In this article, Serhii Pospielov, lead software engineer, Exadel, covers some of the key business use cases of facial recognition technology and the common costs associated with adopting it.
Facial recognition might seem like new technology, but this form of biometric screening has been in development since the 1960s. Today, however, advances in the hardware used in facial recognition systems, as well as data processing, storage, artificial intelligence, and automation, have opened new avenues for the use and development of this ground-breaking technology. In this article, we discuss some of the business use cases for this tech, both old and new, and explore the costs of facial recognition technology.
Facial Recognition Use Cases
The original and most often deployed use case of facial recognition technology comes from the world of security. Like fingerprint or retinal scans, facial recognition can be used to restrict access and identify potential security threats. With advances in technology, the use of facial recognition in security has become a booming business, including for organizations like the FBI, who are purported to have over 650 million imagesOpens a new window in their facial recognition database.
Today, however, there are new avenues for facial recognition coming to fruition. One application for this technology is in attendance, whether for schools and universities or in workplaces. For most organizations, attendance requires manual intervention of some form, whether that is on the part of the employee who must manually check-in when they arrive at work, or in schools, on the part of the teacher who needs to call for attendance to ensure every student is present. Facial recognition systems give the opportunity for automation of this previously manual task, allowing employers and teachers to save valuable time and ensure increased attendance accuracy.
Another potential growth market for facial recognition technology is in the field of marketing and personalization. Imagine a scenario where retail stores can have additional data on the products their customers are browsing and spending the most time with. Today, online ecommerce organizations are already able to track that data and use that information to serve up suggested or related products, offer targeted discounts and promotions, and even create bespoke online experiences for specific customers. With facial recognition tech, retail spaces could mimic at least some of this experience, offering real-time discounts or changing electronic displays to appeal to specific customers as they move through the store.
Another potential use case for facial recognition is to help create VIP experiences for key customers. When a customer known to make frequent purchases enters the store, staff could be alerted to their presence and be prepared to create a “VIP experience†for them.
One additional use case for facial recognition comes from the hospitality industry, where this technology could be used to streamline the check-in and check-out processes. For example, when a guest arrives at the hotel, facial recognition could bring up their details and automatically check them in. More simply, the software could automatically bring up their file and information for the hotel employee to create a more personalized and streamlined experience.
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Costs Associated With Facial Recognition
The cost of deploying facial recognition solutions can vary significantly but almost always come from three sources: the development of business logic, integration with facial recognition solutions, and product costs.
For the development of business logic, consider the above use case of an attendance system. Once you have the information on who is present, what do you do with this information? Do you simply store it in a Google Document, or do you create a complex web application with the users’ roles? The business logic varies significantly depending on your use case and requirements and can impact cost greatly.
The next expense is integrating with a facial recognition solution. This cost tends to not vary widely across different solutions but, like the development of business logic, is impacted by your requirements and specific use case. However, when you have your business logic well-planned and developed, the integration with a facial recognition solution can be relatively painless.
The last cost comes from production. This is often a surprise cost for users deploying facial recognition systems; they tend to focus on what they need to spend to get the system up and running but don’t necessarily consider the continued costs of putting the system into production. It can be expensive, so ensuring the system offers a sustainable return on investment is important.
Conclusion
As use cases for facial recognition continue to grow, there is an ever-increasing opportunity to develop and deploy these types of systems. Increased hardware capabilities, as well as artificial intelligence and machine learning solutions are rapidly making facial recognition a real option for many organizations. However, companies need to tread carefully as the costs associated with facial recognition remain relatively high. We are hopeful that in the near future, costs will continue to fall, and combined with ever-increasing technological capabilities, facial recognition will become an increasingly commonplace tech.
In the next article, we’ll dive deeper into facial recognition services and discuss the advantages and disadvantages of these various platforms. Stay tuned!
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