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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21686
Article Published : 8549
Total Authors : 22487
Total Reviewer : 811
Total Countries : 159
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| Paper Title: | Real-Time Classification of Driving Behavior for Fuel Efficiency Optimization Using Machine Learning |
| Authors Name: | Shantaraddy , Yash sharma , Indushree l , Dr. Manjunath T K |
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IJRTI_203448
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| Published Paper Id: | IJRTI2505038 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | This study explores the application of machine learning techniques in optimizing driving behavior for improved fuel efficiency and road safety. By utilizing OBD-II data and real-time driving behavior classification, the proposed system leverages machine learning algorithms such as Random Forest, SVM, and deep learning methods to analyze and predict driving patterns. The integration of real-time feedback mechanisms, including attention-based monitoring and Explainable AI, provides personalized insights to help drivers adopt fuel-efficient and safer driving habits. The research highlights the potential of combining clustering techniques, energy estimation models, and event detection to enhance energy management and safety applications. Results demonstrate a significant reduction in aggressive driving tendencies and fuel consumption, emphasizing the effectiveness of predictive analytics in transportation systems. Future work will focus on expanding datasets, enhancing classification accuracy with deep learning, and implementing these models in Advanced Driver Assistance Systems (ADAS) for broader impact. The findings suggest that AI-driven solutions can play a pivotal role in creating sustainable, data-driven transportation systems that benefit both drivers and the environment. |
| Keywords: | Driving Behavior, Machine Learning, Fuel Efficiency, Real-time Feedback, Predictive Analytics. |
| Cite Article: | "Real-Time Classification of Driving Behavior for Fuel Efficiency Optimization Using Machine Learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.a382-a386, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505038.pdf |
| Downloads: | 000448 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505038
Registration ID:203448
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: a382-a386 Country: banglore, karnataka, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505038 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505038 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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