Quantum Announces 2017 Outlook...Impact of Increased Distribution and Traffic Management Applications
Need for Storage System Construction to Support Video Data Analysis

Quantum announced its 2017 video surveillance market outlook on the 17th.

Quantum forecasts that the 2017 video surveillance market will continue to grow with not only security but also increases in distribution and traffic management applications, along with IoT trends. HIS projects that video surveillance-related data in 2017 will generate approximately 6,000PB of data capacity, and that by 2019, 3.3 trillion hours of surveillance video will be captured daily. Video data will see increased long-term retention due to growing demand for various advanced analytics including evidence adoption in law enforcement and analysis of retail customer purchase trends.

In Quantum's 2017 video surveillance market outlook, it identified the following: ▲storage systems must be constructed to support video data analysis ▲efficient data management methods must be in place to accommodate the increase in high-performance, high-definition video surveillance cameras ▲expanded application of biometric authentication applications to strengthen security ▲infrastructure must be constructed to enable integrated management of IoT and video surveillance data ▲video surveillance-as-a-service, and others.



Quantum stated that video-based data is expected to be widely used in enterprises to support business decision-making and therefore must be safely retained in storage for extended periods. Additionally, with the rapid increase in HD cameras, storage management solutions capable of effectively managing high-capacity data inflow are expected to gain attention.

Expanded Application of Biometric Authentication Applications to Strengthen Security

Furthermore, biometric authentication is expected to be used as a cybersecurity measure by public and private organizations such as medical and transportation organizations, and it announced plans to expand application of such technologies. With increased data generation from IoT devices, the challenge has arisen to construct infrastructure for storing, protecting, and analyzing IoT sensor files, requiring integrated management and analysis of data. As cameras become smarter and various types of sensors are integrated, self-analysis trends are becoming more pronounced, and the convergence of multiple analytical functions is becoming the foundation for "surveillance-as-a-service," it explained.