The Internet of Things (IoT) has gained significance in agriculture, using remote sensing and machine learning to help farmers make high-precision management decisions. This technology can be applied in viticulture, making it possible to monitor disease occurrence and prevent them automatically. The study aims to achieve an intelligent grapevine disease detection method, using an IoT sensor network that collects environmental and plant-related data. The focus of this study is the identification of the main parameters which provide early information regarding the grapevine’s health. An overview of the sensor network, architecture, and components is provided in this paper. The IoT sensors system is deployed in the experimental plots located within the plantations of the Research Station for Viticulture and Enology (SDV) in Murfatlar, Romania. Classical methods for disease identification are applied in the field as well, in order to compare them with the sensor data, thus improving the algorithm for grapevine disease identification. The data from the sensors are analyzed using Machine Learning (ML) algorithms and correlated with the results obtained using classical methods in order to identify and predict grapevine diseases. The results of the disease occurrence are presented along with the corresponding environmental parameters. The error of the classification system, which uses a feedforward neural network, is 0.05. This study will be continued with the results obtained from the IoT sensors tested in vineyards located in other regions.

A case study was performed, concerning the behavior and degradation of a polymeric biocomposite material – “liquid wood”. This material is biodegradable and it is obtained from renewable resources. Three presentation forms – Arbofill Fichte, Arboform F45 and Arboblend V2, were subjected to the action of external factors present in a marine environment. The results pertaining to the change in the physico – chemical properties of “liquid wood” when subjected to the action of seawater and seawater microorganisms, with significant – but nevertheless positive – consequences upon the environment. The material exhibits good performance after the surface and mass stabilization – due to water, C, Na, Cl and O absorption. As such – due to the emergence of a protective organic biofilm – growth of microorganisms significantly decreases and electric conductivity increases. This case study may be viewed as a starting point for subsequent studies of “liquid wood”.