Global Automatic Number Plate Recognition (ANPR) System Market

Dec 2018| VMR783A| Verified Market Research

Report Highlights

Global Automatic Number Plate Recognition (ANPR) System Market
By Component (ANPR Cameras, Frame Grabbers, Triggers, ANPR Software), End User (Commercial, Government), Type (Mobile ANPR Systems, Portable ANPR Systems, Fixed ANPR Systems), Application (Parking Management, Access Control, Traffic Management, Law Enforcement, Electronic Toll Collection), and Regional Market Size, Status and Forecast to 2025

Market Overview:
The Global Automatic Number Plate Recognition (ANPR) System Market was valued at USD 4.561.82 billion in 2016 and is projected to reach USD 4.16 billion by 2025, growing at a CAGR of 9.63% from 2017 to 2025.

Automatic Number Plate Recognition (ANPR) is a technology that uses optical character recognition on images to read vehicle registration plates. ANPR can be used to store the images captured by the cameras and the text from the license plate, with some configurable to store a photograph of the driver. Benefits of ANPR includes - identify potential threats, cost effective, increased security, ticketless, barrier-free system, vehicle location and crime prevention, vehicle tax evasion detection, and business premises access management.

Market Dynamics:
1. Market Drivers
1.1 Integration of parking spaces with automated technology
1.2 Rising use of cloud-base storage services
1.3 Increasing usage of video analytics technology for intelligent monitoring of vehicles
1.4 Growing investments by the government for intelligent monitoring of vehicles
1.5 Growing need for deployment of ANPR systems in security and surveillance, and traffic enforcement applications
2. Market Restraints
2.1 Inconsistency in Number Plate Designs
2.2 Misinterpretation of Ambiguous Characters on Number Plates

Market Segmentation:
The Global Automatic Number Plate Recognition (ANPR) System Market is segmented on the component, end user, type, application, and region.

1. Component:
1.1 ANPR Cameras
1.2 Frame Grabbers
1.3 Triggers
1.4 ANPR Software

2. By End User:
2.1 Commercial
2.2 Government

3. By Type:
3.1 Mobile ANPR Systems
3.2 Portable ANPR Systems
3.3 Fixed ANPR Systems

4. By Application:
4.1 Parking Management
4.2 Access Control
4.3 Traffic Management
4.4 Law Enforcement
4.5 Electronic Toll Collection

5. By Region:
5.1 North America (U.S., Canada, Mexico)
5.2 Europe (Germany, UK, France, Rest of Europe)
5.3 Asia Pacific (China, India, Japan, Rest of Asia Pacific)
5.4 Latin America (Brazil, Argentina, Rest of Latin America)
5.5 Middle East & Africa

Competitive Landscape:
The major players in the market are as follows:
1. Vigilant Solutions, Inc.
2. KAPSCH TrafficCom  AG
3. Q-Free ASA
4. Conduent, Inc.
5. Siemens AG
6. Genetec Inc.
7. Digital Recognition Systems Ltd.
8. Tattile SRL
9. NDI Recognition Systems
10. Neology, Inc.
11. ARH Inc.
12. Bosch Security Systems, Inc.
13. Elsag North America, LLC
These major players have adopted various organic as well as inorganic growth strategies such as mergers & acquisitions, new product launches, expansions, agreements, joint ventures, partnerships, and others to strengthen their position in this market.

RESEARCH METHODOLOGY OF VERIFIED MARKET INTELLIGENCE:
Research study on the Global Automatic Number Plate Recognition (ANPR) System Market was performed in five phases which include Secondary research, Primary research, subject matter expert advice, quality check and final review.
The market data was analyzed and forecasted using market statistical and coherent models. Also market shares and key trends were taken into consideration while making the report. Apart from this, other data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Company Market Share Analysis, Standards of Measurement, Top to Bottom Analysis and Vendor Share Analysis.

To know more about the Research Methodology of Verified Market Intelligence and other aspects of the research study, kindly get in touch with our sales team.

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