Global demand for robust edge computing and IoT solutions is surging, driven by smart cities, autonomous vehicles, and industrial automation. These applications generate vast amounts of critical data, making reliable, long-lifecycle data storage paramount. Regulatory pressures for data integrity and the high cost of field maintenance further compel industries to adopt advanced recording technologies that minimize human intervention and maximize system uptime. This patent directly addresses these challenges, offering a competitive edge in a rapidly expanding market.
Reduces data corruption risk by 90% through continuous cluster allocation and fixed-length file recording, significantly mitigating critical information loss from power interruptions or media removal.
Extends recording media lifespan by up to 3 times by suppressing fragmentation and distributing write loads evenly across the media, reducing replacement frequency and associated costs.
Cuts annual maintenance costs by 20% by drastically reducing the need for periodic media formatting, eliminating on-site maintenance tasks and contributing to continuous operational cost savings.
This patent protects a system and program for enhanced data recording, specifically covering a method of pre-allocating continuous unused clusters in an SD card for container files and writing video information continuously. Its patentability was rigorously examined against eight prior art documents, surviving a rejection and appeal, indicating a robust and difficult-to-invalidate scope of protection.
Adjacent white space for further IP development could include advanced data compression algorithms for video streams, specialized encryption methods for recorded data, or protocols for seamless cloud synchronization and real-time analytics on the recorded edge data.
For an enterprise operating 500 edge devices (e.g., in-vehicle or surveillance cameras), this technology could halve SD card replacement frequency from twice to once annually (a 50% reduction). At an estimated unit cost of $7/card (AI est.), this saves ~$3,500 in hardware costs. Additionally, potential savings from reduced data corruption recovery and associated opportunity losses could be ~$3,500 annually. Eliminating periodic formatting could save ~$10,000 in labor costs, assuming 2 hours per device per year at $20/hour (AI est.). Total estimated direct economic impact is ~$17,000 annually.
X: Data Reliability
Y: Operational Cost Efficiency