Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
In present-day urbanized, high-speed
environments, it’s is imperative to know
traffic flow for effective management of
transportation. In this project, traffic flow is
studied using GPS data, providing useful
insights regarding congestion areas, most
congested routes and busiest traffic times.
By using GPS coordinates, timestamp, and
speed data, we are able to trace the
movement of vehicles across different
zones and spot traffic congestion spots.
Involves the gathering and processing of
huge amounts of location data from vehicle,
smartphones and other GPS devices. The
addition of external conditions such as
weather and road accidents make’s us more
precise in our analytics. Employing
visualization methods, we can also create
interactive maps, graphs and charts that
help in the interpretation of results. Lastly,
this study aims enhance traffic management
methodologies through intelligent urban
planning, enhancing routing planning, and
processing, and promoting better urban
development for smooth and efficient
traffic.
"TRAFFIC PATTERN ANALYSIS USING GPS DATA IN PYTHON", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 7, page no.a12-a16, July-2025, Available :http://www.ijrti.org/papers/IJRTI2507003.pdf
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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