquires data stream &a

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Md., Abbas Ali Khan, Hanif Ali Mohammad, Haque Fazlul, and Tarek Habib Md. "A machine learning approach for driver identification." A machine learning approach for driver identification 30, no. 1 (2023): 276–88. https://doi.org/10.11591/ijeecs.v30.i1.pp276-288.

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Driver identification is a momentous field of modern decorated vehicles in the perspective of the controller area network (CAN-Bus). Many conventional systems are used to identify the driver. One step ahead, most of the researchers use sensor data of CAN-Bus but there are some difficulties because of the variation of a protocol of different models of vehicle. We aim to identify the driver through supervised learning algorithms based on driving behavior analysis. To identify the driver, a driver verification technique is proposed that evaluate driving pattern using the measurement of CAN sensor

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Din, M. A. C., M. T. A. Rahman, H. A. Munir, A. Rahman, and A. F. A. Hamid. "Development of CAN Bus Converter for On Board Diagnostic (OBD-II) System." IOP Conference Series: Materials Science and Engineering 705 (December 2, 2019): 012011. http://dx.doi.org/10.1088/1757-899x/705/1/012011.

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Kim, Hwa-Seon, Seong-Jin Jang, Jae-Hyun Nam, and Jong-Yug Jang. "Implement of Knocking diagnostic algorithm and design of OBD-II Diagnostic system S/W on common-rail engine." Journal of the Korean Institute of Information and Communication Engineering 16, no. 11 (2012): 2446–52. http://dx.doi.org/10.6109/jkiice.2012.16.11.2446.

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Jeong, Da-Woon, Jae-Hyun Nam, and Jong-Wook Jang. "A Implementation of motorcar consumption diagnostic management iPhone based software with OBD-II and WiFi network." Journal of the Korean Institute of Information and Communication Engineering 15, no. 11 (2011): 2347–52. http://dx.doi.org/10.6109/jkiice.2011.15.11.2347.

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Vlakh-Vyhrynovska, Halyna, and Maksym Budzin. "MODULAR ARCHITECTURE AND DATA PROCESSING ALGORITHMS IN C-ITS SYSTEMS." Measuring Equipment and Metrology 86 (2025): 61–66. https://doi.org/10.23939/istcmtm2025.01.061.

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This research investigates the use of data obtained through the OBD-II diagnostic interface and the CAN bus in C- ITS systems, using processing methods such as Pearson correlation analysis and linear interpolation. C-ITS systems are designed to enhance road safety and efficiency, particularly in urban environments. The paper examines existing approaches to sensor data processing and V2I communication quality prediction using GRU and VMD-BO-BiLSTM models, and also explores the role of mobile applications in integrating traffic participants.

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Khan, Md Abbas Ali, Mohammad Hanif Ali, Fazlul Haque, and Md Tarek Habib. "A machine learning approach for driver identification." Indonesian Journal of Electrical Engineering and Computer Science 30, no. 1 (2023): 276. http://dx.doi.org/10.11591/ijeecs.v30.i1.pp276-288.

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Driver identification is a momentous field of modern decorated vehicles in the perspective of the controller area network (CAN-Bus). Many conventional systems are used to identify the driver. One step ahead, most of the researchers use sensor data of CAN-Bus but there are some difficulties because of the variation of a protocol of different models of vehicle. We aim to identify the driver through supervised learning algorithms based on driving behavior analysis. To identify the driver, a driver verification technique is proposed that evaluate driving pattern using the measurement of CAN sensor

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Kim, Hwa-seon, Seong-jin Jang, and Jong-wook Jang. "A Study on Development of Engine Fault Diagnostic System." Mathematical Problems in Engineering 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/271374.

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This study implemented a mobile diagnosing system that provides user-centered interfaces for more precisely estimating and diagnosing engine conditions through communications with the self-developed ECU only for industrial CRDI engine use. For the implemented system, a new protocol was designed and applied based on OBD-II standard to receive engine data values of the developed ECU. The designed protocol consists of a message structure to request data transmission from a smartphone to ECU and a response message structure for ECU to send data to a smartphone. It transmits 31 pieces of engine con

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Pan, Yu-Jen. "Evaluation of Drivers' Driving Behavior in Heavy Traffic Situations from OBD-II Data." International Journal of Membrane Science and Technology 10, no. 2 (2023): 419–26. http://dx.doi.org/10.15379/ijmst.v10i2.1214.

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The analysis and discussion of the onboard diagnostic data will help understand the driver's behavioral characteristics and develop a sustainable transportation system. The research content of this paper is to mine the driving behavior data through the vehicle preload equipment, analyze the factors affecting safe driving and establish a prediction model. This study collected data from 50 Taiwanese drivers while operating in heavy traffic. Understand the driver's behavioral characteristics through data analysis, such as calculating the times of the driver's emergency braking is based on the dri

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Kumar Singh, Siddhanta, and Ajay Kumar Singh. "Driving pattern analysis to determine driver behaviors for local authority based on cloud using OBD II." International journal of electrical and computer engineering systems 13, no. 10 (2022): 937–44. http://dx.doi.org/10.32985/ijeces.13.10.14.

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Aggressive driving is the main cause of road accidents and it is affected by driving behavior which endanger not only the driver himself but also the people around. It is very significant step to identify such behaviors of the drivers by the local authorities which would help in correcting the behaviors or to understand the root cause of the accidents by analyzing the data recorded by the On Board Diagnostic( OBD ) II device. An aggressive driving behavior is characterized by sudden change inmaneuverings of vehicle which eventually yields non uniform parameters values returned by the ECU (Engi

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BOGUŚ, Piotr. "Misfire detection in a diesel engine using clustering in a short-time analysis of vibroacoustic signals." Combustion Engines 123, no. 4 (2005): 31–40. http://dx.doi.org/10.19206/ce-117367.

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The paper presents some results of the research on new diagnostic methods in combustion engines. It describes the application of short-time signal analysis together with pattern recognition techniques in the diagnosis of misfire in Diesel engines through vibroacoustic signals. One considered Diesel locomotive in particular. In the area of the nonroad sources of combustion gases the locomotives rate relatively high as air polluters. There are some regulations in the area of locomotives (e.g. Cart UIC 623 1-2-3 in Europe) but we still observe a lack of obligatory requirements for systems monitor

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Turker, Gul Fatma, and Akif Kutlu. "Methods of monitoring Vehicle’s CAN data with mobile devices." Global Journal of Computer Science 5, no. 1 (2015): 51. http://dx.doi.org/10.18844/gjcs.v5i1.31.

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<p>Informing the drivers are very important for ensuring the traffic flow properly and safely in highway transportation. Mobile devices take part in technologies that support the improvement of intelligent systems in traffic management and control systems which vehicle and way knowledge are shared. Due to the GPS, Accelaration, wi-fi etc. features of smart phones developed by using built-in sensors are prefered to use in traffic. In this study, how diagnostic tool ELM327, which reads data through vehicle network, communicates with mobile devices, what type of software are used for data t

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Yang, Yalian, Baolin Chen, Lin Su, and Datong Qin. "Research and Development of Hybrid Electric Vehicles CAN-Bus Data Monitor and Diagnostic System through OBD-II and Android-Based Smartphones." Advances in Mechanical Engineering 5 (January 2013): 741240. http://dx.doi.org/10.1155/2013/741240.

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Yamaji, Kouki, and Hirokazu Suzuki. "Research on Variable Cylinders of the Tandem 4-Cylinder Gasoline Engine for Fuel Economy." Journal of Robotics and Mechatronics 20, no. 1 (2008): 75–81. http://dx.doi.org/10.20965/jrm.2008.p0075.

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With progress in internal combustion engine fuel economy, variable cylinder systems have attracted attention. We measured fuel consumption in cylinder cutoff by stopping the injector alone, collected data changing the location and number of cutoff cylinders and when varying the cutoff cylinder, and compared the difference in fuel cost reduction. A transistor is inserted serially into the injector control circuit of the electronic control unit (ECU). By controlling the transistor via microcomputer, the injector is turned on or off independently from ECU control in obtain cylinder cutoff. The am

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Yusupov Sarvarbek Sodiqovich and Inoyatkhodjaev Jamshud Shukhratullaevich. "Analysis of test results using an automatic start-stop system in vehicle driving modes." Open Journal of Science and Technology 4, no. 2 (2021): 77–84. http://dx.doi.org/10.31580/ojst.v4i2.1791.

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In this paper, the energy efficiency of automobiles through the automatic start-stop system as a part of the intelligent transport systems was determined by the research method. In the research method, the vehicle's driving mode was analyzed according to the NEDC (New European Driving Cycle) standard. The M1 category Chevrolet Nexia used the method of measuring fuel consumption by volume in the drive cycle at the auto polygon. In this method, the capabilities of the car's design and electronic control unit were used to determine fuel consumption and vehicle speed. The data were obtained via OB

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Silva, Marianne, Gabriel Signoretti, Julio Oliveira, Ivanovitch Silva, and Daniel G. Costa. "A Crowdsensing Platform for Monitoring of Vehicular Emissions: A Smart City Perspective." Future Internet 11, no. 1 (2019): 13. http://dx.doi.org/10.3390/fi11010013.

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Historically, cities follow reactive planning models where managers make decisions as problems occur. On the other hand, the exponential growth of Information and Communication Technologies (ICT) has allowed the connection of a diverse array of sensors, devices, systems, and objects. These objects can then generate data that can be transformed into information and used in a more efficient urban planning paradigm, one that allows decisions to be made before the occurrence of problems and emergencies. Therefore, this article aims to propose a platform capable of estimating the amount of carbon d

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Rojas-Reinoso, Vicente, Janko Alvarez-Loor, Henrry Zambrano-Becerra, and José Antonio Soriano. "Comparative Study of Gasoline Fuel Mixture to Reduce Emissions in the Metropolitan District." Sustainability 15, no. 4 (2023): 2921. http://dx.doi.org/10.3390/su15042921.

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In the present investigation, the behavior of fuel consumption was studied due to the high cost of gasoline and its price increase in Ecuador in recent years, for which reason the different mixtures have been studied to obtain lower consumption. The optimum fuel mixture rate for a T18SED e-tec II engine, Multiport Electronic Fuel Injection System (MPFI) between extra gasoline, super gasoline, and ethanol was obtained on two urban roads in the city of Quito (Ecuador). For the first test, mixtures of 10% super gasoline and 90% extra gasoline were made, and so on, for the following tests: (20–80)

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