NIMay 19

A Meshtastic-based LoRa Mesh System for Smart Campus Applications: From Solar-Powered Sensing to Containerized Data Management

arXiv:2605.2037945.5Has Code
Predicted impact top 77% in NI · last 90 daysOriginality Synthesis-oriented
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It provides an autonomous, reproducible infrastructure for environmental monitoring and asset tracking in university campuses, reducing reliance on commercial LoRaWAN operators.

This work presents a LoRa mesh network using Meshtastic for smart campus applications, demonstrating robust connectivity across a 2.47 km link with mean RSSI of -110 dBm and SNR of +2.75 dB, and integrates containerized microservices for data management.

This work presents the design, implementation, and evaluation of a LoRa-based mesh network using the Meshtastic protocol for Smart Campus applications at Universidad Militar Nueva Granada (UMNG). The system integrates heterogeneous hardware nodes including a solar-powered ecological sensing node built around a Raspberry Pi Pico and a Semtech SX1262 transceiver, and mobile trackers based on the Seeed SenseCAP T1000-E managed through a containerized edge gateway running on a Raspberry Pi 4. A Docker Compose microservices stack handles data ingestion via Node-RED, time-series storage in InfluxDB, and real-time visualization through Grafana dashboards. The architecture's performance was evaluated under realistic propagation scenarios at the UMNG Cajicá campus, characterizing link quality using Received Signal Strength Indicator (RSSI) and Signal-to-Noise Ratio (SNR) metrics. Experimental results demonstrate robust mesh connectivity across key university facilities, including an extended-range link of approximately 2.47 km linking the campus gateway to a remote station at Mirador La Cumbre (n = 62 packets received, mean RSSI = -110 dBm, mean SNR = +2.75 dB). This architecture demonstrates that open-source mesh protocols combined with containerized microservices offer an autonomous, highly reproducible infrastructure for environmental monitoring and asset tracking, supporting the transition toward data-driven "Smart Campus" ecosystems without reliance on centralized commercial LoRaWAN operators.

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