IMPACT OF AUTONOMOUS VACUUM CLEANING TECHNOLOGIES ON SUSTAINABILITY AND COST-EFFECTIVENESS IN INDUSTRIAL AND COMMERCIAL FACILITIES

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Anirudh Bhattarai
Eman Ahmed Ibrahim Abdelhalim

Abstract

The advent of autonomous vacuum cleaning technologies has revolutionized maintenance practices in industrial and commercial facilities. This paper explores the impact of these technologies on sustainability and cost-effectiveness, highlighting significant improvements in energy efficiency, waste reduction, and operational costs. Autonomous vacuum cleaners, equipped with advanced sensors and artificial intelligence, offer a unique opportunity to enhance cleaning processes, reduce human error, and optimize resource allocation. By conducting a thorough analysis of their deployment in various settings, this study demonstrates how these innovative solutions contribute to environmental sustainability and financial savings. The findings suggest that autonomous vacuum technologies not only streamline maintenance tasks but also align with global efforts to promote eco-friendly practices and economic efficiency in the industrial and commercial sectors.

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How to Cite
IMPACT OF AUTONOMOUS VACUUM CLEANING TECHNOLOGIES ON SUSTAINABILITY AND COST-EFFECTIVENESS IN INDUSTRIAL AND COMMERCIAL FACILITIES. (2023). International Journal of Machine Intelligence for Smart Applications, 13(11), 1-7. https://dljournals.com/index.php/IJMISA/article/view/1
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Author Biographies

Anirudh Bhattarai, Department of Journalism, Madan Bhandari Memorial College, Tribhuvan University, Kathmandu, Nepal

Anirudh Bhattarai, Department of Journalism, Madan Bhandari Memorial College, Tribhuvan

University, Kathmandu, Nepal

Eman Ahmed Ibrahim Abdelhalim, Department of Nursing, Kafr El-Sheikh University, Kafr ElSheikh, Egypt

Eman Ahmed Ibrahim Abdelhalim, Department of Nursing, Kafr El-Sheikh University, Kafr ElSheikh, Egypt

How to Cite

IMPACT OF AUTONOMOUS VACUUM CLEANING TECHNOLOGIES ON SUSTAINABILITY AND COST-EFFECTIVENESS IN INDUSTRIAL AND COMMERCIAL FACILITIES. (2023). International Journal of Machine Intelligence for Smart Applications, 13(11), 1-7. https://dljournals.com/index.php/IJMISA/article/view/1

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