Project Description

Current research on intelligent transportation mainly focus on utilization of Vehicle-to-Vehicle (V2V) and Vehicle-to-GPS (V2G) communication, which are able to provide real-time information including traffic delays and route guidance. However, much critical information such as the road surface and traffic conditions are not able to be communicated via these methods. To further enhance the safety and intelligence of transportation systems we plan to introduce low-cost self-powered sensor nodes embedded in the pavement either during or after construction, which provide measurements on detailed road surface conditions (e.g. potholes, water retention, snow etc.) and traffic behaviors at the first level. This program aims to develop a multi-scale sensing methodology from an integration of self-powered sensors, distributed optimizations, and Artificial Intelligence (AI)/Machine Learning to enable autonomous sensing of roadway infrastructure for smart cities and highways. The proposed research will focus on sustainability by introducing low-cost self-powered sensors, connectivity by enabling communications among sensors; edge-devices, base-towers, vehicles and drones, scalability by developing distributed algorithms for coordination and optimizations, and intelligence by employing existing AI techniques. Both theoretical results and experimental demos will be achieved from collaborations through faculty from distinctive research areas.

Start Date

June 2020

Postdoc Qualifications 

A highly motivated individual with research background in piezoelectric sensor development, signal processing, and/or skillsets in developing deep learning method using python based language.

Co-advisors 

Prof. Luna Lu
Lyles School of Civil Engineering and School of Materials Engineering 

Prof. Guang Lin
School of Mechanical Engineering and Department of Mathematics

References 

E. Ghahafi, N. Lu., "Self-polarized electronspun polyvinylidene fluoride nanofiber for sensing applications," Composites Part B, 160 (2019) 1-9. 

YF. Su, G. Han, AG. Amran, T. Nantung, and N. Lu, “Instantaneous Sensing of the Early Age Properties of Cementitious Materials using PZT-based Electromechanical Impedance (EMI) Technique”. Construction and Building Materials, 225, 340-347, 2019.

YF. Su, R. Kotian, and N. Lu. “Energy Harvesting Potential of Bendable Concrete using Polymer Based Piezoelectric Generator”. Composites Part B: Engineering, 153, 124-129, 2018. 

S. Mou, J. Liu, A. S. Morse., "A distributed algorithm for solving a linear algebraic equation," IEEE Transactions on Automatic Control, 60 (2015), 2863-2878.

N. Winovich, K. Ramani, G. Lin, "Fast convolutional encoder-decoder networks with quantified uncertainty for heterogeneous elliptic partial differential equations on varied domains," Journal of Computational Physics, in press, 2019