## 4 Applications of WSN in Urban Areas  
### Power System Applications  
Power systems face numerous challenges in urban areas, such as excessive loads, malfunctions, and the risk of blackouts, leading to significant economic and human losses. The safe and reliable operation of power systems is crucial for maintaining stability and meeting the daily needs of urban populations. Power systems consist of generation, transmission, and distribution components, each requiring continuous monitoring and fault diagnostics to prevent disruptions and ensure uninterrupted power supply. WSNs offer a promising solution by providing real-time monitoring of power grid components, detecting faults, and enabling timely interventions to prevent outages. By deploying sensors across the power grid, WSNs can collect data on voltage levels, current flows, and equipment conditions, allowing operators to identify potential issues and take preventive measures proactively. Additionally, WSNs can facilitate predictive maintenance by analyzing data patterns to predict equipment failures before they occur, thus improving the reliability and resilience of power systems in urban areas. Precautions such as regular maintenance, redundancy in critical components, and cybersecurity measures can further enhance the effectiveness of WSN-based power system monitoring and ensure uninterrupted power supply for urban residents. [PERSON] et al. (2020) [12] introduced an intelligent power quality monitoring method to efficiently collect data on power quality events while minimizing coverage area and analysis time. By utilizing a power meter in a centralized network with a mesh network topology, the methodology aims to address issues such as voltage sags and harmonic resonance modes. The method allows for more targeted monitoring, reducing the resources required for analysis and enhancing the efficiency of power quality monitoring in electrical networks. The proposed method is faster, more economical, more accurate, and easier to operate for many real-time applications. [PERSON] et al. (2022) [13] introduced the harmonic resonance mode analysis approach. The designed approach focused on mitigating susceptibility to voltage sags and harmonic resonance modes in power systems by optimizing the placement of power quality monitors (PQMs) within a decentralized architecture and star network topology. By leveraging RMS voltage and RMS current measurements, the methodology aims to overcome budget limitations by strategically distributing a restricted number of monitors to check for severe conditions effectively. The designed approach ensures efficient monitoring of power quality events through optimizing resource allocation. [PERSON] et al. (2023) [14] discussed an optimal configuration method for power quality monitors (PQMs) with a focus on voltage sag location. By employing light and motion sensors in a decentralized network with a peer-to-peer topology, the methodology utilizes co-connectivity examination-based integer linear programming to achieve optimal placement of PQMs. Additionally, decision trees are utilized to remove PQM deployment in areas with higher costs, ensuring cost-effective and efficient monitoring of power quality events. [PERSON] et al. (2018) [15] presented a multi-objective optimization approach to distributing power quality monitors (PQMs) in the distribution system. By utilizing ammeters and cameras in a centralized network with a tree network topology, the methodology aims to reduce monitoring costs while enhancing load monitoring and reducing voltage sags. The Multi-objective Evolutionary Algorithm with Tables (MEAT) addresses the monitoring issues, leading to improved monitoring redundancy and reliability in power quality monitoring. [PERSON] et al. (2023) [16] proposed a Fault Position Method (FPM) and Harmonic Resonance Modal Analysis (HRMA) that focuses on efficiently allocating PQMs in distribution systems to address issues related to fault location and harmonic resonance modes.