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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66354
Volume:
10 |
7 |
Jul 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of studies in Computer Science (M.Sc.)
Davangere University
Department of studies in Computer Science (M.Sc.)
Davangere University
Department of studies in Computer Science (M.Sc.)
Davangere University
Bad body odor affects personal hygiene, confidence, and social interactions. This project presents a low-cost, automated Bad Body Odor Detection and Spraying System using an ESP32 and MQ135 gas sensor. The MQ135 detects gases and volatile compounds associated with body odor. When the gas level exceeds a preset threshold, the ESP32 activates a relay to switch on an electric room freshener, which automatically sprays fragrance to reduce unpleasant odors. The system provides a real-time, hygienic, and efficient solution for odor management in homes, offices, hospitals, and public places.
KEYWORDS
The proposed Bad Body Odor Detection and Spraying System provides a practical and cost-effective solution for identifying unpleasant breath and automatically neutralizing it through fragrance spraying. By combining ESP32, MQ135 gas sensing technology, relay control, and an AC-powered room freshener, the system achieves reliable odor monitoring and automatic response. The project demonstrates the effective use of embedded systems for health and hygiene applications and provides a strong foundation for future IoT-enabled smart odor management systems.
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Publication Date
7/27/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
Funding Agency: FUNDED BY KARNATAKA STATE COUNCIL FOR SCIENCE AND TECHNOLOGY INDIAN INSTITUTE OF SCIENCE CAMPUS , BENGALURU
Grant / Project ID: 49S_MSC_0004
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