Speaker
Description
Commercial microwave links (CML) deployed in regional Internet service provider (ISP) networks provide continuous telemetry that can be repurposed for opportunistic environmental sensing. This work presents the design and implementation of a real-time data processing microsystem that leverages operational microwave backhaul measurements for precipitation monitoring. The system targets heterogeneous point-to-point links operating across a wide frequency range (5–80 GHz) and integrates automated data acquisition, processing, and visualization within a unified architecture.
Telemetry data, including received signal level (RSL), transmitted signal level (TSL), and device parameters, are collected using SNMP and HTTP-based APIs and stored in a time-series database (InfluxDB). A processing pipeline based on the TelcoRain framework converts signal attenuation into rainfall intensity estimates using standardized rain-attenuation models. The architecture supports real-time processing, historical data import, and web-based visualization of network-wide measurements.
The presented implementation focuses on practical deployment aspects in small-scale ISP infrastructures, addressing challenges related to heterogeneous hardware, data normalization, and real-time processing. The work explores the feasibility of integrating regional ISP backhaul telemetry into opportunistic sensing workflows and provides a basis for further experimentation with distributed precipitation monitoring using existing regional network infrastructure.