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Automated Fingerprint Identification System (AFIS) Market Valued at USD 7.64 Billion in 2019; Will Surpass USD 33.39 Billion by 2026 at 23.8% CAGR | North America Region Holds the Leading Market Share with Valuation of USD 2,755 Million


Global Overview
Automated fingerprint identification systems are used in identifying personnel based on their fingerprints. Utilization of biometric systems for authorized entry into restricted locations and preventing unlawful trespassing are likely to witness its huge adoption by enterprises and government entities. The global AFIS (automated finger identification system) market size can surge to a valuation of USD 33.39 billion by 2026, growing at a 23.8% CAGR during the forecast period (2020-2026). Prominent uses of AFIS applications are electronic voter registration, election management, fraud prevention, e-passports, biometric visas, and digitized documentation.
The AFIS Market is expected to gain traction owing to growing concerns of offline and online payments. The high penetration rate of the internet combined with need for AFIS for rapid and accurate identification of individuals can drive the global market growth. Moreover, government plans for legalizing biomet ....

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Global Automatic Number Plate Recognition (ANPR) System Markets, 2016-2020 and 2021-2022 & 2026


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The Global Automatic Number Plate Recognition (ANPR) System Market is expected to grow at a formidable rate of around 10% during the forecast period.
The Global Automatic Number Plate Recognition (ANPR) System Market is driven by the growing need for effective traffic management and safety. The increasing incidences of thefts, crimes, road accidents, breach of traffic laws, among others are expected to fuel the market growth during the forecast period.
Furthermore, increased adoption of advanced technologies such as cloud based services, IoT, AI, among others is expected to propel the market through 2026. However, inconsistency in size, designs, font, color, style, among others can hamper the market growth over the next few years since it becomes very difficult to make an algorithm that can read all the different number plates pattern without any discrepancy. ....

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