Detection and Classification of Bacteria in Common Street Foods Using Electronic Nose and Support Vector Machine

被引:0
|
作者
Balbin, Jessie R. [1 ]
Sese, Julius T. [1 ]
Babaan, Crissa Vin R. [1 ]
Poblete, Dianne Mei M. [1 ]
Panganiban, Ramiel P. [1 ]
Poblete, Joeylito G. [1 ]
机构
[1] Mapua Univ, Manila, Philippines
来源
2017 7TH IEEE INTERNATIONAL CONFERENCE ON CONTROL SYSTEM, COMPUTING AND ENGINEERING (ICCSCE) | 2017年
关键词
Street food; Electronic Nose; Support Vector Machine; Enterococcus faecalis; Escherichia coli; Staphylococcus aureus;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Street food has a major impact on the culture and lifestyle of Filipinos, but because of the lack of knowledge in proper food preparation, the cleanliness and quality of street food is neglected. Bad bacteria that causes diarrheal diseases lives on it, and it is hard to detect whether the bacteria are present, without an instrument like an electronic nose, and image processing. This paper aims to design an electronic nose with gas sensors that will detect three common types of bacteria on street foods namely Enterococcus faecalis, Escherichia coli and Staphylococcus aureus; and to classify if the said bacteria are present in the pre-cooking stage and which bacteria are still present after cooking. Electronic nose system detects the bacteria in the sample street food during pre-cooking stage and Support Vector Machine detects the bacteria in the sample street food during post-cooking stage.
引用
收藏
页码:247 / 252
页数:6
相关论文
共 50 条
  • [31] Detection and Classification of Advanced Persistent Threats and Attacks Using the Support Vector Machine
    Chu, Wen-Lin
    Lin, Chih-Jer
    Chang, Ke-Neng
    APPLIED SCIENCES-BASEL, 2019, 9 (21):
  • [32] A Novel Approach for the Brain tumor detection and Classification using Support Vector Machine
    Shankaragowda, B. B.
    Siddappa, M.
    Suresha, M.
    PROCEEDINGS OF THE 2017 3RD INTERNATIONAL CONFERENCE ON APPLIED AND THEORETICAL COMPUTING AND COMMUNICATION TECHNOLOGY (ICATCCT), 2017, : 90 - 93
  • [33] Early Detection and Classification of Bearing Faults using Support Vector Machine Algorithm
    Senanayaka, Jagath Sri Lal
    Kandukuri, Surya Teja
    Van Khang, Huynh
    Robbersmyr, Kjell G.
    2017 IEEE WORKSHOP ON ELECTRICAL MACHINES DESIGN, CONTROL AND DIAGNOSIS (WEMDCD), 2017,
  • [34] Citrus Leaf Disease Detection and Classification Using Hierarchical Support Vector Machine
    Hanh Dang-Ngoc
    Cao, Trang N. M.
    Chau Dang-Nguyen
    2021 INTERNATIONAL SYMPOSIUM ON ELECTRICAL AND ELECTRONICS ENGINEERING (ISEE 2021), 2021, : 69 - 74
  • [35] Preliminary Melanoma Detection Mobile Application using Support Vector Machine Classification
    Sadiq, Muhammad Umer
    Sankalpa, Donthi
    Ahfid, Karam
    Sagahyroon, Assim
    Dhou, Salam
    2020 INTERNATIONAL CONFERENCE ON COMPUTING, ELECTRONICS & COMMUNICATIONS ENGINEERING (ICCECE, 2020, : 115 - 118
  • [36] Classification of Beverages Using Electronic Nose and Machine Vision Systems
    Mamat, Mazlina
    Samad, Salina Abdul
    2012 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2012,
  • [37] Classification of silent speech using support vector machine and relevance vector machine
    Matsumoto, Mariko
    Hori, Junichi
    APPLIED SOFT COMPUTING, 2014, 20 : 95 - 102
  • [38] Classification of Human Pathogen Bacteria for Early Screening Using Electronic Nose
    Zulkifli, Syahida Amani
    Mohamad, Che Wan Syarifah Robiah
    Abdullah, Abu Hassan
    2ND INTERNATIONAL CONFERENCE ON APPLIED SCIENCE AND TECHNOLOGY 2017 (ICAST'17), 2017, 1891
  • [39] Classification of data from electronic nose using relevance vector machines
    Wang, Xiaodong
    Ye, Meiying
    Duanmu, C. J.
    SENSORS AND ACTUATORS B-CHEMICAL, 2009, 140 (01): : 143 - 148
  • [40] Masquerade Detection Using Support Vector Machine
    YANG Min
    WuhanUniversityJournalofNaturalSciences, 2005, (01) : 103 - 106