The objective of this research is to develop a methodology for diagnosing network problems and assessing network status in scenarios where wireless sensor network (WSN) systems experience issues and faults based on the understanding of the operating mechanisms of WSNs in civil infrastructure monitoring. The proposed methodology involves the utilization of a sniffer device to monitor and analyze the radio activities of WSNs. It is developed by investigating radio activities under different conditions and employing deterministic methods and data-mining algorithms to identify significant parameters associated with network problems and network status. The implementation of the methodology is tested on real WSN devices in a testbed, demonstrating its capability to diagnose network problems and assess network status on-site and in a non-intrusive manner. The study yields 4 main contributions: (1) The development of a novel approach for creating non-intrusive models to diagnose network problems and assess network status specifically for WSN applications in civil infrastructure monitoring. (2) The creation of a network problem diagnosis model through the examination of key parameters associated with network problem scenarios, reconstructed in a WSN emulator. (3) The formulation of a network status assessment model through the analysis of parameters related to network status using statistical analysis and data-mining methods. (4) The implementation and testing of these models in a testbed environment, along with a demonstration of the network optimization process utilizing these implemented models.