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In this blog, we are discussing some prominent use cases of facial recognition technology across various industries.
Access control is necessary to ensure restricted access to premises or services. Facial recognition can improve access control in many ways. Some of these are the following:
Personnel Facility Secure Access:
Facial recognition technology can help companies to only allow their employees or authorized personnel to the business facilities. It also helps to apply access restrictions within the building for areas where not every person is allowed to enter.
Face recognition technology helps to monitor employees’ activities and implement security effectively especially in rushed places.
Smart locks use a wireless protocol and cryptographic key to allow access. Such smart locks are getting popular for workspaces, homes, devices, etc. to ensure controlled access. These smart locks can be integrated with facial recognition technology to grant access to space or devices only after biometric verification.
Aircraft boarding often turns into a time-taking process with long queues of passengers undergoing boarding pass scans, etc. Airlines are now investing in facial recognition technology for implementing self-boarding.
The technology matches the live face with the saved ID data and allows passengers to board the plane while making the process quite safe and quicker.
Access to Specialized Equipment:
Research facilities, factories, hospitals, etc. have specialized equipment and tools that require restricted access and control usage. Facial recognition technology is more effective in such controlled access and operations than traditional methods of keys, computerized cards, etc.
A contactless face login can monitor access time, duration of use, etc. efficiently.
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Know your Customer (KYC) is a business practice used by financial institutions to understand their customers and the suitability of their relationship with the business. The process involves viewing personal information and documents such as passports, etc. to verify the identity of the user. User information is often cross-referenced from different sources.
As businesses are accessing users’ personal information, the KYC practices are highly regulated so that there is no misuse of the information.
KYC helps businesses in many ways, from preventing fraud practices to implementing access control. Facial recognition can improve KYC procedures by making them more secure and robust.
Moreover, face recognition can transform KYC into an electronic KYC process, where the whole process can be digitized. Customers will be able to access financial services remotely from anywhere but in a more secure way. eKYC system usually goes through the following steps:
- Scan state-issued documents of a user, such as an ID card.
- Capture the user’s face in real-time.
- Facial recognition tech detects face and performs a matching process. Advanced facial technology like liveness detection make sure that users are unable to spoof the face detection and recognition process.
Financial institutions are using a facial recognition solution in the following ways:
For opening a bank account:
Facial recognition helps make the digital verification process more secure. The customer applies for opening a bank account. The clerk takes the user’s photo and government-issued document. The facial recognition technology performs a match and authenticates the originality of the document.
In this way, the customer easily gets passed through an eKYC check at the bank and gets access to the bank services.
For contactless ATM transactions:
Face recognition technology also helps in the implementation of a two-step authentication process when a user wants to withdraw money from an ATM. The ATM captures the user’s face and performs a match with the user’s information in the bank database.
Once the verification is done, users can add a PIN and complete their ATM transactions.
For Insurance policy application:
Identity verification is an important step when a customer wants to open an investment account. After filling out the essential information, the insurance agent makes use of the eKYC process using face recognition technology.
Face recognition-powered biometric verification makes the process way easier to prevent fraud and money laundering practices.
Facial recognition technology is also now being used to effectively diagnose diseases that can cause changes in the appearance of the patient. Research studies have shown that sophisticated facial recognition algorithms based on machine learning give increased accuracy in the diagnosis of Parkinson’s disease and the identification of facial cues for acute illness.
Facial recognition technology is also helping medical researchers in the diagnosis of rare genetic diseases. For example, researchers at National Human Genome Institute Research Institute use facial recognition techniques to detect DiGeorge syndrome which is caused by the lack of the 22nd chromosome in an individual.
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Surveillance systems for ensuring security in corporate and residential areas are quite common today. These security systems comprising CCTV cameras, etc. are recording real-time videos of the covered environments.
However, there is a need for continuous monitoring through security individuals who then manually alert in case of any suspicious activity. This process is heavily dependent on humans and also costly.
Facial recognition technology can make security systems more effective. Such a system can automatically detect human faces and match them with the saved database information. Alerts can be raised automatically in case of any suspicious activity or human intervention.
Such security systems using facial recognition technology can be used in a variety of areas from factories, hospitals, residential buildings, etc. to ensure restricted access to the premises and safety of all.
Facial technology is used in a variety of ways to provide personalized customer service. Businesses can ask their VIP customers to register their photo ID with them.
Whenever such a premium customer visits the brand outlet, they are recognized immediately to provide them with hospitable services.
The previous shopping experience of the customer adds more value. It enables salespeople at retail stores to make personalized recommendations to the customer according to their previous choices.
Facial recognition can also be applied to provide a self-service shopping experience through a contactless payment option to premium loyal customers. A facial recognition system identifies customers’ faces, thereby enabling customers to make payments seamlessly in a retail store. Apple uses such facial recognition technology for its iPhone customers.
Digital advertisements are also gaining popularity. Even anonymous users can make use of facial recognition-powered digital signs. Such marketing tools can make suggestions to customers according to their appearance and mood.
Facial recognition can also help with gathering important data from the environment for elaborate data analysis process. Cameras can be used to study customer behavior in the shopping area.
The customer behavioral data will help answer questions like how customers react to a certain product? What are their expectations regarding the product display?
Businesses can then change their marketing and sales practices according to the collected data insights.
Facial recognition technology finds some major use cases in the law enforcement field. Although there are concerns related to invasive surveillance and false identifications, still facial recognition technology is helpful for local law enforcement in many ways, from identifying thieves to tracking serious criminals involved in human trafficking.
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Moreover, facial recognition usage enables law enforcement individuals to identify people who are unable to do so themselves, like small missing children, senior citizens, people left unconscious in accidents, etc. Police officials can match their biometric data with government databases to get the necessary information.
Similarly, face recognition cameras installed in public places, airports, etc. can be used to locate missing people. Law enforcement agencies have records of such people in their databases.
As soon as they appear on security cameras, they are recognized, and concerned authorities are notified. Such facial recognition technology has helped to locate 3,000 missing people in just 4 days.
Planning to invest in facial recognition technology?
Facial technology is helping make processes for access control, digital marketing, biometric verification, etc. more secure and robust across all industries. Developing facial recognition software using the latest technology is, however, a complex process.
You will need experienced software developers who know facial recognition technology and available development tools thoroughly.
Some common facial recognition algorithms that your software developers should know include AdaBoost algorithm, Local Binary Pattern Histogram (LBPH), FaceNet based on Convolution Neural Network, etc. OpenFace and Kairos API, among others, are good open-source tools for face recognition.
Our bog here discusses how you can develop and integrate facial recognition software in your business process.
If you are still looking for experienced software development partners, DevTeam.Space can help you. Write to us your initial requirements for your facial recognition project via this quick form.
One of our technical managers will get back to you to answer any questions and to connect you with the field-expert software developers who have experience in working with similar technologies.
Top FAQs on facial recognition technology use cases
It helps to recognize faces using technology like artificial intelligence and cognitive learning. Facial recognition technologies use biometrics to map facial features to the image or video data.
There are tools and services available to ease the process of developing facial recognition solutions. One example is of Amazon Rekognition service, which uses machine learning to analyze the image and video data.
Some common facial recognition use cases include assistance in implementing robust access control, biometric identification, security and surveillance systems, etc.