In 2015, the Obama Administration released a new strategy officially naming Smart Cities as one of nine areas of strategic opportunity for American innovation. {1} In accordance with the strategy, the U.S. Department of Transportation announced the Smart City Challenge, seeking to select a mid-size American city to help realize the department’s vision “to identify where advanced technologies are integrated into the aspects of a city and play a critical role in helping cities and their citizens address challenges in safety, mobility, sustainability, economic vitality, and address climate change.” {2}
The ongoing evolution of the Internet of Things (IoT) is helping to make this happen. Sensor technologies are becoming more sophisticated, and the number of connected devices and use cases continues to increase every year, generating massive volumes of data. The analyst firm Gartner estimates 6.4 billion connected “things” will be in use worldwide in 2016 {3}. Approximately 1.6 billion of those will be used by smart cities. {4}
Besides the growing impact of the IoT, advancements in camera technology are making it possible to capture more detailed images over a wider viewing area than ever before, resulting in increased adoption of high-resolution digital units. In fact, HD camera shipments were expected to surpass analog camera shipments globally for the first time in 2015. {5} Today, HD 1080p cameras are commonplace, and given advancements in network infrastructure, it is not uncommon to see tens of thousands of cameras deployed in large metropolitan areas.
Better camera technology and the IoT are creating new opportunities for innovation. Forward-thinking cities are seeking to cut down on unnecessary congestion and to improve public safety and services through sensor technologies, video cameras, and data analytics that work in unison. For example, automatic license plate recognition (ALPR) systems are being used to enforce traffic and parking laws and to locate wanted vehicles. Traffic signal information is being integrated with road sensors to capture vehicle counts and to reduce congestion. In fact, a pilot project in Pittsburgh was able to reduce the average commute time by 25 percent by using signal information to coordinate adjacent traffic signals. {6}
Storage Considerations
Storage infrastructure can have a significant impact on IoT initiatives. Given the growth of data-generating devices and proliferation of sensors, some estimates predict that machines that communicate with each other will account for 40 percent of the world’s data by the year 2020. {7} By that same year, video surveillance systems alone are estimated to produce 859 petabytes of data worldwide on a daily basis. {8} While the success of IoT initiatives depends on many factors, storage infrastructure and the unrestricted movement of data are certainly two of them. When evaluating storage platforms, here are three factors to consider that will help avoid storage-related problems down the road:
Performance
The most obvious factor to consider is performance. If the storage platform is incapable of ingesting large volumes of data at high speeds from a variety of input devices, storage I/O bottlenecks can occur. For example, in the case of video surveillance, higher resolution, multi-sensor cameras generate larger file sizes at faster frame rates than previous generation cameras. As smart city initiatives drive camera counts up, the storage infrastructure must be able to simultaneously process the increased number of video streams in order to ingest the data without degrading performance.
Data Retention
While some analytics applications perform real-time analysis and enable automated actions to occur based on alerts and algorithms, predictive analytics depends on aggregating data from disparate sources and analyzing it over time to identify trends and patterns. For this to occur, data not only must be kept for longer periods of time, but also it must be easily accessible to allow aggregation and analysis. In addition, law enforcement agencies are increasingly dependent on video data for crime prevention and prosecution, requiring data to be retained longer to satisfy legal requirements and to protect against litigation. To avoid problems, the storage architecture must accommodate long-term, low-cost data archiving and provide effective data management so data sets are stored affordably yet available for analysis when needed.
Scalability
As technology advances and new use cases are envisioned, the IoT will continue to grow and so will the demand for storage capacity. Investing in a storage platform with limited scalability can be expensive, creating islands of storage dedicated to single uses and making data integration more difficult. To be prepared, the storage architecture must be flexible and scale out as needed to accommodate growth as more sensors are added, camera counts go up, retention times increase, image formats change, and file sizes grow larger.
Multi-Tiered Storage for Maximum Benefit
Leveraging sensor technologies, video cameras, and data analytics working in unison to reduce congestion and improve public safety and services places high demand on storage infrastructures. To deliver the best results, the storage infrastructure must be flexible, high performing and affordable, while ensuring files are easily accessible.
Implementing a multi-tiered storage architecture is the best approach. With a tiered architecture, multiple levels of storage exist to address the need for high performance as well as low-cost archiving, and the data is managed based on user-defined policies. When implemented effectively, a tiered structure is the most cost-effective way to manage and retain large data sets to be used for advanced analytics and IoT applications.
Wayne Arvidson is Quantum’s Vice President of Video Surveillance and Security Solutions. Wayne has 25 years senior management experience in companies ranging from start-ups to Fortune 500 firms and drives Quantum’s strategy in the surveillance and security market.
Sources:
{1}{6} “FACT SHEET: The White House Releases New Strategy for American Innovation, Announces Areas of Opportunity from Self-Driving Cars to Smart Cities,” The White House Office of the Press Secretary, October 21, 2015
{2} “Questions and Answers for the Beyond Traffic Smart City Challenge,” U.S. Department of Transportation
{3} “Gartner Says 6.4 Billion Connected “Things” Will Be in Use in 2016, Up 30 Percent From 2015,” Gartner, November 10, 2015
{4} “Gartner Says Smart Cities Will Use 1.6 Billion Connected Things in 2016,” Gartner, December 7, 2015
{5} “Enterprise and IP Storage used for Video Surveillance,” IHS, November 2015
{7} “Trillions of Sensors Feed Big Data,” Signal Online, February 1, 2014
{8} “Top Video Surveillance Trends for 2015,” IHS, December 2014
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