Network and Innovation Laboratory

The research group at the Network and Innovation Lab focuses on research on communication networking and innovative technologies such as autonomous sensing, unmanned vehicles, and blockchain to solve problems in optimizing the sustainable use of resources.

LAB DIRECTOR

Dr. Ziqian (Cecilia) Dong

Dr. Ziqian (Cecilia) Dong

ACTIVE PROJECTS

Food, Energy, and Water Nexus

This project investigates interconnection amongst food, energy, and water systems in different scales in an urban environment. The team develops visualization tools to help stakeholders in decision-making processes and uses case studies to examine best practice for sustainable urban development. This is an international collaborative project with partners from Stuttgart Technology University of Applied Sciences (HFT), Austrian Institute of Technology (AIT), City University of New York, Landkreis Ludwigsburg, Alpen-Adria Universität Klagenfurt, bw-engineers GmbHthree, and the College of Engineering and Computing Sciences and School of Architecture and Design. It is funded by the Belmont Forum, National Science Foundation grant number 1830718.

Signals in the Soil

This project focuses on the development of a passive, low cost, pervasive, maintenance-free sensor that can be interrogated wirelessly and provide measurement of soil water content, temperature, pH, and nutrient concentration for precision agriculture and environmental monitoring. This is a collaborative project with faculty from the College of Engineering and Computing Sciences and College of Arts and Sciences. It is funded by the National Science Foundation grant number 1841558.

City-as-Lab Research Coordination Network (RCN)

A project to establish a research coordination network to study food, energy, and water nexus for sustainable and resilient urban development. Read the media release.

Geolocation Project

IP geolocation is the process of finding the geographic location of an Internet host that bears a certain IP address. Database based IP geolocation methods have drawbacks of data not being updated and obsolete. Thus resulting in inaccurate or misleading results.

Measurement based IP geolocation is studied to find a fit model for anchor nodes to locate an unknown IP based on RTT measurements. IP geolocation has wide applications such as localized advertising, user location verification to avoid credit fraud. Indoor localization of network devices presents unique challenges for its complex environment induced interferences. We search for novel approaches through ultra wideband systems, machine learning and multilateration of wifi access point signals for accurate localization when GPS is not available.

Selected Publications

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