The goal of these LoRaWAN based greenhouse monitoring datasets, is to provide the global research community with a benchmark tool to evaluate different techniques for precision agriculture in large greenhouse environments. An identical collection methodology was used for both of the two datasets over the same tomato crop: during a period of five months, respectively. Together with temperature and humidity values, network information such as receiving time of the message and Received Signal Strength Indicator (RSSI) were stored in the greenhouse monitoring datasets: Greenhouse-1.csv Data from 27 sensors denoted as AF 16-42 with an average of 19687 LoRaWAN messages per sensor from April till August 2020, obtained in the greenhouse for tomato crop in Belgium. Greenhouse-2.csv Data from 19 sensors denoted as AF 49-67 with an average of 19009 LoRaWAN messages per sensor from July till November 2020, obtained in the other greenhouse for tomato crop in the Netherlands. Greenhouse-1-Transformed-Data.csv Mean temperature, humidity, and RSSI values along with plant height for the same period. Both the greenhouses, had no LoRaWAN connectivity, so individual gateway were installed for both locations. For Greenhouse-1 data, sensors were switched on in a room on 10th of April and brought to the greenhouse chamber on 17th April at 06:38 am for sensing. It would be crucial to accordingly use data set, considering the above time period. The collection methodology of datasets, and first results of a joint communication and sensing proof-of-concept are documented in the journal paper : https://www.mdpi.com/1424-8220/22/4/1326.

LoRaWAN based greenhouse monitoring datasets.