CANLEISHTitle: Non-invasive volatiles test for canine leishmaniasis diagnosis
Reference: H2020-MSCA-RISE-2020 101007653 Duration: 1/5/2021 – 30/4/2025 Summary: Canine leishmaniasis is among the most important vector-borne parasitic diseases of dogs. The study of this project focusses on investigating the feasibility of a non-invasive methodology for the diagnosis of canine leishmaniasis in dogs via the analysis of non-invasive volatile samples emitted by dogs’ breath and hair, employing analytical methods and a system composed of different chemical gas sensing devices. Website: https://h2020.canleish.spiruharet.ro/ |
SENSORFINTTitle: European Network for assuring food integrity using non-destructive spectral sensors
Reference: COST Program - CA19145 Duration: 30/9/2020-29/9/2024 Summary: This project aims at developing generic solutions to existing and emerging problems in non-invasive food process control building a "smart food control system" as well as developing a cadre of well-trained young researchers who will convert scientific results into a reality that matches industrial needs. Website: https://www.sensorfint.eu/ |
DIGITALIS
Title: Developing digital monitoring System for optimal conservation efforts
Reference: Swedish Institute – Seed funding for cooperation projects in the Baltic Sea region - 01682/2021
Duration: 1/10/2021 – 30/9/2022
Summary: The aim of this project is to define the need for new methods for data collection of pollutants in the Baltic Sea and to determine the principles for the development of a new digital sensor network, which can follow the change in pollutants in real time over time and identify their sources.
Reference: Swedish Institute – Seed funding for cooperation projects in the Baltic Sea region - 01682/2021
Duration: 1/10/2021 – 30/9/2022
Summary: The aim of this project is to define the need for new methods for data collection of pollutants in the Baltic Sea and to determine the principles for the development of a new digital sensor network, which can follow the change in pollutants in real time over time and identify their sources.
