Enhancing Real-Time User IP Tracking and Country Identification with APIs

DOI

10.2991/978-94-6463-471-6_18How to use a DOI?

Keywords

Geo Tracking; Cloud; Historical Data Analysis

Abstract

In the dynamic landscape of modern business, efficiently delivering data across diverse regions with varying demands presents a formidable chal-lenge. Current methodologies, leveraging APIs and machine learning algorithms for real-time user country identification, struggle to adequately optimize resource allocation and data delivery efficiency and calculate it. While IP-based geolocation methods and advanced programming language modules endeavor to track users’ IP addresses and identify their countries in real-time, they frequently fail to accurately predict future demand trends and integration with application. Despite efforts to analyze historical data request patterns, existing approaches lack the resilience required to scale resources effectively in specific regions, leading to suboptimal resource utilization and heightened costs for dynamic enterprises such as Over-the-Top (OTT) platforms and payment sites and cloud clients. Prevalent techniques face hurdles in data collection, cleaning, and feature engineering, resulting in inaccuracies and inconsistencies in forecasting future demand trends. As cloud providers track data but won’t share to clients in detail which affects clients to build large scale applications commonly employed machine learning algorithms have demonstrate limitations in accurately predicting demand patterns across diverse industries, including e-commerce, healthcare, and finance. The shortcomings of existing technologies in optimizing data delivery efficiency through real-time user IP tracking and country identification highlight the urgent need for an innovative system to effectively address modern data delivery challenges. Therefore, there is a pressing demand for novel approaches that can overcome these limitations and provide more robust solutions for optimizing data delivery and service efficiency in today's dynamic business environment. Such advancements have the potential to significantly enhance resource utilization, reduce costs, and improve the overall user experience, thereby driving innovation and competitiveness across various industries.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - G. V. S. Abhishek Varma
AU  - P. Srinivasa Rao
AU  - B. Aruna Kumari
AU  - G. V. N. Akshay Varma
PY  - 2024
DA  - 2024/07/30
TI  - Enhancing Real-Time User IP Tracking and Country Identification with APIs
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 180
EP  - 189
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_18
DO  - 10.2991/978-94-6463-471-6_18
ID  - Varma2024
ER  -