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AI-Based Optimization of Smart City Wireless Sensor Networks: Applications for Traffic, Environmental and Energy Management in Bangladesh

Students & Supervisors

Student Authors
Nazmus Sakib Sami
Bachelor of Science in Computer Science & Engineering, FST
Jannatul Ferdous
Bachelor of Science in Computer Science & Engineering, FST
Kazi Warisa Tabassum
Bachelor of Science in Computer Science & Engineering, FST
Supervisors
Md. Mortuza Ahmmed
Associate Professor, Faculty, FST

Abstract

To create AI-driven optimization strategies for smart city wireless sensor networks, we aim to improve traffic flow, monitor the environment, and manage energy in Bangladesh effectively. Materials and Methods: This study employs a mixed-method approach with secondary data. The data includes government reports, smart city documents, IoT records, and academic literature. Researchers analyzed trends in wireless sensor networks and AI optimization using Excel and Python. They applied descriptive statistics and correlation modeling. The findings show how AI improves traffic, environmental, and energy management. This offers guidance for policymakers, urban planners, and ICT developers in creating sustainable smart city initiatives in Bangladesh. The correlation heatmap shows the relationships between various urban infrastructure technologies, such as smart traffic systems, IoT sensors, renewable energy grids, and AI-based management tools, from 2000 to 2023. Each cell displays the correlation coefficient between two technologies. Positive correlations, which are closer to +1, mean that when one technology is adopted, the other is also likely to be adopted. Negative correlations, closer to -1, suggest the opposite trend. Strong correlations are represented by darker shades, which help identify clusters of technologies that are often adopted together. This reveals patterns in smart city development and informs policymakers about the deployment of integrated technologies. This study shows that using AI to optimize smart city wireless sensor networks can greatly improve traffic management, environmental monitoring, and energy efficiency in Bangladesh. These intelligent systems allow for real-time decision-making, cut down on resource waste, and aid sustainable urban development. The findings emphasize how combining AI with sensor networks can tackle increasing urban challenges. This approach leads to smarter, more resilient cities that enhance quality of life and increase operational efficiency.

Keywords

AI optimization smart city wireless sensor networks traffic management environmental monitoring energy efficiency.

Publication Details

  • Type of Publication:
  • Conference Name: 6th International Conference on Physics for Sustainable Development and Technology (ICPSDT)-2025
  • Date of Conference: 29/10/2025 - 29/10/2025
  • Venue: Chittagong University of Engineering and Technology (CUET), Chattogram-4349, Bangladesh
  • Organizer: Department of Physics, Chittagong University of Engineering & Technology (CUET)
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