Frequent adjustment of operating strategies in a wastewater treatment plant as a situational response to water quality in the water body for effluent disposal has been facing a grand opportunity. This opportunity is emanated from transitioning the sporadic water quality monitoring in the water body for effluent disposal to the satellite-based situation-awareness, self-adaptive and fast response system. To achieve this goal, the cyber-physical system (CPS) is developed in this study to respond to the needs of smart wastewater infrastructure management. This prototype CPS is able to gather the massive volumes of water quality information via advanced remote sensing technologies to timely detect water pollution, exchange information through cyber interfaces, provide early-warning awareness with the aid of different feature extraction models, and support actionable intelligence for tuning the effluent disposal and recycling strategies for wastewater treatment. Integrated feature extraction techniques using extreme learning machine algorithms within the CPS architecture is emphasized in this study for smart wastewater infrastructure management through the interactions between the treatment facilities and satellites.