Facial Recognition
Facial recognition-based biometric clocking does not require contact with any communal surface. Oloid identifies the employees accurately using facial recognition as they approach the tablet running the Oloid app.
Integrated with Turnstiles and Doors
- Clock employees in and out as they enter and exit the building. Increase convenience and accuracy of punches.
Commitment to Responsible AI
Together with ADP Marketplace, our company is committed to the responsible use of AI. When incorporating AI into our product(s), we have agreed to comply with ADP Marketplace’s AI principles focused on human oversight, monitoring, privacy, explainability, transparency, and mitigating bias. Learn more here.
How we use AI
- Oloid leverages artificial intelligence (AI) in several ways to enhance its authentication solutions, focusing on security, user experience, and operational efficiency, including optimizing time and attendance. While specific AI implementations can vary, the core principles applied in authentication technologies and time and attendance management provide a solid understanding of Oloid's approach.
Biometric Authentication for Access Control
- AI-driven biometric authentication is a key feature, using facial recognition for secure and efficient access control. These AI algorithms are trained on large datasets, enabling them to accurately and quickly verify individuals’ identities, thus streamlining access to facilities and systems without compromising security.
AI in Time and Attendance Management
- For time and attendance, AI can optimize workforce management by accurately tracking employee work hours, breaks, and absences through biometric data. This not only reduces the possibility of time theft and buddy punching but also streamlines payroll processing. AI-driven systems can analyze patterns over time to predict staffing needs, identify trends in absenteeism, and even suggest adjustments to staffing levels or individual schedules to improve operational efficiency.
Liveness
- In the sphere of AI-driven authentication, liveness detection is paramount for distinguishing authentic human presence from spoof attempts during biometric verifications. This crucial technology employs two distinct models to ensure the integrity of the authentication process:
- Hardware-Based Liveness Detection: This model utilizes advanced technologies, such as TrueDepth cameras and depth maps, to analyze the physical depth and contours of a subject's face. By assessing the three-dimensional aspects of the face, it can effectively differentiate between a real person and replicas, such as photos, videos, or masks. This method offers a robust barrier against spoofing attempts, leveraging the precise capabilities of specialized hardware to detect the unique spatial characteristics of live subjects.
- Software-Based Liveness Detection: In contrast, the software model relies on sophisticated AI algorithms that have been trained on a comprehensive dataset of spoof images. It meticulously examines visual artifacts, patterns, and variations in lighting conditions that are indicative of spoofing attempts. This model's strength lies in its ability to identify subtle inconsistencies and anomalies that distinguish genuine human interaction from forgeries, without the need for specific hardware. The adaptability and accessibility of software-based liveness detection make it an invaluable tool in the fight against increasingly sophisticated spoofing techniques.
Together, these models provide a multifaceted approach to securing authentication systems against fraudulent access attempts, ensuring that only legitimate users are authenticated through biometric verification processes.
User Experience and Efficiency
- In both authentication for access control and time and attendance management, AI enhances user experience by making processes faster and more intuitive. AI algorithms can make intelligent decisions on the user’s intent and when to prompt for additional authentication, how to handle recurrent and routine access requests, and even automate time and attendance tasks to reduce administrative overhead.
Best Shot Detection and Intent
- In the context of Oloid's use for time and attendance systems, AI significantly elevates the efficiency and accuracy of capturing employee attendance and activity, incorporating technologies like "Best Shot Detection" and understanding "Intent" to ensure seamless and accurate user identification. Within this framework:
- Best Shot Detection: Leveraging AI, Oloid's system analyzes multiple biometric data points in rapid succession to identify the most accurate and clear representation of an individual during the check-in or check-out process. This could involve facial recognition where the AI assesses factors such as lighting, angle, and clarity to choose the best image for authentication, ensuring a quick and seamless verification process. This capability is crucial in dynamic environments where conditions can vary widely, ensuring the system consistently captures and recognizes individuals accurately for attendance purposes.
- Intent Understanding: In time and attendance systems, understanding the user's intent involves AI discerning the context of an authentication attempt to optimize its response. For example, the system might recognize an employee's approach towards a time clock and preemptively prepare to authenticate, thereby reducing wait times and enhancing user experience. Similarly, by analyzing patterns of individual interactions with the system over time, the AI can adapt its recognition process to become more efficient and user-friendly, anticipating common issues or errors before they happen.
If you have questions about how Oloid uses AI, please contact us.
Easy Onboarding
Onboarding users on the Oloid platform is as easy as taking a selfie. Employees or contractors can be registered easily by clicking pictures on the iPad or by exporting selfies from personal devices or HR systems. It's fast and easy.
Robust Data Privacy
Oloid offers a sophisticated infrastructure to secure and protect employee data. Facial images are converted and stored as an encrypted numerical code, which helps ensure the security and privacy of the biometric data.
PPE Mask Detection
Oloid uses computer vision to detect the presence of PPE masks. Reduce manual effort by reducing reliance on manual screening.
Automating Safety and Compliance
- When enabled, Oloid can detect if the PPE mask is properly worn. If not, it reminds the employees to wear their mask properly
Wellness Attestation
Eliminate manual checks for administering health questionnaires on Oloid and integrate them with the clocking process. The wellness checks can be combined with the status of vaccination records or test results. Oloid helps employers comply with employee safety guidelines and improve employee trust and wellbeing.
Contactless Data Entry with Air Touch & Voice
Employees can fill out the screening questionnaires using their personal devices or by using voice commands or touchless gestures called Air Touch. Help keep your team members stay safe with a contactless system and save on costs and time.
