Prototype Based on a LoRaWAN Network for Storing Multivariable Data, Oriented to Agriculture with Limited Resources

Abstract

Due to the advancement in information digitization in the agricultural area that has resulted in processes which are more intelligent and independent of precision agriculture, having as objective the verification, quantification, calculation, processing, and storage of variables immersed in the agricultural area, the present work shows a LoRa sensors network system, with visualization in a cloud environment through The Things Network and data analysis in an IoT platform called ThingSpeak. The objective of the use of sensors in precision agriculture (PA) is to measure the different environmental parameters (e.g., temperature, humidity, soil pH value), which are sent through a LoRaWAN gateway that receives the variables sensed by the final nodes and in turn incorporates a specialized node based on artificial vision to obtain the vegetation index. In addition, a comparison with a commercial datalogger is carried out, achieving an average error of 3.67% in the measured variables and a cost 17 times smaller in the design of the proposed system.