PyLoGreen: Design and implementation of a low-cost agricultural data acquisition and monitoring system using Raspberry Pi, LoRa, and nRF24L01 in the High-Andean Tundra.

Abstract

This article presents PyLoGreen, an open-source hardware platform that enables continuous monitoring of air temperature, relative humidity, soil moisture, soil pH, and internal and external light levels inside greenhouses located in the High-Andean tundra of Juliaca (3824 m a.s.l.). The system is designed as a cost-accessible and reproducible scientific platform for regions where commercial greenhouse monitoring solutions are either unavailable or economically inaccessible for small-scale farmers. A hybrid architecture, combining long-range LoRa links (up to 7.5 km validated in dedicated line-of-sight tests with 100% packet delivery, and 2.53 km operational deployment) between a Raspberry Pi 4B Main Base and a remote greenhouse with a local nRF24L01 sensor network based on Raspberry Pi Pico nodes, is implemented to ensure reliable operation under harsh climatic conditions and limited connectivity. A one-month deployment in a real greenhouse demonstrates stable data acquisition from all nodes and robust LoRa communication, validating PyLoGreen as a practical tool for generating high-resolution environmental datasets that can support agronomic and environmental research in high-altitude systems.