We address the feasibility of the pragmatic implementation of monitoring systems for real-time distributed fault diagnosis in complex processes. We delve into the integration of theoretical distributed estimation methods and practical distributed embedded systems. This study emphasizes the merger of distributed computing and signal processing to augment fault diagnosis in dynamic systems. We introduce a generic mathematical model for distributed fault diagnosis algorithms, laying the groundwork for a reference network computing architecture that details the essential components, organization, and operational characteristics necessary for distributed monitoring systems. Subsequently, we evaluate existing software and hardware solutions that facilitate the realization of these systems. The theoretical framework and system design are empirically validated through an experimental setup involving a liquid-level control system, demonstrating the efficacy and applicability of our approach.