The EU-SENSE System for Chemical Hazards Detection, Identification, and Monitoring
Source abstract
Abstract
Chemical reconnaissance, defined as hazards detection, identification, and monitoring, requires tools and solutions which provide reliable and precise data. In this field, the advances of artificial intelligence can be applied. This article aims to propose a novel approach for developing a chemical reconnaissance system that relies on machine learning, modelling algorithms, as well as the contaminant dispersion model to combine signals from different sensors and reduce false alarm rates. A case study of the European Union Horizon 2020 project–EU-SENSE is used and the main features of the system are analysed: heterogeneous sensor nodes components, chemical agents to be detected, and system architecture design. Through the proposed approach, chemical reconnaissance capabilities are improved, resulting in more effective crisis management. The idea for the system design can be used and developed in other areas, namely, in biological or radiological threat reconnaissance.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Chemical Sensor Technologies · Air Quality Monitoring and Forecasting · Fault Detection and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Political Science and International Studies, University of Warsaw, 00-927 Warsaw, Poland
Faculty of Command and Management, War Studies University, 00-910 Warsaw, Poland
ITTI, 61-612 Poznań, Poland
Technisch-Mathematische Studiengesellschaft mbH (tms), 53229 Bonn, Germany
Funding
European Union
References (64)
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