Alert Level: Investigating and Preventing Food Contamination Problem in Bangladesh using AI

Authors

  • Tasnim Sultana Sintheia American International University-Bangladesh
  • Khushbu Alam Rahi American International University-Bangladesh
  • K. M. Tahsin Kabir American International University-Bangladesh
  • Md. Sayem Kabir American International University-Bangladesh
  • Kazi Tanvir Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, India
  • Mohamed Kaisarul Haq Shannon School of Business, Cape Breton University, Nova Scotia, Canada
  • Farzana Nazera Post-Doctoral Fellow, Jesselton University College.
  • Valliappan Raju Director of Research, Perdana University, Malaysia

Keywords:

Food Contamination, Students, Artificial Intelligence, Technology

Abstract

The main purpose of the report was to investigate and prevent food contamination problem in Bangladesh using AI. A survey was conducted on 70 students currently studying at American International University-Bangladesh. This survey was hosted on Google form by preparing a questionnaire and the link was sent through teams to the students. Single choice and multiple choices were used in the survey. The result illustrated that 36.1% of students ate restaurant or street food 2-3 times a week and 39.3% students got stomach ache occasionally after eating outside food. The least number of students consulted with doctor after having food poisoning which is 2.5% approximately. The researcher recommended implementing technology and AI based app “Foodies” for detecting and preventing contaminated food.

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Published

2024-11-01

How to Cite

Tasnim Sultana Sintheia, Khushbu Alam Rahi, K. M. Tahsin Kabir, Kabir, M. S., Kazi Tanvir, Mohamed Kaisarul Haq, Farzana Nazera, & Valliappan Raju. (2024). Alert Level: Investigating and Preventing Food Contamination Problem in Bangladesh using AI. Journal of Reproducible Research, 2(3), 54–63. Retrieved from https://journalrrsite.com/index.php/Myjrr/article/view/89

Issue

Vol. 2 No. 3 (2024): Diversified Researches

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