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Paper ID:IJSREM62501

Development of IoT-Integrated Real-Time Performance Monitoring Systems for Conventional Internal Combustion Engine Vehicles

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM62501

Volume:

10 |

5 |

May 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AN

Abhijeet Nanotkar

Mechanical engineering

Shri sant gajanan maharaj college of engineering shegaon

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AU

Adinath Udgirkar

Mechanical engineering

Shri sant gajanan maharaj college of engineering shegaon

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TR

Tushar Raut

Mechanical engineering

Shri sant gajanan maharaj college of engineering shegaon

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PKS

Pragati K Sonone

Mechanical engineering

Shri sant gajanan maharaj college of engineering shegaon

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Gb

Gayatri bhore

Mechanical engineering

Shri sant gajanan maharaj college of engineering shegaon

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Abstract

The proliferation of the Internet of Things (IoT) has catalyzed a paradigm shift in automotive telematics, moving beyond fleet management to empower individual owners of conventional internal combustion engine (ICE) vehicles. This paper reviews the developmental trajectory, architectural frameworks, key enabling technologies, applications, and challenges associated with IoT-integrated real-time performance monitoring systems for conventional cars. We analyze the evolution from basic On-Board Diagnostics (OBD-II) loggers to sophisticated cloud-based analytics platforms that leverage Machine Learning (ML) and edge computing. The core architecture is deconstructed into sensing (via OBD-II and additional sensors), connectivity (4G/5G, Bluetooth, CAN Bus), cloud processing, and user-facing applications. Key applications reviewed include predictive maintenance, real- time diagnostics, eco-driving assistance, security enhancement, and usage-based insurance (UBI). Despite significant advancements, challenges such as data security, privacy, system interoperability, and network latency remain critical hurdles. This review concludes that the continued integration of IoT in conventional vehicles is not only bridging the data gap with connected and electric vehicles but also creating a new ecosystem for automotive aftermarket services, enhanced safety, and sustainable vehicle ownership.

KEYWORDS

Keywords: Internet of Things (IoT) Automotive Telematics Real-Time Monitoring OBD-II Predictive Maintenance Connected Car Cloud Computing CAN Bus.

Cite This Article

Abhijeet Nanotkar, Adinath Udgirkar, Tushar Raut, Pragati K Sonone, Gayatri bhore, "Development of IoT-Integrated Real-Time Performance Monitoring Systems for Conventional Internal Combustion Engine Vehicles," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-4, May 2026.

Full Article/Conclusion

The development of IoT-integrated real-time performance monitoring systems has fundamentally changed the relationship between owners and their conventional vehicles. By leveraging a stack of technologies from the standardized OBD-II port to powerful cloud- based AI, these systems have democratized advanced telematics, making it accessible for the entire fleet of existing ICE vehicles. They deliver tangible benefits in cost savings, safety, security, and environmental impact. While challenges related to security, privacy, and interoperability must be continuously addressed, the trajectory is clear: the conventional car is becoming a deeply connected, intelligent, and data-rich component of the broader IoT ecosystem, paving the way for a smarter and more sustainable automotive future.

References

[1]         Ashton, K. (2009). That 'Internet of Things' Thing. RFID Journal. [2]         He, Y., Nie, L., Guo, T., & Liu, F. (2019). A Survey on Vehicle Telematics: Architecture, Applications, and Challenges. IEEE Internet of Things Journal. [3]         Chen, B., Wan, J., Shu, L., Li, P., Mukherjee, M., & Yin, B. (2018). Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges. IEEE Access. [4]         Koscher, K., et al. (2010). Experimental Security Analysis of a Modern Automobile. IEEE Symposium on Security and Privacy. [5]         Staples, M., & Niazi, M. (2007). Experiences using systematic review guidelines. Journal of Systems and Software. ·                         Specific product literature from industry leaders (e.g., Automatic, Mojio, Verizon Connect) was also consulted.  

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Publication Date

5/6/2026

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Double-Blind Peer Review

Review Rounds: 2

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