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Redefining video surveillance effectiveness with big data

Redefining video surveillance effectiveness with big data
The introduction of IoT and big data has enabled surveillance systems to perform logical processing and intelligent video analytics, enhancing the usability of data and reducing response latency.
The introduction of IoT and big data has enabled surveillance systems to perform logical processing and intelligent video analytics, enhancing the usability of data and reducing response latency. By deploying intelligent surveillance systems, not only has the large number of staff that was once required for monitoring been reduced, the automatic data processing and analysis have also transformed the system from passive monitoring to proactive reporting of any abnormal events. The improved timeliness and accuracy of data have created great value for different business sectors.

From unstructured data to insightful information  

According to research, one third of the video data generated worldwide will be stored in the cloud system and processed using edge computing by 2020. With surveillance cameras being widely deployed and generating more and more data every day, the current servers on the market will soon become slower and insufficient with the overload. The need for advanced technologies and solutions to transfer and process the tremendous amount of unstructured data or raw images produced into valuable information cannot be ignored. Fortunately, recent developments in artificial intelligence, deep learning and edge computing technologies have made it possible to turn large amounts of unorganized data into valuable information to help businesses improve operational efficiency.

Big data in video surveillance

Big data has been used in various industries, but it wasn't until 2017 that it's been increasingly adopted due to the exploding amount of data generated in the transportation and retail sectors. In general, the big data platform is built with a distributed and cluster architecture to enable surveillance system reaching load balancing in data processing. When it comes to data storage, there are a few points to keep mind, first is to determine what data needs to be stored, secondly is to select and store the right data from the original system during system reconstruction, and lastly but most importantly is to ensure data reliability.
In order to collect video data, the architecture of video processing platform divided into three layers: data layer, platform layer and application layer. Data layer, mainly consist of IT infrastructure data, data resources and video images, can, receive, store, and process a large amount of data from foot traffic, license plate, and facial information and more. Platform layer, also known as the big data platform, covers the broad spectrum of data storage, data processing, data transfer, and data management. At the same time it provides an interface for application layer to process data more efficiently. Application layer, on the other hand, enables all the users to store, search, and analyze data generated in different vertical sectors, such as retail, industrial, transportation, healthcare, home, smart city, fire safety and more.

Four must-see technology trends at Secutech 2018

Keeping pace with the current technology trends, Secutech 2018 will highlight four technologies: key components, AI, IVA, edge computing & big data analytics, ICT transmission and LPWAN, and cybersecurity, which are necessary for surveillance systems to collect, store, process, secure and transform the data into actionable insights that are beneficial for different vertical markets. Register today! 
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