In just a few short years, the Internet of Things (IoT) has reshaped the way we live. We now encounter internet connected devices in our homes, workplaces and throughout our cities. The proliferation of smart, connected devices however, is just the beginning. These devices can now harness the power of edge computing to bring the benefits of Artificial Intelligence (AI) to the very fabric of our life. We have now arrived in the world of AIoT - the Artificial Intelligence of Things.
AIoT enables connected devices with sufficient processing power to perform important tasks while simultaneously employing machine learning. The result is smarter, more efficient operation, and the potential for greatly enhanced user experiences. Crucially, it also means that facial recognition can now play a much greater role for businesses and consumers across an entire spectrum of industries.
IoT, or the Internet of Things, refers to the smart devices that now proliferate the world we live in. These include digital devices that feature sensors, processing, software, and the ability to communicate with other devices on a network. From refrigerators that can be monitored and controlled via a smartphone, to retail, healthcare, manufacturing, transportation, and the creation of truly Smart Cities, the Internet of Things is reshaping the way we live, work and play.
The potential for a more intelligent world is also accelerated by massive advances in Artificial Intelligence (AI), and the development of an Artificial Intelligence of Things, or AIoT. Adding advanced AI capabilities to the smart devices around us means better efficiency, and the ability for devices and systems to react instantly to changing conditions without human intervention. This is transformational for businesses who can now apply machine learning to the vast quantity of data IoT provides, to make more informed and intelligent decisions in an instant.
There is immense potential for facial recognition and AIoT, especially with edge-based facial recognition solutions. Edge-based facial recognition is embedded in local IoT devices, without the need for cloud processing. Devices like smart locks, mobile phones, point-of-sale (POS) systems, interactive kiosks, and digital signage are just a few examples. By taking advantage of chipset solutions with vastly improved processing power, and AI technology such as AI vision, which essentially allows devices to see, IoT devices can use facial recognition with extreme precision in milliseconds. On top of dramatically speeding up the process, the absence of cloud processing addresses data security issues and results in huge cost savings.
The best edge-based facial recognition AIoT solutions are highly accurate, process images and camera feeds quickly, encrypt data for security purposes, and work across hardware, platforms, and programs. With a clear understanding of the benefits and potential of edge-based AI, device makers have been quick to optimize their technologies for these solutions.
Read more: Building AIoT Devices for Facial Recognition
AIoT is a transformational technology that can be advantageous for many businesses. Let's look at a few of the most common applications for AIoT today.
One of the most common AIoT use cases is access control. Facial recognition can transform access control and monitoring systems for homes, residential complexes, and commercial facilities. The technology enables precise, instantaneous identification of individuals. It then provides contactless access for authorized people or sends instant alerts if block-listed individuals or intruders are detected. Integration of facial recognition in AIoT devices benefits a variety of outlets and technologies, including smart locks on doors or cabinets, mobile devices, and equipment logins.
Facial recognition solutions such as FaceMe TimeClock can streamline clock-in/out processes, reduce errors, eliminate the risk of employees sharing access cards, and monitor for unauthorized entry attempts. Access systems can also use facial recognition to unlock facilities for approved employees during specific work hours.
In short, using biometric face identification to log employee time and attendance means improved accuracy, fewer errors, and better transparency. FaceMe provides identity verification, attendance management, access control, security alerts and AI smart monitoring. With an accuracy rate of 99.81%, businesses can enjoy peace of mind when upgrading to an AIoT access system.
Access and identity verification protects more than facilities. You can also implement facial recognition technology into machinery and specialized equipment usage. By granting access only to designated personnel, there is less risk of unauthorized operation and more security and control. In addition, if a warehouse manager wants to set rules for a machine to be operated only during working hours, they can program the AIoT device with those specific conditions.
Toyota Motor Corporation adopted a vehicle inspection information system that integrates FaceMe to provide high-speed and precise facial recognition to ensure only certified inspectors can inspect finished vehicles. Integrating touchless, highly accurate face authentication improves productivity, without requiring inspectors to remove safety gear and masks.
The integration of FaceMe in such scenarios is made easy with the FaceMe SDK, a cross-platform facial recognition engine that is uniquely positioned to integrate edge-based AI facial recognition into a wide range of IoT and AIoT solutions.
Healthcare facilities that distribute medicine can use smart medicine cabinets that integrate FaceMe facial recognition to ensure only authorized personnel have access. The medicine cabinet is synchronized to the staff schedule to ensure pharmacists are authorized for access at that specific time and day. The integration of facial recognition improves the quality in smart healthcare by providing streamlined, frictionless access to controlled substances.
AIoT is also crucial in the world of retail and digital signage, altering the way we shop and the relationship between retailer and customer.
Modern signage embedded with facial recognition technology, such as FaceMe Smart Retail, can now display rich media content that is curated to keep customers engaged, factoring in gender, age, and even the mood of the person in front of the sign. Below are some of the benefits of integrating facial recognition in retail environments:
Retailers can leverage AIoT devices with facial recognition for data analysis. Devices capture behavior and demographics to determine if customers look confused in certain aisles, or if they are more inclined to smile when viewing certain products. Facial recognition technology can capture these patterns and use AI to perform customer analysis. Retailers can then rearrange their store to produce more positive experiences.
As financial and Fintech industries continue to evolve, we find the integration of AIoT and facial recognition becoming a necessity, not a feature. Facial recognition provides the most accurate, secure, and convenient form of two-factor authentication for opening bank accounts, applying for credit, conducting ATM transactions, mobile banking, insurance purchases, and remote customer service.
Financial service companies have always strived to maintain healthy relationships with customers, but with facial recognition technology it is now possible to electronically Know Your Customer (eKYC). This has resulted in improved online banking security, and an entirely new way to conduct financial transactions. One crucial aspect of this transition is the development and implementation of anti-spoofing technology - an area where FaceMe excels, having passed the stringent independent ISO PAD (Presentation Attack Detection) iBeta Level 2 anti-spoofing tests.
FaceMe’s edge-based facial recognition solution is easy to integrate across a wide range of devices, offering one of the most comprehensive chipsets and OS support. The highly accurate AI engine is ranked one of the best in the NIST Face Recognition Vendor Test (FRVT) with an accuracy rate of 99.81% and a less than 1 million false recognition rate. FaceMe can be deployed across a wide range of scenarios, including security, access control, public safety, smart banking, smart retail, smart city, and home protection.
FaceMe® Platform is an easy-to-use, on-premises facial recognition solution that consists of central services (console), APIs, and system services. The system allows you to develop facial recognition applications for virtually any scenario – including financial services, healthcare, retail, and access control.
Customers can also use FaceMe® SDK, a cross-platform facial recognition engine uniquely positioned to integrate edge-based AI facial recognition into a wide range of IoT and AIoT solutions.
Facial recognition is the future of AIoT technology. It makes AIoT solutions safer, smarter, and more human. However, there are barriers to reaping its full potential. Some of these barriers are physical, such as hardware. Others are social, including privacy and data security concerns.
When considering physical barriers, it is important to remember that there is no one-size-fits-all approach. Businesses have varying needs, as well as budgets, and should look to solutions that will work for them. The best facial recognition solutions can be scaled up or down to suit the specific needs of a business and its use case.
It is also important to ensure physical environments are conducive to facial recognition technology. This means paying attention to factors that can affect accuracy, such as lighting, camera position, and lens cleanliness.
In terms of social barriers, facial recognition has been viewed as a privacy concern. This does not mean the technology should be abandoned. Rather, we need to clarify exactly how facial recognition works and ensure ethical regulations are in place. To help tackle privacy concerns, FaceMe has introduced active facial recognition which requires user consent, for example in the form of a head nod, for identity verification to occur.
For a full overview of facial recognition, how it works and how it can be deployed, remember to read Edge-based Facial Recognition - The Ultimate Guide.