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Intelligent Traffic Cameras Market Decade Long Trends, Analysis and Forecast 2025-2033
Latest study released by AMA Research on Global Intelligent Traffic Cameras Market research focuses on latest market trend, opportunities and various future aspects so you can get a variety of ways to maximize your profits. Intelligent Traffic Cameras Market predicted until 2030*.
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Rising adoption of intelligent traffic cameras for traffic control and monitoring is due to the significant advances in the field of computer vision will help to boost the global intelligent traffic camera market. An intelligent traffic camera is referred to as a video camera that detects vehicular traffic on a road by using artificial intelligence. It helps expand traffic safety as well as mobility while improving productivity. There are various features which help to drive market including compact, onboard memory buffering, lightweight, versatile choice of a data interface, and ruggedized for harsh environments. Moreover, technological advancements, multi-tasking capabilities, and large coverage area are few other growth factors.
Some of Key Players included in Intelligent Traffic Cameras Market are Teledyne DALSA Inc. (Canada), FLIR Systems, Inc. (United States), Omnibond Systems, LLC (United States), EFKON India Pvt. Ltd. (India), BOSCH SECURITY SYSTEMS (United States), TV Rheinland (Germany), ATT Systems Group (Singapore), OMNIBOND SYSTEMS, LLC (United States), FLIR SYSTEMS, INC. (United States), TYCO SECURITY PRODUCTS (Johnson Controls) (United States),
Market Trends:
Up Surging Demand Due To Increase in Traffic Problems
Growing Demand Large Coverage Area
Market Drivers:
Rising Demand Due to Multi-Tasking Capabilities
High Adoption due To Technological Advancements
Market Opportunities:
High Growth Rate of Vehicle Sales
Rise in Trend of Computerized Surveillance
The titled segments and Market Data are Break Down by Type (Mega-Pixel 2-5, Mega-Pixel 5-8, Others), Application (Speed Measurement, Security Monitoring, Others), Distribution Channel (Online, Offline)
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