I-Corps: Novel Biometric Authentication Using a Smart Device

I-Corps项目更广泛的影响/商业潜力是开发基于个人安全生物识别的访问技术。拟议的商业市场是汽车和设备访问，而拟议的技术解决了丢失车钥匙的问题，以及丢失或被盗手机被错误的人访问的问题。目前，美国每年花费27亿美元来更换丢失的物品。手机和车钥匙是最容易丢失的五件物品之一。此外，如果汽车被其他用户使用，汽车可能会被盗，但使用建议的解决方案可以防止汽车被盗。另一个潜在的应用包括建筑访问。身份识别（ID）卡通常用于控制进入建筑物。然而，公司每年要花费数千美元来更换丢失的身份证，使用拟议中的技术可能会减轻这一问题。此外，拟议的非接触式技术可能有助于减少与COVID-19和其他高传染性疾病相关的传播和成本。这个I-Corps项目是基于生物识别认证方法的发展。面部识别和指纹识别已成为生物识别认证市场上流行的方法。该技术是一种基于光电体积脉搏波（PPG）的认证解决方案，使用信号处理和机器学习算法，可以通过智能手机上的集成传感器收集生理数据。它是一种测量数据的非接触式监测方法，不需要额外的硬件来识别用户。目前的生物识别认证解决方案，包括面部识别和物理指纹，需要外部硬件组件，这可能会限制使用，并引起隐私问题，以及需要接触监控，并为制造商带来昂贵的投资。提出的基于生物识别的非接触式身份验证解决方案可以降低成本，保护用户隐私，并消除接触点，以减轻COVID-19和其他疾病的传播。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of an individual security biometric-based access technique. The proposed commercial market is cars and device access while the proposed technology solves the problem of losing a car key, and of having a lost or stolen phone accessed by the wrong person. Currently, $2.7 billion is spent annually in the U.S. replacing lost items. Phones and car keys are in the top five lost items. In addition, cars may be stolen if those items are used by other users, but using the proposed solution car theft may be prevented. Another potential application includes building access. Identification (ID) cards are used commonly to control access to buildings. However, companies spend thousands of dollars each year to replace lost ID cards, which may be mitigated by using the proposed technology. In addition, the proposed touchless technology may be useful to reduce the spread and costs associated with COVID-19 and other highly transmissible diseases. This I-Corps project is based on the development of a biometric authentication method. Facial and fingerprint recognition have become popular methods in the biometric authentication market. The proposed technology is a photoplethysmography (PPG)-based authentication solution using signal processing and machine learning algorithms that can gather physiological data by using integrated sensors on smartphones. It is a touchless monitoring method to measure data and does not require additional hardware to recognize users. Current biometric authentication solutions, including facial recognition and physical fingerprint, require external hardware components that may limit use and raise privacy concerns as well as the need for contact monitoring, and expensive investments for manufacturers. The proposed touchless biometric-based authentication solution may cost less, protect user privacy, and eliminate touch points to mitigate the spread of COVID-19 and other diseases.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.