Global Automatic License Plate Recognition (ALPR) Systems Market Research Report 2021

SKU ID : QYR-19366315 | Publishing Date : 14-Oct-2021 | No. of pages : 133

Automatic number-plate recognition (ANPR; see also other names below) is a technology that uses optical character recognition on images to read vehicle registration plates to create vehicle location data. It can use existing closed-circuit television, road-rule enforcement cameras, or cameras specifically designed for the task. ANPR is used by police forces around the world for law enforcement purposes, including to check if a vehicle is registered or licensed. It is also used for electronic toll collection on pay-per-use roads and as a method of cataloguing the movements of traffic, for example by highways agencies.
In this study, the market for the Automatic License Plate Recognition (ALPR) consumption divided into five geographic regions. Europe was the largest market for ANPR systems in 2017. The large market in this region can be attributed to the high adoption of intelligent transportation systems for traffic management, tolling management, law/police enforcement, and other applications. Factors that are driving this market include the infrastructure growth in emerging economies, increasing allocation of funds by various governments on intelligent transport system (ITS), deployment of camera technologies in security and surveillance, and traffic enforcement application, and the growing usage of video analytics technology for intelligent monitoring of vehicles.

The global Automatic License Plate Recognition (ALPR) Systems market was valued at US$ XX million in 2020 and is expected to reach US$ XX million by the end of 2027, growing at a CAGR of XX% during 2021-2027.
This report focuses on Automatic License Plate Recognition (ALPR) Systems volume and value at the global level, regional level and company level. From a global perspective, this report represents overall Automatic License Plate Recognition (ALPR) Systems market size by analysing historical data and future prospect. Regionally, this report focuses on several key regions: North America, Europe, Asia-Pacific, Latin America and Middle East & Africa.

Global Automatic License Plate Recognition (ALPR) Systems Market: Segment Analysis
The research report includes specific segments by region (country), by company, by Type and by Application. This study provides information about the sales and revenue during the historic and forecasted period of 2016 to 2027. Understanding the segments helps in identifying the importance of different factors that aid the market growth.

Segment by Type
Cameras
Hardware
Software & Services

Segment by Application
Traffic Management& Law Enforcement
Electronic Toll Collection
Car Park Management
Others

By Region
North America
U.S.
Canada
Europe
Germany
France
U.K.
Italy
Russia
Asia-Pacific
China
Japan
South Korea
India
Australia
Taiwan
Indonesia
Thailand
Malaysia
Philippines
Vietnam
Latin America
Mexico
Brazil
Argentina
Middle East & Africa
Turkey
Saudi Arabia
U.A.E

By Company
Neology
Siemens
Elsag
Kapsch TrafficCom
ARH
Genetec
Bosch Security Systems
NDI Recognition Systems
Tattile
Arvoo Imaging Products
Shenzhen AnShiBao
Petards Group
Digital Recognition Systems
CA Traffic
Clearview Communications
GeoVision
NEXCOM
HTS
TagMaster
ParkingEye Limited
AlertSystems
MAV Systems

Frequently Asked Questions

This market study covers the global and regional market with an in-depth analysis of the overall growth prospects in the market. Furthermore, it sheds light on the comprehensive competitive landscape of the global market. The report further offers a dashboard overview of leading companies encompassing their successful marketing strategies, market contribution, recent developments in both historic and present contexts.
  • By product type
  • By End User/Applications
  • By Technology
  • By Region
The report provides a detailed evaluation of the market by highlighting information on different aspects which include drivers, restraints, opportunities, and threats. This information can help stakeholders to make appropriate decisions before investing.
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