The traditional black-box models have done well so far, but the intricate nature of modern vehicular traffic and the multi-faceted and sophisticated details of accidents requires more complex forensics solutions. To that end, we present the system “Vehicle Crash Forensics Node”. It is an embedded system realized in ESP32 that enables real-time logging of a crash’s critical parameters, and the location metrics, with addition of DHT22 sensor for context regarding environmental conditions. An integer-based algorithm is employed to compute a crash severity index based on impact intensity, while a premorbid buffer records 10 seconds of motion data to provide insight into behavior. All data, devoid of alteration, is securely stored with SHA-256 hashing in a circular buffer that is tamper-proof. With ESP-MESH, the system enables decentralized consensus through crash log voting by majority among neighboring nodes. With dual-core computing Wi-Fi allows for logs to be recovered ‘Over the Air’ boosted system usability and efficiency. This prototype, with ultra-low-power monitoring for small fleets enabled via the ULP coprocessor, and without needing an internet connection, unlocks scalable forensic solutions alongside real-time reporting and logging diagnostics.