Project description
Training future researchers in water quality sensing technologies
Water quality deterioration is a major global concern. Scientists are seeking to mitigate poor water quality by developing tools that can monitor and take measurements of biogeochemical variables. In this context, the EU-funded AQUASENSE project will train 15 early stage researchers in the fields of aqua/agriculture and sensing technologies to develop sensors for environmental monitoring. Autonomous underwater robots and drones will be used to improve the data gathering, and AI methods will be used to improve the data analysis. Hands-on project training will be supplemented with formal training courses in relevant fields, such as sensors fabrication, system integration and robotics. The overall aim of the project is to bring a step change in the field of water quality monitoring while training future research leaders.
Objective
The deterioration of water quality, caused by climatic/seasonal changes, or industrial waste etc. is a major global concern. Over the last decade, water quality observing technology has risen to the challenge of scientists to identify and mitigate poor water quality by providing them with cost-effective tools that can take measurements of essential biogeochemical variables autonomously. Yet, despite these options becoming more readily available, there is a gap between the technology and the end-user (including the investigators and technicians that deploy these technologies) due to a collective lack of training, in-depth knowledge, and skilled workers who can meet new and emerging challenges. There is also a disconnect between data quality, data gathering by autonomous sensors and data analysis, which is a major obstacle, as the sensors are already being deployed (e.g. through buoys, boats etc.). AQUASENSE will address these challenges through 15 early stage researchers (ESRs), who will receive 540 person-month of unparalleled multidisciplinary training in the field of water quality monitoring. Each ESR will be mentored by carefully selected experts from academia and industry in 9 European countries (UK, Germany, Ireland, Serbia, Sweden, Italy, Poland, Austria, Estonia) and will have access to state-of-the-art equipment to develop autonomous sensors for improved data quality. The autonomous underwater robots and drones will be used to improve the data gathering and AI methods will be used to improve the data analysis. Hands-on project training will be supplemented with formal training courses in relevant fields such as new materials, sensors fabrication, wireless communication, system integration, and robotics, and a variety of complementary courses such as IPR, grant writing and exploiting the scientific results. Mobility within the network will ensure exposure to complementary academic and industrial research environments.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesdata science
- natural sciencesearth and related environmental scienceshydrology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsautonomous robotsdrones
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
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Programme(s)
Coordinator
G12 8QQ Glasgow
United Kingdom