Intelligent Governance: Examining the Impact of AI Integration on Utility Services for Smarter Governmental Operation in UAE - A Case Study of Bee'ah AI City Vision in Sharjah

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
2025-04-05
DOI
https://doi.org/10.36348/sjet.2025.v10i04.003
Citations
1
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
2.48
Controls
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article

Intelligent Governance: Examining the Impact of AI Integration on Utility Services for Smarter Governmental Operation in UAE - A Case Study of Bee'ah AI City Vision in Sharjah

Serageldeen Sultan, L. Sultan
1 citations
Saudi Journal of Engineering and Technology
Organizational and Employee Performance
2.48
article

Intelligent Governance: Examining the Impact of AI Integration on Utility Services for Smarter Governmental Operation in UAE - A Case Study of Bee'ah AI City Vision in Sharjah

Serageldeen Sultan, L. Sultan
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 11%
Organizational and Employee Performance
2.48
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Intelligent Governance: Examining the Impact of AI Integration on Utility Services for Smarter Governmental Operation in UAE - A Case Study of Bee'ah AI City Vision in Sharjah — Serageldeen Sultan, L. Sultan · Saudi Journal of Engineering and Technology (2025) | TGRS Research Map | TGRS