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Over the past few years, intelligent video analytics, also referred to as just video analytics or video content analysis, has attracted interest from both academic and industrial arenas. Advancements in deep learning technology has facilitated intelligent video analytics that automates tasks that once required exclusive interference from humans. Recent developments in intelligent video analytics have enabled the technology to find new applications, ranging from use cases that count attendees at events, to automated license/number plate recognition. Some other well-known use cases include smart parking and facial recognition.
Some use cases in the field of intelligent video analytics are widely known to end-users and the general public. One instance of such use cases is video surveillance, which involves tasks that have existed for almost 50 years. Conceptually, the task involves strategic installation of cameras to help operators control and monitor what happens in the premises under surveillance.
Practically, however, this task is far more complicated. Operators are responsible for a multitude of cameras and not just a single one. Increasing the number of operational cameras that are supposed to be monitored minimizes the productivity and performance of operators. Even when a large number of hardware solutions are made available and producing signals, a bottleneck is sure to form due to human limitations, when the time comes to analyze and process those generated signals.
Intelligent video analytics has the ability to facilitate a way to accurately deal with huge volumes of signals and other unstructured data. This capability is the primary factor enhancing the attractiveness of intelligent video analytics among probable end-users.
Stringent lockdowns have been legislated on a global scale, which have resulted in collapse of the hospitality industry. With governments prioritizing sales of essential products over non-essential goods, procurement abilities in industries like retail and manufacturing have taken a hit. End-users are cutting costs and regular clients of intelligent video analytics solution and service providers are minimizing their operational expenditures. With declining growth of key industries that maintain market stability, intelligent video analytics solution and service providers are recording declining orders on a global level. Also, with companies being forced to ensure that their employees work from home, the demand for intelligent video analytics is estimated to falter during the ongoing COVID-19 pandemic.
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Some of the key players in the global Intelligent Video Analytics market are Axis Communications, Honeywell International Inc., ALLGOVISION, Genetec, Intuvision, Avigilon, Cisco Systems Inc., Agent VI, Aventura Systems, and Intellivision, among many more.
Following are some strategies incorporated by the key players operating in the global intelligent video analytics market:
Intelligent video analytics market in North America, especially the United States, is leading the global market. Huge consistent investments made by government authorities in the region to ensure public safety and security is boosting adoption. Further, implementation of nationwide public safety LTE network is estimated to propel adoption of intelligent video analytics during the forecast period. Nations like Italy, Spain, India and ASEAN countries are always focusing on promoting tourism and with tourists flocking to such tourist nations, the adoption of intelligent video analytics is estimated to rise at a considerable growth rates during the forecast period.
The Intelligent Video Analytics market report is a compilation of first-hand information, qualitative and quantitative assessment by industry analysts, and inputs from industry experts and industry participants across the value chain. The report provides in-depth analysis of parent market trends, macro-economic indicators, and governing factors, along with market attractiveness as per segment. The market report also maps the qualitative impact of various market factors on market segments and geographies.
