Monitoring systems and the Internet of Things become increasingly important in horticulture. To monitor water requirements of plants, not only a measuring device but also an intelligent monitoring system to control, process, and store the data is necessary. Based on the PLANTSENS project, the composition of the individual modules within the server infrastructure and the associated communication methods are explained. By using Python libraries, individual algorithms were developed to determine the demand of water. The crop water stress index (CWSI) and normalized difference water index (NDWI) calculated from the infrared images are stored in a time-series database. Data visualization and alarming is implemented in the web-based software “Grafana”.