The increase in the budget for procuring advanced video surveillance systems by various countries including the U.S., India, Russia, Israel, China, Singapore, South Korea, and among others, for procuring technically advanced video surveillance systems to track the individuals’ quarantine activity is playing a major role in strengthening the market growth.
Read Report Overview: https://bisresearch.com/industry-report/global-video-surveillance-market.html
Stringent regulations posed by various governments to install video surveillance systems in educational institutes is expected to propel the market growth. For instance, in June 2015, the U.S. government passed a law in Texas to mandate the deployment of video surveillance units in special education classrooms including all public schools and self-contained classrooms. Further, the U.S. higher educational institutes have also planned to propose body-warn cameras and other video surveillance units due to the growing campus shootings. For instance, in May 2020, Konica Minolta Business Solutions U.S.A., Inc. received a contract from the Ohio Council of Educational Purchasing Consortia (OCEPC) to provide MOBOTIX Intelligent Camera Solutions to higher education institutions, local government agencies, and other public entities of Ohio to ensure safety and security.
With the video surveillance industry undergoing a paradigm shift, the use of Internet Protocol (IP) technology-based cameras using IoT has increased, resulting in transforming of the surveillance industry. The IP cameras allow the users to convert their local broadband connection into a home surveillance system. Some features of IP-based camera outpacing the traditional analog closed-circuit television cameras (CCTV) are as follows:
The cloud-based analytics offers intelligent video services without the need for additional hardware or licensing fees. The data coming from different locations through a single web-based interface is analyzed at one place. Since analog cameras work with digital video recorder (DVR) storage technology, they cannot highlight any event. In case of a crime detection event, it might take a longer period of time to play or analyze the full video. However, an IP system with video analytics can highlight or flag events with functions such as motion detection, camera tampering, and a range of other events.
For Sample Report, Click here: https://bisresearch.com/requestsample?id=935&type=download
With the increasing adoption of video surveillance systems for various applications such as infrastructure security, business intelligence, and preserving law and order, the dependence on these surveillance systems has gradually increased. Their performance not only depends on efficiency but is also driven by promptness, accuracy, and embedded processors employed. These processors basically provide features such as securing intellectual property, lowering power dissipation, minimizing cost, and reducing the overall development time. Therefore, the developers are readily grabbing the opportunity of introducing such processors. The existing options for processors in the video surveillance systems are digital still camera (DSC) processors, application-specific integrated circuits (ASIC), digital signal processors (DSP), and field-programmable gate arrays (FPGA).
While several factors are working in the favor of extensive deployment and adoption of video surveillance technology, there are certain factors which are hindering its overall growth in the market. Although the demand for the video surveillance is increasing at a very fast pace, the privacy issues and the cost of deployment are some of the major concerns working against the massive proliferation of video surveillance. With the rising privacy concerns, the demand for bandwidth in order to set up a video surveillance system is one of the major concerns. The major challenge in providing cloud-based video services is the lack of available bandwidth. High bandwidth internet connection is required for the rapid transmission of data with a shorter response time, which may not be available at remote locations. Since real-time analysis and detection are not possible at such locations, they pose as a challenge against the deployment of video surveillance systems.