<![CDATA[The robustness and resilience of enterprise networks are critical in ensuring consistent performance, even in the face of unexpected disruptions. This study addresses the significant challenges faced in maintaining network stability by introducing edge sensors using Raspberry Pi 4, Prometheus, and Grafana. The primary objective is to assess the impact of edge sensors on enhancing the robustness and resilience of campus wireless networks, with a particular focus on Universitas Islam Indonesia. The system effectively monitors critical metrics such as packet loss and ping in real-time, enabling early detection and alerts for declining network performance. The findings highlight that this approach significantly improves network stability, providing a cost-effective and scalable solution for continual network management. Furthermore, the study recommends the integration of machine learning algorithms to enhance anomaly detection accuracy.]]>
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