With the Advent of the internet into every sphere of our lives, more commonly known as the Internet of Things (IoT), video analytics is gaining a strong ground too.
The security measures applied to almost every corporate and non-corporate setting involve the use of video analytics.In simpler terms, video-analytics is the love child of video and IoT.
It is the technology that applies machine-learning algorithms to video feeds, which, in turn, allows cameras to recognize people, objects, and situations automatically.
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As per report by McKinsey and Co., the demand for AI video-analytics applications would be greatest in the city, retail, vehicle and work-site settings by the year 2020. Similar trends are expected in the manufacturing industry as well.
AI powered video-analytics software provided by Silversparro analyzes video inputs; transforms them into intelligent data which further helps in making decisions.
Silversparro offers video analytics solutions via Sparrosense, which is a suite of plug and play video-analytics apps for your business.
Sparrosene AI apps are built to scale leveraging the best of Edge, Cloud,and AI technologies and can be real-time, that is, configured to track and provide alerts to specific incidents as they occur – or post event, meaning that they can retrospectively search for incidents that have already taken place.
Recent years have seen a rise in the applications of the CCTV surveillance and analytics apps are seeing rapid growth due to factors like the sophistication of analytical algorithms and lower costs for hardware, software, and storage devices.
Video-analytics is showing signs of growing more and more prevalent in the world, with a report by Technavio predicting an 11% growth in the global video surveillance market between the years 2019 and 2021.
The following are the key reasons for the sudden burst of interest in the field of video analytics for businesses like yours:
The systems installed with latest video-analytics software are capable of processing very high volumes of video footage in real time. This feature allows the users to identify potential problems at the earliest and take immediate corrective measures to deal with the same.
Video-analytics applications have the capability to provide much more precise image analysis than was possible till now. This revolution in surveillance applications from the first ones which were only capable of basic motion detection, using pixel matching and frame referencing to detect changes in the position of objects within their view to the current video-analytics applications that can recognize and disregard motions that previously triggered false alarms, such as a leaf falling in front of a security camera has greatly increased the accuracy and precision of the AI-powered CCTV surveillance systems.
In addition to the enhanced accuracy and precision of the latest video-analytics systems, the users can even program the systems to detect specific visual patterns as per their requirements, like movements associated with retail theft or the appearance of flames based on trends.
As the latest video-analytics applications can consider multiple visual inputs, they are capable of advanced image-processing, especially of the ones which may be ambiguous and require careful processing. For example, by assessing the demographics and behaviors of retail customers, and using it as business insights can assist with product assortment and placement, which can potentially improve store efficiency, customer conversion, customer loyalty, and other such metrics.
With enhanced technology and software that can be customized, audio and video footage's can be compiled and analyzed at the same, providing the user a better understanding of the event that occurred.
The software algorithms in video-analytics applications are now capable of generating more detailed insights bg gathering and analyzing video footage from multiple sources. For example, in the manufacturing industry, video analytics can help track the movement of every person that enters a warehouse and makes some changes to the inventories and they can be identified by their physical characteristics collected from video feeds.
Video footage from various sources can be collected via CCTVs and using the internet can be shared to the same IP address, without any need for deploying human resources at any step of the way.
With every new G added to the internet services, your work gets easier. Meaning, the ease of accessibility and sharing over the network increases. This, in turn, helps better and faster collection of data and its sharing.
With the internet services and technology improving at the same place, the CCTV cameras are becoming better at their task too. Pervasive CCTV cameras that can record videos with better quality enhance the chances of the viewer exploring more details in the video feeds.
With improved variety of hardware which enables edge processing, the response time reduces and the bandwidth improves. With the combination of faster internet services and better hardware, edge computing systems are capable of accelerating the creation and support of real-time applications, such as video processing and analytics, self-driving cars, and artificial intelligence, to name a few.
With the increased onrush of AI-powered video analytics systems in the industry, it is only obvious to understand what the pros and cons of the system are. Or stating it simply, what the benefits and the challenges of the system are that need to be considered before installing it.
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