• Utham Kumar Anugula Sethupathy

The proliferation of smartphones and the rising demand for seamless connectivity have created a pressing need for efficient, scalable network diagnostic platforms. Traditional diagnostic methods such as drive testing, though accurate, are expensive and limited in scope. This paper presents a cloud-enabled approach to mobile network diagnostics, where lightweight smartphone applications collect real-time performance metrics—including FTP and HTTP throughput, ping latency, and RF signal parameters—and transmit them to a cloud back-end for aggregation and analysis. The cloud integration enables large-scale data processing, visualization, and crowdsourced intelligence, allowing operators to identify coverage gaps, diagnose service issues, and benchmark performance across networks. By combining portable diagnostic tools with elastic cloud infrastructure, the proposed platform delivers cost-effective, scalable, and user-centric insights into mobile network quality. The study highlights architectural design principles, implementation strategies, and practical use cases that demonstrate the potential of these platforms to enhance both operational efficiency and end-user transparency.

Mobile Network Diagnostics; Cloud Computing; Android Applications; Real-Time Analytics; Crowdsourced Data; Network Performance Monitoring; QoS Measurement; RF Signal Analysis

"Cloud-Enabled Mobile Network Diagnostic Platforms: Real-Time Data Collection and Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.2, Issue 9, page no.598-609, September-2015, Available :http://www.jetir.org/papers/JETIR1701D39.pdf

"Cloud-Enabled Mobile Network Diagnostic Platforms: Real-Time Data Collection and Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.2, Issue 9, page no. pp598-609, September-2015, Available at : http://www.jetir.org/papers/JETIR1701D39.pdf