SCC-IRG Track 2: Transportation Gaps and Disability-Related Unemployment: Smarter Cities and Wearables combating Commuting Challenges for the Visually Impaired

几个世纪以来，视力丧失和缺乏运动之间的病理联系一直困扰着医生、科学家、工程师和患者。流动性的丧失是非常多变的，不仅与生活质量的重大妥协有关，而且还与糟糕的失业率有关。在城市地区，与流动性丧失有关的一个巨大的就业障碍是在日常通勤中使用公共交通工具的持续斗争。虽然数据科学和人工智能的技术进步继续迅速催生新的数字工具和电子解决方案，但这些新设备中的许多都是不完整的答案，让最终用户在设备切换和任务完成之间认知上不知所措。该项目将支持研究低视力行为所需的基础研究，并开发更强大的可穿戴设备，可以处理数据密集型处理，实现并行功能。该项目将提供革命性的可穿戴平台VIS4ION，该平台使用背包式传感器、先进的机器视觉、无线通信和人机界面，能够在复杂的城市环境中为视障人士执行“连接”动态定位和导航辅助。该项目将为低视力人群带来更健康的就业机会，为残疾研究提供行为调查框架，为以导航为重点的可穿戴设备的设计和交付提供指导，为精通多学科和残疾研究的学生提供指导，并为智能和互联社区提供蓝图，以增强经济活力、安全、保障、健康和福祉以及整体生活质量。这项研究将通过科学和工程的创新，在视障居民和周围环境之间建立新的联系，以应对阻碍就业的通勤挑战。该项目设想在新的行为研究、优化数据流、增强电源管理和城市-机构合作方面进行基础研究，以填补一些知识空白，包括：(1)缺乏对用户需求和行为模式的科学原则、基于实验的理解；(2)通过计算机视觉算法解释现实世界场景的能力有限，计算负担过重；(3)对平衡本地与云分析和有效管理电力的技术方法的理解不完整；(4)缺乏具有生态有效性的假设驱动研究，可以扩大规模以解决通勤挑战。一项融合研究计划将填补这些空白，并在计算机视觉、机器学习、视频压缩、无线传输、人为因素和空间定位方面取得关键进展。通过量化用户在交通方面的需求并随后提高视障旅行者的安全状况，将改善有酬就业，并对减轻健康和经济负担产生次要影响。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 pathologic link between vision loss and physical inactivity has confounded doctors, scientists, engineers, and patients for centuries. Mobility losses are extremely variable and not only tied to significant compromises in quality of life, but also to an abysmal unemployment rate. One massive employment barrier related to mobility loss in urban areas is the ongoing struggle to utilize public transportation during daily commuting. While technological advances in data science and artificial intelligence continue to rapidly spawn new digital tools and electronic solutions, many of these new devices are incomplete answers that leave end users cognitively overwhelmed between device switching and task completion. This project will support foundational research needed to study low-vision behavior and develop more powerful wearables that can handle data-intensive processing, enabling parallel functionality. The project will afford VIS4ION, a revolutionary wearable platform that uses backpack-mounted sensors, advanced machine vision, wireless communications, and human-machine interfaces, the ability to perform ‘connected’ dynamic localization and navigation assistance for the visually impaired in complex urban environments. The project will lead to a healthier low vision population with more gainful employment, a framework for behavioral investigation in disability studies, guidelines for the design and delivery of navigation-focused wearables, students who are well-versed in multi-disciplinary and disability-focused research, and a blueprint for a smart and connected community that enhances economic vitality, safety, security, health and wellbeing, and overall quality of life.This research will respond to the commuting challenges that stymie employment by creating new connections between visually impaired residents and their surrounding environment through innovations in science and engineering. The project envisions fundamental research in novel behavioral studies, optimized data streams, enhanced power management, and city-agency cooperation to fill a number of knowledge gaps, including (1) lack of a scientifically-principled, experimentally-based understanding of users’ needs and behavioral patterns, (2) limited ability to interpret real-world scenes through computer vision algorithms and excessive computational burden, (3) incomplete understanding of technical methods to balance local versus cloud analytics and manage power effectively, and (4) lack of hypothesis-driven studies with ecological validity that could scale-up to solve commuting challenges. A convergent research plan will fill these gaps and contribute key advancements in computer vision, machine learning, video compression, wireless transmission, human factors, and spatial positioning. By quantifying user needs regarding transportation and subsequently enhancing the safety profile of visually impaired travelers, gainful employment will improve, with secondary impacts on reducing health and economic burden.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.