Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM42826
Volume:
9 |
3 |
Mar 2025
Pages:
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.
With the growing demands of urbanization, traditional methods of road pavement cleaning often struggle to meet the efficiency, environmental, and cost-effectiveness requirements of modern cities. The concept of smart cleaning offers a promising solution by integrating advanced technologies like Internet of Things (IoT), artificial intelligence (AI), and autonomous systems to optimize street cleaning operations. Smart cleaning systems utilize IoT sensors placed on pavements and cleaning machines to collect real- time data on dirt levels, debris, and waste accumulation. This data is processed by AI algorithms to determine optimal cleaning schedules and routes, focusing on high-priority areas while reducing the need for unnecessary cleaning. These systems help to conserve resources, such as water and energy, by ensuring they are used efficiently. One of the key benefits of smart cleaning is environmental sustainability. Many systems are powered by electricity or solar energy, reducing reliance on fossil fuels. Additionally, smart cleaning machines often use waterless cleaning technologies or consume significantly less water compared to traditional methods. The use of biodegradable detergents further minimizes the environmental footprint. Beyond sustainability, smart cleaning systems also offer improved operational efficiency and cost savings. Autonomous machines, such as robotic street sweepers, require minimal human intervention, reducing labour costs and improving the precision and consistency of cleaning. Furthermore, predictive maintenance capabilities ensure the longevity and optimal performance of equipment. Despite the clear advantages, challenges such as high initial investment, technology adaptation, and concerns about job displacement remain.
KEYWORDS
Publication Date
3/22/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
2
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...