REU Site: Research Experiences for Undergraduates in Smart & Connected Communities

这个本科生（REU）网站的研究经验让学生参与智能互联社区（S CC）的新兴领域的研究，这是智能城市的重要组成部分。通过全国范围的招聘过程，10名本科生将参加为期10周的夏季研究计划，为期三个夏天，在得克萨斯州州立大学主办。在确保妇女、退伍军人和少数民族参与的同时，还特别努力从主要教学的大学和学院招收学生。该项目包括由经验丰富的计算机科学教师指导，技术研讨会和讲习班，学生演示和专业发展机会。这些活动是在一个智力环境中进行的，通过提高他们的技术，沟通和社会技能来发展学生的职业生涯。在这个REU网站的研究部分福尔斯沿着三个主要的推动力，在建设支持S CC发展的下一代信息和通信技术&：（1）智能人与环境交互的模型、机制和工具，以监测和保护智能基础设施免受意外故障和恶意攻击;（2）收集和分析各种数据的新方法，从人类生物信号到活动和众包数据，以促进城市环境中公民的健康和福祉;以及（3）智能交通系统的新型调度和监控方法，可以减少拥堵、提高安全性并减少对城市环境的不利环境影响。通过理论和数值分析、模拟实验以及各种设备、传感器和机器人的真实的实施，对所提出的方法进行了评估。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Research Experience for Undergraduates (REU) Site engages students in research in the emerging area of Smart & Connected Communities (S&CC), the essential building blocks of smart cities. Through a nationwide recruitment process, cohorts of 10 undergraduate students will participate in a 10-week summer research program, for three summers, hosted at Texas State University. Special efforts are made to recruit students from primarily teaching universities and colleges while ensuring the participation of women, veterans, and minorities. The project includes mentoring by experienced computer science faculty members, technical seminars and workshops, student presentations, and professional development opportunities. These activities are carried out in an intellectual environment that develops the students' professional careers through enhancing their technical, communication, and social skills.The research component in this REU Site falls along three main thrusts in building the next generation of information and communication technologies supporting the development of S&CC: (1) models, mechanisms and tools for smart human-environment interactions to monitor and protect smart infrastructure against accidental failures and malicious attacks; (2) new methods for collecting and analyzing various types of data ranging from human biosignals to activity and crowd-sourcing data, to promote health and well-being of citizens in urban settings; and (3) novel scheduling and monitoring methods for intelligent transportation systems that would decrease congestion, promote safety and reduce adverse environmental impacts in urban settings. Evaluation of the proposed methods is done through theoretical and numerical analysis, simulation experiments, and real implementations with various devices, sensors, and robots.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.