Jelena Gorbatšova

The ENACT (https://enact-eu.net/) strengthens crime prevention and counter-terrorism efforts by supporting cutting-edge technologies like the Drug Hunter Analyzer. Developed by TalTech and the Estonian Police and Border Guard Board, Drug Hunter enables fast and reliable on-site drug detection in oral fluid within minutes. ENACT funding aims to enhance the visibility of Drug Hunter by supporting pilot studies, validation, and dissemination efforts, ensuring its successful adoption in law enforcement and forensic applications.

Ukraine has a quarter of the world’s chernozems and 41.5 million hectares of agricultural land, covering 70 percent of the country. Agriculture pollutes about 60 percent of land resources and approximately 45-48 percent of reservoirs, representing 18-24 % of global GHG emissions. SmartAGRO's goal is to develop a precision fertilization solution that will help Ukraine achieve its climate policy goals. SmartAGRO is based on capillary electrophoresis technology, which enables the determination of various macro- and microelements in the soil. The goal is to develop a precise agriculture platform with recommendations for soil fertilization for agricultural crops growing in Ukraine, taking into account the chemical profile of the soil, the type and the crops grown, helping to reduce the use of fertilizers, increase/maintain yields and reduce GHG emissions.

Drug Hunter is a portable analyzer for the detection of narcotics in saliva. The project's goal was to integrate machine learning methods into an expert system for substance detection to reduce the competence required of the analyzer's user to interpret the results and thereby reduce errors in substance detection. Various machine learning methods based on supervised learning - artificial neural networks - were tested during the project. In order to prepare (annotate) the data necessary for training the neural network, a cloud service was created, where the technical parameters of all analyzes and the obtained electropherograms, on which the substances to be analyzed were marked, were stored. The best results in detecting electrophoretic patterns were obtained using a convolutional neural network (CNN). The analyzer was tested in cooperation with Estonian Police at roadside drug testing raids in Estonia.