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Big Data Analytics for Enhancing Urban Planning and Resource Management in Dhaka City

Students & Supervisors

Student Authors
Sadi Mohammad Meraj
Bachelor of Science in Computer Science & Engineering, FST
Supervisors
Md. Mortuza Ahmmed
Associate Professor, Faculty, FST

Abstract

The study investigates how big data analytics can underpin evidence-based urban planning and resource management in Dhaka City, factoring in temporal patterns across key urban metrics. Drawing from a longitudinal dataset of yearly measurements, this methodology leverages descriptive analytics, trend analysis, and comparative assessment to identify fluctuations, anomalies, and long-term trajectories of three indicators of urban activity and resource utilisation from 1995 forward. Overall, substantial year-to-year variability is evident across all three metrics, with pronounced peaks and troughs indicating irregular patterns in resource demand and performance of the urban system. The time series for Metric A demonstrates sharp fluctuations, including extreme highs in excess of 900 units during multiple years, indicating unstable pressures on associated urban infrastructure. For Metric B, volatility is the greatest, ranging from low double-digit values to near-800-unit spikes, indicating grossly inconsistent utilization or reporting practice for this dimension of city dynamics. In contrast, Metric C records relatively consistent high elevations, intimating steadily high patterns of resource consumption over time. These findings suggest that the urban systems of Dhaka manifest substantial instability-a situation that might not be conducive to long-term planning-and require increased continuity in data gathering through more integrated analytics frameworks. This paper discusses how big data methods may assist planners by enabling the timely detection of emerging issues, optimization of limited resource allocations, and design of adaptive policy responses, supported by quantitative evidence. The paper concludes that the integration of multi-year quantitative datasets into urban planning strategies for megacities such as Dhaka enhances the capability for informed decision-making, improved resilience, and sustainable urban development.

Keywords

Urban metrics; Trend analysis; Fluctuations; Inconsistent; Quantitative evidence

Publication Details

  • Type of Publication:
  • Conference Name: 2nd ICFS:ITGI-2026
  • Date of Conference: 15/01/2026 - 15/01/2026
  • Venue: Bangladesh University of Engineering & Technology
  • Organizer: Faculty of Science, Bangladesh University of Engineering & Technology
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