Arizona State University


Visible to the public CAREER: Building Energy-Efficient IoT Frameworks - A Data-Driven & Hardware-Friendly Approach Tailored for Wearable Applications

Sensor energy efficiency is the top critical concern that hinders long-term monitoring in energy-constrained Internet-of-things (IoT) applications. Conventional compressive sensing techniques fail to achieve satisfactory performance in IoT and especially wearable applications due to the lack of prior knowledge about signal models and the overlook of individual variability. The research goal of this CAREER plan is to develop a data-driven and hardware-friendly IoT framework to fundamentally address the unmet energy efficiency need of IoT and especially wearable applications.


Visible to the public A Cyber-Physical System for PV Monitoring and Control Cloud Movement and Shading Prediction

In this paper, we describe a Cyber-Physical system approach to Photovoltaic (PV) array control. A machine learning and computer vision framework is proposed for improving the reliability of utility scale PV arrays by leveraging video analysis of local skyline imagery, customized machine learning methods for fault detection, and monitoring devices that sense data and actuate at each individual panel. Our approach promises to improve efficiency in renewable energy systems using cyber-enabled sensory analysis and fusion.


Visible to the public Synergy: Collaborative Research: Collaborative Vehicular Systems

As self-driving cars are being introduced into road networks, the overall safety and efficiency of the resulting traffic system must be established and it must be guaranteed. This project develops methods to analyze and coordinate networks of fully and partially self-driving vehicles that interact with conventional human-driven vehicles on road grids. The outcomes of the research add to the understanding of more general systems with reconfigurable hierarchical structures and they help create designs with minimal computation and communication delay.


Visible to the public CAREER: Robustness Guided Testing and Verification for Cyber-Physical Systems

This project develops a theoretical framework as well as software tools to support testing and verification of a Cyber-Physical System (CPS) within a Model-Based Design (MBD) process. The theoretical bases of the framework are stochastic optimization methods, and robustness notions of formal specification languages.


Visible to the public SMARTER -Smart Manager for Adaptive and Real-Time decisions in building clustERs


Despite the current emphasis on developing green buildings, the global energy consumption issue is not being adequately addressed. In this project, we propose a new perspective on this ever-threatening issue: NetZero energy building clusters.