Current practice on submarine platforms is to manually monitor machine performance. Manual monitoring entails expensive allocation of resources, time, and effort and is limited to infrequent, labor intensive, error prone measurements. An autonomous wireless monitoring solution that uses strategically positioned sensors that periodically send their data to an access point for further analysis, is needed. By autonomously gathering periodic, reliable, and accurate data, not only is the impact of the monitoring tasks on personnel drastically reduced but digital twins of the monitored machines can be developed to allow for Condition Based Maintenance of submarine assets.  An increased awareness of system health has important implications for maintenance planning and on-time delivery of parts needed for repair.  Our Phase II effort builds on the complete demonstrated successes of Phase I allowing for an autonomous wireless network of multiple sensors of various disciplines that are self-powered through ambient energy harvesting, non-invasively measure vibration, temperature, current, and voltages of the monitored equipment and provide real-time, high speed, high volume, accurate raw data for downstream analysis and processing