Page 335 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD)
Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies
Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470

Smart Vehicle Management System:

A Case Study of VehicleLogix for Valuation Precision

Prathamesh Machave , Harshal Karare , Prof. Usha Kosarkar
1
3
2
1,2,3 Department of Science and Technology,
1,2 G H Raisoni Institute of Engineering and Technology, Nagpur, Maharashtra, India
3 G H Raisoni College of Engineering and Management, Nagpur, Maharashtra, India

ABSTRACT [Author Name] highlights the integration of GPS and
Vehicle management systems play a pivotal role in modern telematics in improving fleet efficiency. This technology
transportation by streamlining operations, optimizing asset facilitates better decision-making, reduces delays, and
utilization, and improving valuation precision. This paper ensures higher vehicle utilization.
focuses on "VehicleLogix," a smart vehicle management 2. Predictive Maintenance Systems: Studies by [Author
system that integrates advanced algorithms, IoT sensors, Name] emphasize the role of predictive analytics in
and data analytics to enhance valuation accuracy. By
leveraging real-time data and predictive modeling, reducing downtime by anticipating vehicle failures.
Predictive maintenance systems not only improve
VehicleLogix enables precise assessments of vehicle health, reliability but also contribute to cost savings by
market value, and operational efficiency. The study
demonstrates how this system enhances decision-making preempting expensive repairs.
for fleet operators, dealerships, and insurers, ultimately 3. Valuation Models: Research in machine learning has led
improving productivity and cost efficiency. Furthermore, to advancements in automated valuation models (AVMs)
the implications for sustainability and regulatory for vehicles. [Author Name] explores the use of AI
compliance are discussed, showcasing the holistic benefits algorithms for predicting residual values and market
of adopting such systems. trends. These models provide a scientific basis for

setting vehicle prices, enhancing transparency for
KEYWORDS: Smart Vehicle Management, IoT, Data Analytics, buyers and sellers.
VehicleLogix, Valuation Precision, Fleet Management,
Predictive Analytics, Sustainability 4. Data-Driven Decision Making: [Author Name] discusses
the role of data analytics in transforming traditional fleet
I. INTRODUCTION management practices. By leveraging historical and real-
The advent of smart technologies has transformed the time data, organizations can achieve strategic goals
automotive industry, driving innovations in vehicle more effectively.
management. As transportation networks grow more VehicleLogix builds on these technologies to create a unified
complex, traditional methods of vehicle valuation and fleet platform for valuation precision and operational
management struggle to keep pace with the demands for management, setting a new benchmark for the industry.
real-time insights, predictive analytics, and operational
efficiency. III. Proposed Work
The proposed VehicleLogix framework consists of the
VehicleLogix represents a cutting-edge solution designed to following components:
address these challenges. By combining IoT-enabled sensors,
machine learning algorithms, and advanced data A. Data Acquisition
visualization techniques, the system delivers precise and VehicleLogix employs IoT-enabled sensors to collect data on:
actionable insights into vehicle valuation and operational Ø Vehicle health metrics (engine performance, tire
health. The comprehensive capabilities of VehicleLogix pressure, fuel efficiency, etc.)
extend beyond individual vehicle monitoring to fleet-wide Ø Environmental conditions such as road quality and
optimization, reducing inefficiencies and improving weather
profitability.
Ø Driver behavior, including speed, braking patterns, and
This paper examines the framework, implementation, and fuel consumption trends
efficacy of VehicleLogix, highlighting its potential to
revolutionize vehicle management practices. The study B. Data Processing
evaluates its impact on stakeholders, including fleet The system utilizes edge computing to preprocess raw data
operators, dealerships, insurers, and regulatory bodies. and transfer actionable insights to the cloud. This approach
Additionally, it explores the broader implications for minimizes latency and reduces data transmission costs while
sustainability by reducing carbon footprints and minimizing ensuring real-time performance.
waste through predictive maintenance. C. Predictive Analytics

II. Related Work Machine learning models are employed to:
1. IoT in Fleet Management: IoT technologies have been Ø Predict market trends for vehicle valuation based on
widely adopted in fleet management to enhance real- historical and current data
time monitoring and data acquisition. Research by

IJTSRD | Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies Page 325