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Journals / Journal of Naval Sciences and Engineering / 2025 / Volume: 21 Issue: 2

Detection of Potential Biological and Chemical Threat Agents by Al-Driven Electronic Nose

Mehmet Milli(Bolu Abant İzzet Baysal Üniversitesi Mühendislik Fakültesi Bilgisayar Mühendisliği Bölümü)0000-0002-0759-4433
Pages
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Publication Date
2025-12-15
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The detection of potential biological threat elements is of vital importance in terms of environmental monitoring, public health, and public safety.
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Key Findings & Data:The collected data was analysed with the Artificial Neural Network model, which is known to show strong performance in gas recognition tasks.
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Conclusion & Impact: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.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Biological Threat · Deep Learning · BME688

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.

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Cite This Article

Milli, M. (2025). Detection of Potential Biological and Chemical Threat Agents by Al-Driven Electronic Nose. Journal of Naval Sciences and Engineering, Volume: 21 Issue: 2. https://doi.org/10.56850/jnse.1693081

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