Year: 2025
Type: article
Abstract: The detection of potential biological threat elements is of vital importance in terms of environmental monitoring, public health, and public safety. The possibility of future military or terrorist use of such biological agents poses a serious risk to global security. Therefore, early detection of the threat plays a critical role in taking effective measures against a possible biological attack and putting emergency action plans into effect on time. In this study, an electronic nose system that can safely and effectively identify complex gas mixtures was designed by developing an artificial intelligence-based model on the data collected using a sensitive gas sensor matrix. However, in research studies, the direct use of highly hazardous biological and chemical agents is not possible due to high-security risks, ethical concerns, and legal restrictions. Therefore, in this study, a simulation environment was established to represent complex biological and chemical gas elements. The collected data was analysed with the Artificial Neural Network model, which is known to show strong performance in gas recognition tasks. The findings indicate that this approach can be used to detect potential biological threats and that electronic nose technologies can be evaluated in the field of security with artificial intelligence-supported applications.
Author: Mehmet Milli
Institution: Bolu Abant İzzet Baysal University
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4414972934