Research

The twenty-first century is an urban living century. It is predicted that by 2050 about 64% of the developing world and 86% of the developed world will be urbanized. Almost everyone will inevitably face and get involved in this rapid urbanization. Urbanization brings us both unprecedented challenges and wonderful opportunities. New technologies are making urbanization easy to manage as they create platforms and systems that make everyday lives of inhabitants easy. For example, today, the Internet of everything and Internet of people are making it easier to manage and provide urban services through smart real-time data-driven management of urban systems. Urban communities can take advantage of smart technologies that are utilizing the rapidly growing real time urban generated data to improve the quality of life of the citizens for the betterment of society. Chattanooga is a growing mid-sized city with a proud tradition of public-private partnerships that drive innovation and sustainable economic growth and development. The city has carefully and smartly used its unique location and its resources to build the first 10Gbps fiber optic internet service through the Electric Power Board (EPB) of Chattanooga to 80,000 householders and businesses. This has led it to be called the GigCity because it is the first city in the Western Hemisphere to acquire such city-wide fast internet service. Chattanooga is uniquely positioned to be the next generation testbed for smart cities.  We have been working collaboratively with the City of Chattanooga, Chattanooga Department of Transportation, EPB of Chattanooga, and The Enterprise Center in to develop, deploy, and publish innovative practices for the smart city of Chattanooga.

Our main focuses are on Transportation, Energy, and Health.

 

 

Transportation

 

Energy

 

Health

 

Energy-Efficient Data Acquisition in Wireless Sensor Networks Using Compressive Sensing

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We studied the problem of data acquisition in wireless sensor networks (WSNs). A recently revitalized technique called compressive sensing (CS) has presented a new method to capture sparse signals at a rate below Nyquist. There are drawbacks to directly applying the existing CS algorithm to WSNs, which are mainly due to the fact that CS requires a large number of inter-communications for generating each projection. 

 

 

An Energy-Efficient and Rate-Optimal Multicast Protocol for Wireless Networks 

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In wireless networks, multicast is an elementary service that is used in many applications. We proposed a new algorithm for constructing a multicast subgraph and a distributed source coding-based Multicast (DSCM) protocol for multihop wireless networks with emphasis on reliability, rate optimality, and energy efficiency. 

 

Distributed Source Coding using Finite-Length Rate-Compatible LDPC Codes: The Entire Slepian-Wolf Rate Region 

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We proposed a technique to reduce the transmission power usage in the wireless sensor networks (WSNs) exploting the spatial correlations between sensor readings in a network. Each node compresses its data without communicating with other nodes and sends the compressed data to the base station. Such a system requires distributed source coding (DSC), since the encoders are distributed and the signals are compressed independently.

 

 

2-D Wavelet Codes for Correcting 2-D Burst Errors

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There are many data transmission and storage systems with two-dimensional (2-D) data structures that suffer from 2-D bursts of error and erasures. 2-D codes can be used to combat such errors and erasures. We introduced two-dimensional wavelet codes (TDWCs).