The technological advancement in biometrics aims to reach a growth rate of 10.5 per cent between 2020 and 2025, to improve the security and usability of biometrics.
FREMONT, CA: The global biometric technology market is expected to grow at a compound annual growth rate (CAGR) of 10.5 per cent till 2025, reaching a total market value of USD 8.5 billion. The amount spent on research and development in this industry is also soaring as a result. Airports are increasing their investments, venture capitalists' (VCs') interest is developing, and tech alliances are springing up everywhere—the world's biometrics ecosystem is booming. The year 2022 will be a turning point for the sector, with major improvements in the application of biometrics and their security, usability, and scalability.
Edge Computing
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Recent developments in GPU processing technology have sparked the development of specialised computer platforms that are very helpful for facial recognition. Without needing to send massive data streams to centralised servers, these platforms can process video data streams locally. The preprocessing of video streams can be done independently by edge devices. Only the findings, which are sent to a central server for comparison, are provided by the edge devices for face recognition, extraction, and template construction. By several orders of magnitude, this lowers the needed throughput of the local data link by as much as tens of megabits. Additionally, edge devices are compatible with current cameras, which lowers the cost of updates. Users can run more cameras simultaneously or use less bandwidth by deploying edge devices or combining and matching them based on the setup that is needed, which improves cloud operability.
Biometrics in the Cloud
Processing-intensive jobs can now be transferred to the cloud instead of a dedicated local server with only a little performance penalty because of the reduction in necessary bandwidth, a task that was previously unimaginable for real-time facial recognition. This enormous advancement creates a host of fresh opportunities, including the simultaneous remote surveillance of multiple locations.
Accurate Image Fragmentation
Small area detectors, high-resolution fingerprint sensors, and neural networks all worked together to make significant advancements in the accuracy of validating fingerprints, even with minute fragments. The prospective uses of this technology are far more varied, even if it is crucial for gaining insight into criminal investigations. It functions with both fingerprint sensors and tiny sensors in cell phones and biometric credit cards. Identification systems for credit cards can use a small portion of a fingerprint to validate the cardholder and won't even require a battery because the device is powered by a tiny current at a point-of-sale terminal. Overall, the banking industry will benefit from the use of biometric fingerprints to assist in stopping financial and credit card fraud.
Multi-Factor Authentication
With the exponential increase in cyberattacks, IT specialists are implementing multi-factor authentication (MFA) for user logins to strengthen their security infrastructure. With the use of multiple authentication factors, where a user must furnish confidential login information, MFA techniques add an extra layer of protection. Typically, these components are something the user is (such as a USB key or phone token), something they have (such as a code), or something they have (biometric identity). As single-factor authentication and easily cracked passwords become less popular, biometric technology is becoming the most desired component. As MFA has frequently been used to safeguard extremely sensitive information, such as main email accounts, financial accounts, and health records, as the desire for improving privacy and limiting permissions spreads throughout all areas, MFA is more widely employed.
Improving Accuracy of Security Protocols
Despite its rapid development, there are still some areas where biometrics cannot reliably produce results, such as when using children’s faces and fingerprints. It is more challenging for algorithms to accurately recognise the nuances of tiny fingerprints. Today, several developing technologies concentrate on these particular use cases and work on accurate identification, which is a very useful tool in the battle against child abuse and trafficking situations.
Streamlined Biometrics
New methods of identity detection and recent developments in edge computing both aid in the development of fresh ideas for seamless identification. New algorithms, for instance, can recognise a person approaching a turnstile, provide entrance (if it's a legitimate entry), summon an elevator to the right floor, and only open the offices the identified person will use. At the top of the list for this technology are establishments like airports. It is possible to travel through airports more quickly and improve overall security by detecting and identifying undesirable people (such as known criminals) and utilising other security technologies. Still, there are other use cases. Biometrics can be used in hospitals to identify unconscious patients, alert medical staff of allergies, or reveal a patient's insurance status.
