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Automatic Number Plate Recognition (ANPR) System Market size was valued at USD 3.2 billion in 2023 and is estimated to register a CAGR of over 9% between 2023 and 2032. The surge in global investments in smart cities is propelling the market growth. As cities worldwide prioritize advanced technologies for urban development, these systems facilitate intelligent transportation, security, and surveillance. The growing emphasis on efficient traffic management, law enforcement, and smart infrastructure within these smart city initiatives significantly contributes to market growth.
According to the India Investment Grid Organization, the Smart City Mission in India encompasses 1,130 projects across multiple states, amounting to a significant investments of USD 26.37 billion as of October 2023. Focused on urban development, these projects aim to enhance infrastructure, technology integration, and the overall quality of life in designated cities, fostering sustainable and intelligent urban growth.
Report Attribute | Details |
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Base Year: | 2023 |
Automatic Number Plate Recognition System Market Size in 2023: | USD 3.2 Billion |
Forecast Period: | 2024 to 2032 |
Forecast Period 2024 to 2032 CAGR: | 9% |
2032 Value Projection: | USD 6.8 Billion |
Historical Data for: | 2018 - 2023 |
No. of Pages: | 250 |
Tables, Charts & Figures: | 346 |
Segments covered: | Component, Type, Application, End Use |
Growth Drivers: |
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Pitfalls & Challenges: |
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The integration of smart parking technology and tolling applications is driving the automatic number plate recognition system market size. As cities and organizations adopt advanced solutions for efficient parking management and seamless toll collection, these systems play a crucial role in automating these processes. For instance, in July 2023, Mangaluru International Airport (MIA) implemented the Automatic Number Plate Recognition (ANPR) system, facilitating frictionless entry and exit for vehicles. Integrating e-payment technologies, such as FASTag, streamlines payment processes for users, thereby enhancing efficiency.
The ANPR system market faces challenges due to the inconsistency in number plate designs. Varied plate formats, fonts, and colors across regions make it difficult for ANPR systems to interpret data uniformly and accurately. This diversity hampers the system's effectiveness, leading to potential errors in identification. Standardizing number plate designs poses a hurdle, necessitating advanced recognition algorithms to cope with the variability and ensure reliable performance in these systems across diverse locations.