LAUSR

Continuous monitoring of dynamic systems in the energy industry can lead to significant cost reductions by optimizing operations and reducing downtime through automatic integrity monitoring. In this paper, we focus on a challenging scenario, continuous subsurface monitoring through passive seismic tomography. Our proposed solution to address this challenge is enabled by marrying low-cost low-power sensing design, large-scale wireless (cellular) Internet of Things (IoT) networking, and advanced edge/cloud computing technologies. We demonstrate that the proposed data compression technique, application protocol design, and signal processing approach at edge sensors and cloud solution, enable us to handle data-demanding subsurface tomography problem using commodity cellular IoT technologies paving the way towards changing the traditional wisdom in our business. Compared to the state-of-the-art, the proposed solution is scalable, easily replicable, and considerably more power-efficient. The simulation results as well as a proof-of-concept (PoC) field test in collaboration with our partners (Vodafone and Nikhef) corroborate the feasibility of the proposed ideas.