Automatic Number Plate Recognition (ANPR) System Market Size, Trends and Insights By Type (Fixed, Mobile), By Component (Hardware, ANPR Cameras, Triggers, Frame Grabbers, Software), By Application (Traffic Management, Electronic Toll Collection, Law Enforcement, Parking Management, Others), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033
Report Snapshot
| Study Period: | 2024-2033 |
| Fastest Growing Market: | Asia-Pacific |
| Largest Market: | Europe |
Major Players
- Kasich TrafficCom AG
- Siemens AG
- Vigilant Solutions
- Conduent Inc.
- Others
Reports Description
According to Custom Market Insights (CMI), The Global Automatic Number Plate Recognition Market size was estimated at USD 2.5 Billion in 2021 and is expected to reach USD 2.9 Billion in 2022 and is anticipated to reach around USD 6 Billion by 2030, growing at a CAGR of roughly 10% between 2022 and 2030.
The global Automatic Number Plate Recognition Market research report offers an in-depth analysis of the worldwide market size, which is further segmented into regional and country-level market size, and segmentation market growth. Also, it provides market share, sales analysis, competitive landscape, impact of domestic and global market participants, trade regulations, value chain optimization, recent key developments, strategic market growth analysis, opportunities analysis, product launches, and technological innovations.
- Automatic number plate systems provide fast traffic control in parking lots, the automation of access control systems with the implementation of a ticket-free system, and new, effective law enforcement methods. ANPR cameras are set higher to ensure a larger field of vision of the entire parking lot, capturing the vehicle’s license plate number as it enters or exits the building.
- ANPR cameras are integrated with car parking management systems, which record the allowed vehicle’s entry and exit timing information and the parking spot and owner’s information. The information regarding the vehicle and the responsible party who damaged the parked car in the parking lot can be found in the system records if any car in the parking is injured by another vehicle. Their use is expanding for smart parking to address these issues, fueling the market for automatic number plate recognition systems.
- The most recent generation of mobile ANPR systems has sensors that can scan license plates up to 60 times per second, both front and back, in all lighting circumstances. Since they are deployed in specific vehicles used by intelligence services or emergency services to support protection and surveillance operations, these mobile ANPR devices are an intelligent way to prevent traffic accidents since they are constantly watchfully on the road.
- Many businesses are being impacted by Covid 19. There are some obstacles in the market for automatic number plate identification. In many areas, the number of roadside cameras is declining. Vehicles on the road are subject to limitations. The need for automatic number plate recognition is seeing a decrease in demand due to restrictions and lockdowns. There is less traffic congestion overall, but especially in the megacities. The market is also severely disrupted by the supply chain. Numerous end users have cut back on their need for number plate recognition.
- Currently, there is a decline in the adoption of automatic number plate recognition. There will likely be a tonne of traffic on the roadways in the upcoming year. In the future years, there will be fewer traffic restrictions. The amount of money that governments are investing in these technologies is increasing. Particularly, markets like the Asia Pacific are seeing an increase in demand for the product. The need for automatic number plate recognition will benefit from all of these.
Report Scope
The study focuses on Automatic Number Plate Recognition Market analysis on a global scale, and market sizing includes the revenue generated by these products provided by different market players. To support the market projections and growth rates over the anticipated 2022-2030, the study additionally monitors essential market factors, underlying growth factors, and significant vendors active in the sector. The study also examines how COVID-19 has affected the ecology generally. The scope of the study includes market sizing and forecast for segmentation by type, component, application, and geography.
| Feature of the Report | Details |
| Market Size in 2021 | USD 2.5 Billion |
| Projected Market Size in 2030 | USD 6 Billion |
| Market Size in 2022 | USD 2.9 Billion |
| CAGR Growth Rate | 10% CAGR (2022-2030) |
| Base Year | 2023 |
| Forecast Period | 2024-2033 |
| Prominent Players | Kasich TrafficCom AG, Siemens AG, Vigilant Solutions, Conduent Inc., Leonardo Company, Tattile SRL, Jenoptik Group, Neology Inc., Genetec Inc., Bosch Group, and Others |
| Key Segment | By Type, Component, Application, and Region |
| Report Coverage | Revenue Estimation and Forecast, Company Profile, Competitive Landscape, Growth Factors and Recent Trends |
| Regional Scope | North America, Europe, Asia Pacific, Middle East & Africa, and South & Central America |
| Buying Options | Request tailored purchasing options to fulfil your requirements for research. |
Key Market Dynamics
- The expansion of the worldwide automated number plate recognition market is anticipated to be fueled by rising demand for ANPR systems for traffic enforcement and management over the projected period. A regular occurrence all across the world is the rise in traffic accidents caused by violations of the law. The World Health Organization (WHO) estimates that 1.35 million individuals each year pass away as a result of traffic accidents. The same source estimates that road traffic accidents cost the majority of nations about 3% of their GDP.
- To increase traffic safety, traffic police departments worldwide are implementing innovative technologies. Since it promotes mobility and traffic safety, automatic number plate recognition is crucial in traffic management. Free-flowing traffic can be made possible through traffic system improvement, leading to quicker mobility and minimal financial loss. Additionally, this technology is economical because it does not need to install gear inside the car or halt traffic.
- Over the projected period, a rising need for better security in the public sector is anticipated to fuel the expansion of the global automatic number plate recognition market. Security companies and police organizations employ automated number plate recognition technology to maintain public safety.
- Police departments often employ ANPR for three primary purposes: intelligence gathering, identifying vehicles used by criminals, and criminal investigation. For instance, a police department in the United States has set up ANPR cameras across all 51 states to trace automobiles used in illegal activity. This is because ANPR systems have the potential to build databases in real-time.
Software Segment to Dominate the Automatic Number Plate Recognition Market
- The ANPR system market can be divided into three categories based on its components: hardware, software, and services. The demand for ANPR frameworks was led by the hardware segment, which is expected to grow significantly during the projected period. The need will likely increase with IoT, enabling radical hardware synchronization through cloud-based computing services.
- The development of the hardware sector is accelerated by the rising demand for ANPR cameras for integration into aeroplanes, patrol vehicles, and Unmanned Aerial Vehicles (UAVs). The effectiveness of ANPR hardware has been improved thanks to significant developments in digital signal processors (DSPs) and field programmable gate arrays (FPGAs). These gadgets currently use a different camera, which is then processed by a separate PC.
- The software market will continue to expand steadily. It relates to photo and character recognition through the ANPR system’s OCR, GUI, and database. The development of the software sector is driven by the growing emphasis businesses place on developing online ANPR software. The program’s growth is driven by the increasing demand for ANPR software that supports ANPR cameras from multiple OEMs.
Competitive Landscape
Leading firms in the automatic number plate recognition system market use collaborations and product innovation as essential tactics to increase their revenue. To enhance their market share, manufacturers in the ANPR system market focus on developing innovative goods and services.
- 2020: To identify vehicle color, class, model, and other information, Q-Free ASA created vehicle analytics solutions for its ANPR portfolio.
- 2019: Next-generation mobile automatic license plate recognition systems with Intel’s Vision processing unit technology were unveiled by Genetec Inc.
Prominent Players:
- Kasich TrafficCom AG
- Siemens AG
- Vigilant Solutions
- Conduent Inc.
- Leonardo Company
- Tattile SRL
- Jenoptik Group
- Neology Inc.
- Genetec Inc.
- Bosch Group
The global Automatic Number Plate Recognition (ANPR) System market is segmented as follows:
By Type
- Fixed
- Mobile
By Component
- Hardware
- ANPR Cameras
- Triggers
- Frame Grabbers
- Software
By Application
- Traffic Management
- Electronic Toll Collection
- Law Enforcement
- Parking Management
- Others
On the basis of Geography
North America
- U.S.
- Canada
- Mexico
- Rest of North America
Europe
- Germany
- France
- U.K.
- Italy
- Spain
- Rest of Europe
Asia Pacific
- China
- Japan
- India
- New Zealand
- Australia
- South Korea
- Rest of Asia Pacific
The Middle East & Africa
- Saudi Arabia
- UAE
- Egypt
- Kuwait
- South Africa
- Rest of the Middle East & Africa
Latin America
- Brazil
- Argentina
- Rest of Latin America
Table of Contents
- Chapter 1. Preface
- 1.1 Report Description and Scope
- 1.2 Research scope
- 1.3 Research methodology
- 1.3.1 Market Research Type
- 1.3.2 Market research methodology
- Chapter 2. Executive Summary
- 2.1 Global Automatic Number Plate Recognition Market, (2022 – 2030) (USD Million)
- 2.2 Global Automatic Number Plate Recognition Market : snapshot
- Chapter 3. Global Automatic Number Plate Recognition Market – Industry Analysis
- 3.1 Automatic Number Plate Recognition Market: Market Dynamics
- 3.2 Market Drivers
- 3.2.1 Expanding use of surveillance technologies on highways
- 3.3 Market Restraints
- 3.4 Market Opportunities
- 3.5 Market Challenges
- 3.6 Porter’s Five Forces Analysis
- 3.7 Market Attractiveness Analysis
- 3.7.1 Market attractiveness analysis By Type
- 3.7.2 Market attractiveness analysis By Component
- 3.7.3 Market attractiveness analysis By Application
- Chapter 4. Global Automatic Number Plate Recognition Market- Competitive Landscape
- 4.1 Company market share analysis
- 4.1.1 Global Automatic Number Plate Recognition Market: company market share, 2021
- 4.2 Strategic development
- 4.2.1 Acquisitions & mergers
- 4.2.2 New Product launches
- 4.2.3 Agreements, partnerships, cullaborations, and joint ventures
- 4.2.4 Research and development and Regional expansion
- 4.3 Price trend analysis
- 4.1 Company market share analysis
- Chapter 5. Global Automatic Number Plate Recognition Market – Type Analysis
- 5.1 Global Automatic Number Plate Recognition Market overview: By Type
- 5.1.1 Global Automatic Number Plate Recognition Market share, By Type, 2021 and 2030
- 5.2 Fixed
- 5.2.1 Global Automatic Number Plate Recognition Market by Fixed, 2022 – 2030 (USD Million)
- 5.3 Mobile
- 5.3.1 Global Automatic Number Plate Recognition Market by Mobile, 2022 – 2030 (USD Million)
- 5.1 Global Automatic Number Plate Recognition Market overview: By Type
- Chapter 6. Global Automatic Number Plate Recognition Market – Component Analysis
- 6.1 Global Automatic Number Plate Recognition Market overview: By Component
- 6.1.1 Global Automatic Number Plate Recognition Market share, By Component, 2021 and 2030
- 6.2 Hardware
- 6.2.1 Global Automatic Number Plate Recognition Market by Hardware, 2022 – 2030 (USD Million)
- 6.3 ANPR Cameras
- 6.3.1 Global Automatic Number Plate Recognition Market by ANPR Cameras, 2022 – 2030 (USD Million)
- 6.4 Triggers
- 6.4.1 Global Automatic Number Plate Recognition Market by Triggers, 2022 – 2030 (USD Million)
- 6.5 Frame Grabbers
- 6.5.1 Global Automatic Number Plate Recognition Market by Frame Grabbers, 2022 – 2030 (USD Million)
- 6.6 Software
- 6.6.1 Global Automatic Number Plate Recognition Market by Software, 2022 – 2030 (USD Million)
- 6.1 Global Automatic Number Plate Recognition Market overview: By Component
- Chapter 7. Global Automatic Number Plate Recognition Market – Application Analysis
- 7.1 Global Automatic Number Plate Recognition Market overview: By Application
- 7.1.1 Global Automatic Number Plate Recognition Market share, By Application, 2021 and 2030
- 7.2 Traffic Management
- 7.2.1 Global Automatic Number Plate Recognition Market by Traffic Management, 2022 – 2030 (USD Million)
- 7.3 Electronic Toll Collection
- 7.3.1 Global Automatic Number Plate Recognition Market by Electronic Toll Collection, 2022 – 2030 (USD Million)
- 7.4 Law Enforcement
- 7.4.1 Global Automatic Number Plate Recognition Market by Law Enforcement, 2022 – 2030 (USD Million)
- 7.5 Parking Management
- 7.5.1 Global Automatic Number Plate Recognition Market by Parking Management, 2022 – 2030 (USD Million)
- 7.6 Others
- 7.6.1 Global Automatic Number Plate Recognition Market by Others, 2022 – 2030 (USD Million)
- 7.1 Global Automatic Number Plate Recognition Market overview: By Application
- Chapter 8. Automatic Number Plate Recognition Market – Regional Analysis
- 8.1 Global Automatic Number Plate Recognition Market Regional Overview
- 8.2 Global Automatic Number Plate Recognition Market Share, by Region, 2021 & 2030 (USD Million)
- 8.3. North America
- 8.3.1 North America Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.3.1.1 North America Automatic Number Plate Recognition Market, by Country, 2022 – 2030 (USD Million)
- 8.3.1 North America Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.4 North America Automatic Number Plate Recognition Market, by Type, 2022 – 2030
- 8.4.1 North America Automatic Number Plate Recognition Market, by Type, 2022 – 2030 (USD Million)
- 8.5 North America Automatic Number Plate Recognition Market, by Component, 2022 – 2030
- 8.5.1 North America Automatic Number Plate Recognition Market, by Component, 2022 – 2030 (USD Million)
- 8.6 North America Automatic Number Plate Recognition Market, by Application, 2022 – 2030
- 8.6.1 North America Automatic Number Plate Recognition Market, by Application, 2022 – 2030 (USD Million)
- 8.7. Europe
- 8.7.1 Europe Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.7.1.1 Europe Automatic Number Plate Recognition Market, by Country, 2022 – 2030 (USD Million)
- 8.7.1 Europe Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.8 Europe Automatic Number Plate Recognition Market, by Type, 2022 – 2030
- 8.8.1 Europe Automatic Number Plate Recognition Market, by Type, 2022 – 2030 (USD Million)
- 8.9 Europe Automatic Number Plate Recognition Market, by Component, 2022 – 2030
- 8.9.1 Europe Automatic Number Plate Recognition Market, by Component, 2022 – 2030 (USD Million)
- 8.10 Europe Automatic Number Plate Recognition Market, by Application, 2022 – 2030
- 8.10.1 Europe Automatic Number Plate Recognition Market, by Application, 2022 – 2030 (USD Million)
- 8.11. Asia Pacific
- 8.11.1 Asia Pacific Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.11.1.1 Asia Pacific Automatic Number Plate Recognition Market, by Country, 2022 – 2030 (USD Million)
- 8.11.1 Asia Pacific Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.12 Asia Pacific Automatic Number Plate Recognition Market, by Type, 2022 – 2030
- 8.12.1 Asia Pacific Automatic Number Plate Recognition Market, by Type, 2022 – 2030 (USD Million)
- 8.13 Asia Pacific Automatic Number Plate Recognition Market, by Component, 2022 – 2030
- 8.13.1 Asia Pacific Automatic Number Plate Recognition Market, by Component, 2022 – 2030 (USD Million)
- 8.14 Asia Pacific Automatic Number Plate Recognition Market, by Application, 2022 – 2030
- 8.14.1 Asia Pacific Automatic Number Plate Recognition Market, by Application, 2022 – 2030 (USD Million)
- 8.15. Latin America
- 8.15.1 Latin America Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.15.1.1 Latin America Automatic Number Plate Recognition Market, by Country, 2022 – 2030 (USD Million)
- 8.15.1 Latin America Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.16 Latin America Automatic Number Plate Recognition Market, by Type, 2022 – 2030
- 8.16.1 Latin America Automatic Number Plate Recognition Market, by Type, 2022 – 2030 (USD Million)
- 8.17 Latin America Automatic Number Plate Recognition Market, by Component, 2022 – 2030
- 8.17.1 Latin America Automatic Number Plate Recognition Market, by Component, 2022 – 2030 (USD Million)
- 8.18 Latin America Automatic Number Plate Recognition Market, by Application, 2022 – 2030
- 8.18.1 Latin America Automatic Number Plate Recognition Market, by Application, 2022 – 2030 (USD Million)
- 8.19. The Middle-East and Africa
- 8.19.1 The Middle-East and Africa Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.19.1.1 The Middle-East and Africa Automatic Number Plate Recognition Market, by Country, 2022 – 2030 (USD Million)
- 8.19.1 The Middle-East and Africa Automatic Number Plate Recognition Market, 2022 – 2030 (USD Million)
- 8.20 The Middle-East and Africa Automatic Number Plate Recognition Market, by Type, 2022 – 2030
- 8.20.1 The Middle-East and Africa Automatic Number Plate Recognition Market, by Type, 2022 – 2030 (USD Million)
- 8.21 The Middle-East and Africa Automatic Number Plate Recognition Market, by Component, 2022 – 2030
- 8.21.1 The Middle-East and Africa Automatic Number Plate Recognition Market, by Component, 2022 – 2030 (USD Million)
- 8.22 The Middle-East and Africa Automatic Number Plate Recognition Market, by Application, 2022 – 2030
- 8.22.1 The Middle-East and Africa Automatic Number Plate Recognition Market, by Application, 2022 – 2030 (USD Million)
- Chapter 9. Company Profiles
- 9.1 Kasich TrafficCom AG
- 9.1.1 Overview
- 9.1.2 Financials
- 9.1.3 Product Portfolio
- 9.1.4 Business Strategy
- 9.1.5 Recent Developments
- 9.2 Siemens AG
- 9.2.1 Overview
- 9.2.2 Financials
- 9.2.3 Product Portfolio
- 9.2.4 Business Strategy
- 9.2.5 Recent Developments
- 9.3 Vigilant Solutions
- 9.3.1 Overview
- 9.3.2 Financials
- 9.3.3 Product Portfolio
- 9.3.4 Business Strategy
- 9.3.5 Recent Developments
- 9.4 Conduent Inc.
- 9.4.1 Overview
- 9.4.2 Financials
- 9.4.3 Product Portfolio
- 9.4.4 Business Strategy
- 9.4.5 Recent Developments
- 9.5 Leonardo Company
- 9.5.1 Overview
- 9.5.2 Financials
- 9.5.3 Product Portfolio
- 9.5.4 Business Strategy
- 9.5.5 Recent Developments
- 9.6 Tattile SRL
- 9.6.1 Overview
- 9.6.2 Financials
- 9.6.3 Product Portfolio
- 9.6.4 Business Strategy
- 9.6.5 Recent Developments
- 9.7 Jenoptik Group
- 9.7.1 Overview
- 9.7.2 Financials
- 9.7.3 Product Portfolio
- 9.7.4 Business Strategy
- 9.7.5 Recent Developments
- 9.8 Neology Inc.
- 9.8.1 Overview
- 9.8.2 Financials
- 9.8.3 Product Portfolio
- 9.8.4 Business Strategy
- 9.8.5 Recent Developments
- 9.9 Genetec Inc.
- 9.9.1 Overview
- 9.9.2 Financials
- 9.9.3 Product Portfolio
- 9.9.4 Business Strategy
- 9.9.5 Recent Developments
- 9.10 Bosch Group
- 9.10.1 Overview
- 9.10.2 Financials
- 9.10.3 Product Portfolio
- 9.10.4 Business Strategy
- 9.10.5 Recent Developments
- 9.1 Kasich TrafficCom AG
List Of Figures
Figures No 1 to 28
List Of Tables
Tables No 1 to 77
Report Methodology
In order to get the most precise estimates and forecasts possible, Custom Market Insights applies a detailed and adaptive research methodology centered on reducing deviations. For segregating and assessing quantitative aspects of the market, the company uses a combination of top-down and bottom-up approaches. Furthermore, data triangulation, which examines the market from three different aspects, is a recurring theme in all of our research reports. The following are critical components of the methodology used in all of our studies:
Preliminary Data Mining
On a broad scale, raw market information is retrieved and compiled. Data is constantly screened to make sure that only substantiated and verified sources are taken into account. Furthermore, data is mined from a plethora of reports in our archive and also a number of reputed & reliable paid databases. To gain a detailed understanding of the business, it is necessary to know the entire product life cycle and to facilitate this, we gather data from different suppliers, distributors, and buyers.
Surveys, technological conferences, and trade magazines are used to identify technical issues and trends. Technical data is also gathered from the standpoint of intellectual property, with a focus on freedom of movement and white space. The dynamics of the industry in terms of drivers, restraints, and valuation trends are also gathered. As a result, the content created contains a diverse range of original data, which is then cross-validated and verified with published sources.
Statistical Model
Simulation models are used to generate our business estimates and forecasts. For each study, a one-of-a-kind model is created. Data gathered for market dynamics, the digital landscape, development services, and valuation patterns are fed into the prototype and analyzed concurrently. These factors are compared, and their effect over the projected timeline is quantified using correlation, regression, and statistical modeling. Market forecasting is accomplished through the use of a combination of economic techniques, technical analysis, industry experience, and domain knowledge.
Short-term forecasting is typically done with econometric models, while long-term forecasting is done with technological market models. These are based on a synthesis of the technological environment, legal frameworks, economic outlook, and business regulations. Bottom-up market evaluation is favored, with crucial regional markets reviewed as distinct entities and data integration to acquire worldwide estimates. This is essential for gaining a thorough knowledge of the industry and ensuring that errors are kept to a minimum.
Some of the variables taken into account for forecasting are as follows:
• Industry drivers and constraints, as well as their current and projected impact
• The raw material case, as well as supply-versus-price trends
• Current volume and projected volume growth through 2030
We allocate weights to these variables and use weighted average analysis to determine the estimated market growth rate.
Primary Validation
This is the final step in our report’s estimating and forecasting process. Extensive primary interviews are carried out, both in-person and over the phone, to validate our findings and the assumptions that led to them.
Leading companies from across the supply chain, including suppliers, technology companies, subject matter experts, and buyers, use techniques like interviewing to ensure a comprehensive and non-biased overview of the business. These interviews are conducted all over the world, with the help of local staff and translators, to overcome language barriers.
Primary interviews not only aid with data validation, but also offer additional important insight into the industry, existing business scenario, and future projections, thereby improving the quality of our reports.
All of our estimates and forecasts are validated through extensive research work with key industry participants (KIPs), which typically include:
• Market leaders
• Suppliers of raw materials
• Suppliers of raw materials
• Buyers.
The following are the primary research objectives:
• To ensure the accuracy and acceptability of our data.
• Gaining an understanding of the current market and future projections.
Data Collection Matrix
| Perspective | Primary research | Secondary research |
| Supply-side |
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| Demand-side |
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Market Analysis Matrix
| Qualitative analysis | Quantitative analysis |
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FAQs
“North America” region will lead the global Automatic Number Plate Recognition market during the forecast period 2022 to 2030.
The key factors driving the market is expanding use of surveillance technologies on highways.
The key players operating in the Automatic Number Plate Recognition market are Kasich TrafficCom AG, Siemens AG, Vigilant Solutions, Conduent Inc., Leonardo Company, Tattile SRL, Jenoptik Group, Neology Inc., Genetec Inc., Bosch Group
The global Automatic Number Plate Recognition market is expanding growth with a CAGR of approximately 10% during the forecast period (2022 to 2030).
The global Automatic Number Plate Recognition market size was valued at USD 2.5 Billion in 2021 and it is projected to reach around USD 6 Billion by 2030.