International Journal For Multidisciplinary Research

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SmartServ: AI-Powered Vehicle Service Assistance System

Author(s) Mr. Hitesh Daval Nandan, Ms. Sanskruti Sachin Nikam, Mr. Shivam Nanasaheb Pawar, Ms. Tanvi Sunil Kothawade
Country India
Abstract The global automotive service in-
dustry faces ongoing problems with customer
communication, cost estimation, and queue man-
agement. SmartServ offers a strong, scalable,
and low-cost solution that combines artificial
intelligence (AI) and cloud computing to au-
tomate damage detection, cost estimation, and
queue tracking. It uses Convolutional Neural
Networks (CNNs) to automatically identify and
localize vehicle damage and a regression-based
model for severity classification and repair cost
estimation. This system achieves high reliability.
Real-time service updates are handled through
Firebase and Socket.io for smooth user interac-
tion, cutting latency to less than one second. This
paper details SmartServ’s full design, training
methods, dataset characteristics, experimental
results, and deployment structure. Experimental
findings show a damage detection accuracy of
84.16% and a mean error range of 6–9% for
price predictions, exceeding those of traditional
methods. A comparison with existing systems
shows the greater efficiency and transparency of
SmartServ, marking significant progress toward
intelligent, data-driven vehicle maintenance sys-
tems.
Keywords Vehicle Servicing, Artificial In- telligence, Computer Vision, Predictive Analyt- ics, Cost Estimation, Real-Time Tracking, Deep Learning, Regression.
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-13
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.60521
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