AI Video Encoding Cuts Storage Needs by up to Half
A new survey reveals that 81% of security professionals face significant storage pressure, driving adoption of AI-driven compression tools.
Key points
- 81.4% of survey respondents rate video storage as a major or moderate business challenge.
- Guanlan Encoding reduces storage needs by 30-50% by compressing static areas more than moving subjects.
- Over half of security professionals are familiar with or already using this AI-based encoding technology.
Security firms are increasingly turning to artificial intelligence to solve a mounting problem: the cost and capacity of storing video footage. A recent survey conducted by asmag.com and Hikvision, distributed via PR Newswire UK, highlights a sharp rise in demand for AI-based video encoding. The technology aims to drastically reduce the amount of data required to store high-quality surveillance footage without losing critical details.
The core issue is that traditional video compression treats every part of a frame equally, wasting space on static backgrounds. The new approach, known as Guanlan Encoding, uses AI to distinguish between important moving subjects and unchanging scenery. By applying different levels of compression to these areas simultaneously, the system promises to lower storage requirements by 30% to 50% on average.
Storage costs remain a top priority
The survey results confirm that storage pressure is a dominant concern in the industry. A combined 81.4% of respondents identified video storage as either a major or moderate challenge for their businesses. Furthermore, 43.2% of participants reported that this burden has increased moderately over the past year. This growing strain on infrastructure is a primary driver for adopting more efficient encoding standards.
Smart compression targets key details
Guanlan Encoding operates on the H.265 standard but adds an intelligent layer of analysis. It identifies information-rich areas, such as people or vehicles, and allocates higher quality to these sections. Conversely, it compresses static backgrounds more aggressively. This trade-off allows for significant data reduction while preserving the specific details needed for investigations and monitoring, ensuring that the most relevant parts of the footage remain clear.
Industry adoption is already underway
Despite its recent introduction, the technology has gained considerable traction. The survey found that 43.3% of respondents are familiar with Guanlan Encoding, even if they have not yet implemented it. Additionally, 8.3% reported that they are already using the system in their projects. This early adoption suggests a strong market appetite for solutions that alleviate storage burdens through intelligent data management.
