Network Coverage Mapping and Route Analysis System Using ESP32 S3 and SIM7670g 4g LTE Telemetry

Author

Dr. Raghavendra R. Maggavi, Akshata Redekar, Rohit Patil, Sahil Patil, Vaishnavi Bongale

Abstract

 Mobile network connectivity is difficult to track continuously and an unexpected cellular dead zone or weak reception pocket can disrupt emergency fleets, logistics tracking and digital navigation. Commuters and transport drivers cannot realistically know the cellular signal quality of every road stretch in advance. This paper describes a low-cost embedded telemetry system that continuously captures mobile network signal strength and geographic coordinates along vehicular transit routes. An ESP32 S3 microcontroller queries a SIM7670G 4G LTE cellular module via AT commands to extract Reference Signal Received Power (RSRP), while an active GNSS patch antenna supplies precise latitude, longitude, and speed. The gathered telemetry is uploaded in real time over cellular data channels to a Supabase cloud database and visualized on an interactive Leaflet mapping dashboard. We also formulate a multi-route analysis algorithm that evaluates candidate travel paths and recommends corridors offering continuous cellular coverage rather than shortest physical distance alone. The prototype demonstrates autonomous field telemetry logging, cloud synchronization and route connectivity scoring; real-world drive tests conducted across Belagavi corridors confirm that shortest distance routes frequently pass through severe signal dropouts, validating the proposed connectivity-aware system.

Keywords

Network coverage mapping, ESP32 S3, SIM7670G, GNSS, 4G LTE, RSRP, multi-route analysis, Leaflet, Supabase, intelligent navigation.

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References

[1] I. Shayea, M. Ergen, M. H. Azmi, D. C. Babaoglu and R. Nordin, "Performance Analysis of Mobile Broadband Networks With 5G Trends and Beyond: Rural Areas Scope in Malaysia," IEEE Access, vol. 8, pp. 65295–65311, 2020.

[2] S. Farthofer, P. Brenner and C. Sommer, "An Open Mobile Communications Drive Test Data Set and Its Use for Machine Learning," IEEE Open Journal of the Communications Society, vol. 3, pp. 1957–1974, 2022.

[3] U. Saeed, J. Hamalainen, E. Mutafungwa, R. Wichman, D. Gonzalez G. and M. Garcia Lozano, "Route-based Radio Coverage Analysis of Cellular Network Deployments for V2N Communication," in Proc. 2019 Int. Conf. WiMob, 2019.

[4] A. Bousselham, O. Bouattane and M. Youssfi, "Data-Driven Prediction of Cellular Networks Coverage: An Interpretable Machine Learning Model," in Proc. 2018 IEEE GlobalSIP, 2018.

[5] Project Report, "Network Coverage Mapping and Route Analysis System," Department of Electronics and Communication Engineering, Jain College of Engineering and Research, Belagavi, 2026.

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