Learning When to See for Long-term Traffic Data Collection on Power-constrained Devices

no code implementations • 25 Jan 2024 • Ruixuan Zhang, Wenyu Han, Zilin Bian, Kaan Ozbay, Chen Feng

We introduce a novel learning-based framework that strategically decides observation timings for battery-powered devices and reconstructs the full data stream from sparsely sampled observations, resulting in minimal performance loss and a significantly prolonged system lifetime.

Agent-based Simulation Model and Deep Learning Techniques to Evaluate and Predict Transportation Trends around COVID-19

no code implementations • 23 Sep 2020 • Ding Wang, Fan Zuo, Jingqin Gao, Yueshuai He, Zilin Bian, Suzana Duran Bernardes, Chaekuk Na, Jingxing Wang, John Petinos, Kaan Ozbay, Joseph Y. J. Chow, Shri Iyer, Hani Nassif, Xuegang Jeff Ban

The COVID-19 pandemic has affected travel behaviors and transportation system operations, and cities are grappling with what policies can be effective for a phased reopening shaped by social distancing.