Facial Recognition is now almost ubiquitous.

What was once a feature exclusive to science-fiction movies has become part of everyday life: We use facial recognition to activate our phones, identify friends on Facebook, or pass through customs.

In line with the expansion of the market, facial recognition programs are fast advancing in complexity. Since the onset of COVID-19, these software manufacturers have modified their algorithms to include new features, like the ability to recognize mask-wearing faces.

Inevitably, then, businesses are looking to gain from this technology by incorporating facial recognition into enterprise workflows.

What Does Facial Recognition Mean for Businesses?

Biometric algorithms are used in facial recognition to map, analyze, and validate an individual’s identity in a photograph or video. Although each solution (which often uses proprietary AI systems) works differently, we can summarize the process as follows:

• Detection: This phase involves locating an individual’s face within an image input. Each face is contained within a box. Using AI training models, facial recognition algorithms are initially instructed to learn what a face appears like on various data entries.
• Analysis: The next step involves mapping out each face’s key features and characteristics. The gap between the facial features is measured for this purpose. All of these distances are subsequently merged and transformed into a distinctive set of integers, referred to as the faceprint.
• Recognition: This stage involves determining an individual’s identity. In some applications, categorization replaces this step. In such instances, algorithms don’t confirm a person’s identity but instead designate the individual as a member of a distinct category, such as by gender or age.

With this 3-step process in mind, businesses can assess which facial recognition use cases are most suitable for their operations.

Innovative and Useful Application of Facial Recognition for Businesses

Companies can explore the following use cases to identify the ones more relevant to them:

1. Physical authorization

It can eliminate the requirement for special permits, keys, or access codes, allowing anyone to move forward with their business without worrying about security or efficiency. The entrance to any confidential zone will be coded to restrict access only to authorized faceprints.

This has immense applications in government offices, manufacturing plants, aerospace and defense, clinical research centers, and the like. Technology companies can also rely on this method to protect the physical storage locations of their IP.

2. Patient data management

Similar to the above use case, identifying patients correctly and automatically can free up enormous resources. Incorporating it into a healthcare facility’s video surveillance system may streamline patient check-in. This eliminates documentation for hospital staff and patients and prevents human error.

What’s more, facial recognition can help automate hospital admin workflows. A facial recognition system may verify a patient’s identity and insurance details by “looking” at them. This accelerates the admissions process, establishes the groundwork for a more personalized experience, and prohibits fraud.

3. Accounts payable (AP) automation

Did you know that facial recognition could play a role in AP automation? Creating accounts for vendors, adding shipping and invoicing addresses, entering bank information, etc., can be a hassle. Companies typically don’t trust apps to store such sensitive data securely.

With facial recognition, online payments to suppliers can be streamlined. You would only need to scan the recipient’s face to trigger the approval workflow and all your details (approver name, designation, sign-off authority, etc.) would be automatically extracted.

4. Crime prevention and public security

By accessing datasets holding the faceprints of previously identified criminals, law enforcement agencies can be immediately alerted when a known offender is captured on camera, for example, entering a retail store.

Airports, immigration, and border patrols have also adopted facial recognition, employing their cameras to enhance security and expedite the movement of large numbers of individuals. The method is used in a number of ways, including the automatic matching of facial scans with ID cards or passport images and the identification of potential threats.

5. New-age marketing

Face recognition possesses the ability to transform marketing techniques. It can make marketing more intelligent and accurately targeted by assessing a person’s age and gender so as to run ads that are specific to them. Eventually, you will be able to use this technology in the B2B world, where a specific buyer from a specific account receives targeted marketing messages from B2B sellers (provided they decide to opt in for the service).

6. Better hospitality experiences

In the hospitality industry, facial recognition may facilitate improved customer service. By linking the software to a guest’s account, employees are able to provide them with a better, more personalized experience.

Using a photo from their online account, this technology might allow a visitor to check in by simply stepping into a hotel. The individual might also use facial recognition to access their room. This could possibly free up the concierge service to better serve their visitors with personalized recommendations, rewards, and specialized offerings.

7. Epidemic/pandemic management

Since the pandemic, facial recognition technologies have been deployed in a new use case: tracking COVID-positive individuals who must stay at home. An app with facial recognition capabilities requests a quarantining individual to take a selfie. The algorithm then verifies their identity to ensure conformity with the self-isolation rules.

This facial recognition application was implemented in South Korea and can be adopted by enterprises looking to prevent employees known to have an infectious disease from entering the premises.

8. Employee mental health

Facial recognition enables the monitoring of mental health trends and employee behavior. For instance, the software may detect an employee’s emotional state based on their facial expressions and provide useful suggestions.

Researchers at Stanford University have created a facial recognition system that operates on Google Glasses. It analyzes facial expressions and offers the wearer suitable prompts, such as ‘anxious’ or ‘glad.’Innovations like this could inspire more open conversations around employee wellness by making the wearer more aware and mindful.

9. Customer loyalty programs

Facial recognition might help in finding and interacting with high-lifetime value customers. It could assist retailers in rewarding loyal consumers without disrupting the shopping experience through integration with CCTV cameras.

As soon as a loyalty club member walks into the store, the facial recognition system labels them. The CRM then provides them with a personalized discount or notifies them of offers or products they may be interested in.

10. L&D engagement

In addition to identifying and categorizing facial attributes, facial recognition systems may decipher a broad range of emotions. This can play a major role when engaging employees in learning & development initiatives.

Analyzing the learners’ facial microexpressions, like raised eyebrows or constricted pupils, may help identify various emotions, like tedium, bewilderment, elation, exasperation, and surprise. This is beneficial for HR departments and L&D designers.

For instance, when holding a workshop, a trainer may assess the mental/emotional state of the participants and figure out which portions of the session stimulate or diminish their interest.

As organizations gain additional knowledge about learner engagement, they may modify the learning process. This will accurately represent employee preferences while offering a more customized learning pathway.

In Conclusion: Implementing Facial Recognition

When creating a facial recognition system customized for your specific requirements, evaluating widely deployed use cases with identical characteristics is a good idea. For instance, if you’d like to try out facial recognition for staff and guest access control, you may gain insights from similar initiatives in other organizations.

Obviously, this is more challenging with a new use case. First of all, you’ll need to identify and evaluate all the variables and factors. Among the most essential considerations are the following:

• The surrounding environment: Will equipment and cameras be located inside, outdoors, or as a combination of both? Lighting also plays a significant role in determining the precision of facial detection and recognition.
• Device connectivity: How will all the devices be connected and deployed? For cloud deployments, a dependable Internet connection is essential. Multiple devices may be needed in edge deployments to connect with one another.
• Device density: Do you require one or multiple devices at a particular entry point? Assess their functions before choosing your facial recognition equipment, as some devices are preferable for more specific applications.

After answering these questions, you should have a better grasp of the magnitude and breadth of facial recognition as a breakthrough technology – and find a solution that best fits your requirements.

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