The paper introduces 1-bit normalization as a preprocessing method for 3D real-time ambient noise tomography inversion. As a widespread and mature technique, 1-bit normalization converts signal amplitudes to binary values (-1 or +1) to reduce noise and compress data. However, existing studies do not examine data under natural noise conditions. Despite its non-linear nature, studies indicate that 1-bit normalization preserves the quality of velocity models derived from ambient noise tomography. In this paper, we investigated the effect of 1-bit normalization on Rex Hillside project ML 6438 using the Fleet's Exosphere technology by comparing the 3D velocity structure and its geological interpretation with and without the normalization. Results show minor discrepancies in velocity structures, suggesting that the technique's substantial data compression does not compromise geological insights. This efficiency makes 1-bit normalization advantageous for real-time applications in IoT, especially with LEO nano-satellites, potentially enhancing subsurface imaging resolution and mineral exploration outcomes.