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Smart Forecasting: AI-Driven Image and Plate Recognition and Predictive Traffic Analysis
ISBN Book

Smart Forecasting: AI-Driven Image and Plate Recognition and Predictive Traffic Analysis

Author:
Sarath Babu Gosipathala

ISBN: 978-93-49929-10-4

DOI: https://doi.org/10.63282/978-93-49929-10-4


Smart Forecasting: AI-Driven Image and Plate Recognition and Predictive Traffic Analysis examines how computer vision and predictive modeling can transform traffic management from a reactive discipline into a genuinely anticipatory one — moving beyond systems that simply record what has already happened toward systems that can see, recognize, and forecast what is about to happen. For decades, traffic management has relied on tools built for a slower, more predictable world: fixed-timing signals, manual monitoring, and historical averages that struggle to keep pace with the volatility of modern urban mobility ride-sharing surges, delivery fleets, shifting commute patterns, and events that can alter traffic volumes within minutes. Meanwhile, advances in deep learning-based computer vision have made it possible to extract structured, actionable information directly from live camera feeds — detecting vehicles, reading license plates, and classifying traffic conditions in real time and at scale. This book explores what becomes possible when that recognition capability is paired with predictive analytics: traffic systems that don't just observe congestion, but anticipate it before it fully forms.


Sarath Babu Gosipathala is an Independent Researcher based in the USA with over 21 years of experience in project and product development, specializing in architecting, designing, developing, and performance engineering enterprise applications built on Microsoft technologies. Sarath Babu received his Master’s degree (2001) in Computer Applications from the University of Hyderabad, India. His career reflects a rare combination of deep technical expertise and long-term domain specialization, having spent more than 14 years working within the Electronic Toll Collection domain, where he has helped shape systems that are critical to the everyday functioning of modern transportation infrastructure. His position oversees mission critical platforms that process millions of daily financial and vehicle based transactions, ensuring accuracy, continuity, and compliance for major toll agency operations.

His role requires deep expertise in high volume transaction processing, distributed systems, real time data workflows, and the unique regulatory and technical requirements of intelligent transportation systems. Throughout his career, Sarath has handled technically challenging assignments across the full software development lifecycle, from initial design through implementation, bringing a disciplined, end-to-end perspective to every project he undertakes. His experience extends beyond pure engineering into the strategic and analytical dimensions of technology delivery, including working on Request for Proposals (RFP) and conducting gap analyses for Requirements Traceability Matrices (RTMs) — work that demands both technical precision and a clear understanding of business and regulatory requirements. He has also served as a critical liaison between agencies, operations teams, and development teams, translating between stakeholders with very different priorities and vocabularies to ensure that complex systems are delivered successfully and function reliably in the field.


Title: Smart Forecasting: AI-Driven Image and Plate Recognition and Predictive Traffic Analysis
Author: Sarath Babu Gosipathala
Publisher: ScienceTech Xplore
Copyright: ScienceTech Xplore
Language: English
Publication Format: Online
ISBN: 978-93-49929-10-4
DOI: https://doi.org/10.63282/978-93-49929-10-4
Subject/Genre: Artificial Intelligence
Pages: 1-223
Chapters: 12
Year of Publication: 2019
URL: https://sciencetechxplore.org/978-93-49929-10-4.php
Cite As:

Gosipathala, S. B. (2019). Smart Forecasting: AI-Driven Image and Plate Recognition and Predictive Traffic Analysis. ScienceTech Xplore. https://doi.org/10.63282/978-93-49929-10-4

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