## 6 Conclusions and Future Work  
This paper presented a comprehensive survey of WSN applications in urban environments. The survey highlights significant advancements and challenges across various domains, including disaster response, healthcare, gas monitoring, transportation, and solid waste management. These applications showcase the versatility of WSNs in enhancing  
Figure 21: Measurement analysis of throughput.  
Figure 22: Overall performance analysis of throughput.  
urban operations by contributing to proactive risk management, efficient response coordination, and sustainable urban development through integrating geo-spatial data, IoT devices, and advanced sensor technologies. The survey analyzed performance metrics such as energy consumption, network lifetime, end-to-end delay, efficiency, routing overhead, throughput, computation cost (Cost), computational overhead, reliability, loss rate, and execution time. These are critical in evaluating the effectiveness and feasibility of WSN applications in urban environments. Reducing end-to-end delay is crucial for real-time applications such as disaster response and healthcare monitoring, where timely data transmission can save lives. Efficiency and routing overhead are also key considerations; high efficiency with minimal routing overhead ensures that data are transmitted effectively without over-burdening the network infrastructure. The results of the proposed method obtain a maximum of 16%, 36%, 20%, and 42%, accuracy, network lifetime, efficiency, and throughput. Also, the proposed method is to provide less than 36%, 30%, 46%, 35%, and 32% energy consumption, computation cost, execution time, error rate, and computational overhead than the existing methods.  
The limitation of the work is the failure to combine IoT devices and sensor networks. Integrating IoT devices and sensor networks is crucial for proactive monitoring of critical urban systems, such as transportation, energy, and water management, enabling real-time detection and the resolution of issues. Also, the optimization method of the WSN application is not considered. In addition, the scalability is difficult to measure in the real world. Computation cost and computational overhead impact the processing capabilities of sensors, affecting their ability to analyze and transmit data without excessive delays or resource usage. Continued research and innovation in optimizing these performance aspects will enhance urban areas' sustainability, resilience, and overall efficiency, leading to smarter, more responsive cities. Advanced data analytics provide valuable insights for decision-making, helping city officials optimize urban planning, reduce environmental impact, and enhance the quality of life for residents.  
In future work, IoT devices and sensor networks will be combined. The optimization method of the WSN application will be focused on WSN. The embracing of these methodologies allows urban areas to become more resilient and responsive to the evolving needs of their inhabitants, fostering smarter and more livable cities. This survey's performance analysis identifies the most efficient WSN methodologies for urban applications by evaluating key metrics like scalability, energy consumption, network lifetime, and delay, providing a valuable framework for future research and practical deployments in urban settings.  
All authors contributed equally to the work. All authors have read and agreed to the published version of the manuscript.  
The work in this paper was supported, in part, by the Open Access Program from the American University of Sharjah. This paper represents the opinions of the author(s) and does not mean to represent the position or opinions of the American University of Sharjah.  
The authors declare no conflicts of interest.