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Original Article

Smart Cities under Noise: A Novel Study on EMI-Induced Performance Degradation in Urban Wireless Systems

  • Paper ID 323
  • Volume 6, Issue 2
  • Pages 324-336
  • Published Online: March-April 2026
  • 30 Views
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Authors

  • Ahmed Fadhil Qutaif1

1 College of education humanities, wasit university, Iraq.

Article Information

Published Online
March-April 2026
Pages
324-336
Article Type
Original Article
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Abstract

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The rapid evolution of smart cities has led to the widespread deployment of wireless communication technologies, including Internet of Things (IoT) networks, 5G infrastructure, and sensor-based urban monitoring systems. However, the dense electromagnetic environment in urban areas introduces significant electromagnetic interference (EMI), which adversely affects the reliability and efficiency of wireless communication. This study investigates the impact of EMI on the performance of urban wireless systems and proposes a structured framework for analyzing interference-induced degradation. The research develops a comprehensive EMI model that incorporates both narrowband and broadband interference sources commonly found in metropolitan environments, such as industrial machinery, power transmission lines, and high-density wireless devices. Using simulation-based analysis, key performance indicators including Bit Error Rate (BER), throughput, latency, and packet delivery ratio are evaluated under varying interference conditions. The results demonstrate that increasing EMI levels lead to a substantial rise in error rates and latency, while significantly reducing overall network throughput and communication reliability. Furthermore, the study highlights critical thresholds beyond which wireless systems experience severe performance deterioration, particularly in high-density IoT deployments. Comparative analysis reveals that conventional communication protocols are not sufficiently robust to handle dynamic EMI conditions in smart city scenarios. To address these challenges, the paper discusses potential mitigation strategies, including adaptive filtering techniques, dynamic spectrum allocation, and intelligent interference-aware routing mechanisms. The findings of this work contribute to a deeper understanding of EMI effects in urban communication networks and provide practical insights for designing resilient wireless infrastructures. This research is expected to support future advancements in smart city development by enabling more reliable and interference-tolerant communication systems.

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