Skip to main navigation menu Skip to main content Skip to site footer
Español (España) | English
Editorial
Revistas / Journals
Salud, Ciencia y Tecnología Metaverse Basic and Applied Research Data & Metadata Interdisciplinary Rehabilitation Salud, Ciencia y Tecnología - Serie de Conferencias Community and Interculturality in Dialogue Seminars in Medical Writing and Education Health Leadership and Quality of Life Gamification and Augmented Reality Southern perspective / Perspectiva austral
Home
Issue
Current Issue Previous Issues Special Issue
About
About the Journal Editorial Team Privacy Statement Digital preservation policy Contact
Submissions
Author Guidelines Peer Review Process Ethical aspects Open Access Policy and Copyright Anti-plagiarism policy Crossmark policy page
Indexing
×
Español (España) | English
Editorial

Salud, Ciencia y Tecnología Metaverse Basic and Applied Research Data & Metadata Interdisciplinary Rehabilitation Salud, Ciencia y Tecnología - Serie de Conferencias Community and Interculturality in Dialogue Seminars in Medical Writing and Education Health Leadership and Quality of Life Gamification and Augmented Reality Southern perspective / Perspectiva austral
Home

Current Issue Previous Issues Special Issue

About the Journal Editorial Team Privacy Statement Digital preservation policy Contact

Author Guidelines Peer Review Process Ethical aspects Open Access Policy and Copyright Anti-plagiarism policy Crossmark policy page
Indexing
Original
Published: 2023-12-30
DOI: https://doi.org/10.56294/dm2023161

Machine Learning Model for Prediction of the Chemicals Harmfulness on Staff and Guests in the Hospitality Industry: A Pilot Study

By
Mr. Rohit ,
Mr. Rohit

School of Hotel Management, Airline and Tourism, CT University, Ludhiana, Punjab, India

Search this author on:

PubMed | Google Scholar
Kapil Sethi ,
Kapil Sethi

Computer Science and Engineering, Bahra university, Shimla hills, Waknaghat, solan Himachal Pradesh, India

Search this author on:

PubMed | Google Scholar
Mudassir Khan ,
Mudassir Khan

Department of Computer Science, College of Science & Arts, Tanumah, King Khalid University, Abha, India

Search this author on:

PubMed | Google Scholar
Ashish Raina ,
Ashish Raina

School of Hotel management, Airline and Tourism, CT University, Ludhiana, Punjab, India

Search this author on:

PubMed | Google Scholar

Abstract

This article examines the trend around the adoption of machine learning in the hotel business in light of the significance of new technologies. According to previous research, the hospitality industry uses a variety of chemicals for cleaning. Cleaning supplies are the housekeeping department's primary tool in their daily routine to keep rooms and common areas clean and tidy. Guest and staff don't know the harmfulness of these chemicals. Providing hospitality that meets the needs of guests requires not only a positive attitude, but also high-quality and excellent services that keep guests warm, relaxed, and comfortable. But in some incidents, we find that the guest and staff health is affected by the chemicals. Also, no one worked on predicting the chemical's effects on staff and guest health in the hospitality sector with the use of Machine Learning models. For this purpose, data is collected from different hotels of Delhi NCR in India. There were two distinct fields utilized for assessment and instruction. For the investigation, machine learning methods were employed. The research project employed five machine learning methods. The newly developed MHC-CNN algorithm achieved the highest accuracy (93.75) in comparison to other cutting-edge machine learning techniques. The created technique can be expanded upon and applied in many hotels all around the world.

Keywords:

Algorithm,
Chemicals,
Employee,
Harmfulness Hotel,
Learning,
Machine,
Technologies,

How to Cite

1.
Mr. Rohit, Sethi K, Khan M, Raina A. Machine Learning Model for Prediction of the Chemicals Harmfulness on Staff and Guests in the Hospitality Industry: A Pilot Study. Data and Metadata [Internet]. 2023 Dec. 30 [cited 2024 Jul. 3];2:161. Available from: https://dm.saludcyt.ar/index.php/dm/article/view/161

Copyright Notice

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

Article metrics

Google scholar: See link

Metrics

Metrics Loading ...

Vol. 2 (2023)
See full issue

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.