Sustainable Manufacturing and Energy-Efficient Production Systems

The research examines the application of Artificial Intelligence (AI) in waste management systems, using Bee'ah AI City Vision in Sharjah, UAE, as a case study. Research checks the application of advanced AI models, including long short-term memory (LSTM) network and transformer-based models, in adaptation to waste collection efficiency and sustainable urban rule. Conclusions display a 30% lower environmental footprint due to a 25% decrease in operating costs, waste volume prediction, and LSTM network in passage optimization. The transformer model also enabled a 20% increase in public satisfaction by increasing the accountability of services through emotion analysis. Research reflects AI's ability to increase operational efficiency, environmental stability, and governance in the public sector, as well as the main challenges, including AI decision-making data secrecy, algorithm bias, and transparency.

Authors

Publication Details

Journal
Saudi Journal of Engineering and Technology
Published
2025-04-19
DOI
https://doi.org/10.36348/sjet.2025.v10i04.008
Citations
1
Primary Topic
Energy Efficiency and Management
Type
article
Field-Weighted Citation Impact
0.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sustainable Manufacturing and Energy-Efficient Production Systems

Sunanda Sharan, Md Ashraful Azad, MD Toukir Yeasir Taimun, Md Mofakhkharul Islam Joarder
1 citations
Saudi Journal of Engineering and Technology
Energy Efficiency and Management
0.36
article

Sustainable Manufacturing and Energy-Efficient Production Systems

Sunanda Sharan, Md Ashraful Azad, MD Toukir Yeasir Taimun, Md Mofakhkharul Islam Joarder
article en
1 citations

Abstract

The research examines the application of Artificial Intelligence (AI) in waste management systems, using Bee'ah AI City Vision in Sharjah, UAE, as a case study. Research checks the application of advanced AI models, including long short-term memory (LSTM) network and transformer-based models, in adaptation to waste collection efficiency and sustainable urban rule. Conclusions display a 30% lower environmental footprint due to a 25% decrease in operating costs, waste volume prediction, and LSTM network in passage optimization. The transformer model also enabled a 20% increase in public satisfaction by increasing the accountability of services through emotion analysis. Research reflects AI's ability to increase operational efficiency, environmental stability, and governance in the public sector, as well as the main challenges, including AI decision-making data secrecy, algorithm bias, and transparency.

Saudi Journal of Engineering and TechnologyVol. 10(04)
Openalex Percentile: Top 44%
Energy Efficiency and Management
0.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.