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Welcome to the Multimedia Networking and Computing Laboratory

Welcome to the Multimedia Networking and Computing Laboratory
Lab Members Fall 2017 WSN Lab Members 2016 IOT Research Discussion UAV Body Sensors

Welcome to Multimedia Networking & Computing Lab!

The Multimedia Networking and Computing (MNC) Laboratory at University of Cincinnati was founded by Dr. Rui (April) Dai in Fall 2014. Our group conducts research in multimedia networking, wireless sensor networks, sensor systems for healthcare applications, future Internet paradigms, and cyber-physical systems. We are particularly interested in multimedia networking and computing solutions for next-generation wireless network architectures. Our research findings have been published in prestigious journals and conferences such as IEEE Transactions on Multimedia, IEEE Multimedia, SPIE Journal of Electronic Imaging, INFOCOM, GLOBECOM, ICC, ISM, and ICIP.

Featured Research

QoE-based Video Communication 

Recent advances in imaging hardware and wireless communications have fostered the deployment of QoE_Provision embedded camera sensors in various wireless imaging applications, such as surveillance, intelligent transportation, remote health care, and consumer electronics and entertainment. We are exploring new communication solutions to provide satisfactory quality of experience (QoE) to users of wireless imaging applications using the minimum energy and bandwidth resources in wireless camera networks. We are investigating mechanisms that can efficiently predict the perceptual quality of networked videos as evaluated by human users. Based on the properties of perceptual quality, we are designing new communication protocols to effectively control QoE in dynamic network environments.

Information-Driven Video Communication for Public Safety

Video surveillance systems have been used heavily in public safety for remote monitoring and variousPublic Safety applications aiming at improving first responders’ situational awareness. Wireless surveillance cameras lower the deployment cost than wired solutions, enables mobility, and offers more rapid deployment in temporary venues such as disaster scenes and sports events. We will design an information-driven video communication framework for wireless-networked video surveillance systems in public safety. The overall goal is to maximize the information that human operators could gain from surveillance videos with the help of automatic video analysis.

Intelligent Mobile Surveillance using UAVs 

The advent of small drones/Unmanned Aerial Vehicles (UAVs) equipped with remote visual sensingMobile_UAV capabilities have played crucial roles in many surveillance applications such as border patrol, disaster response and rescuing, crowd control, traffic monitoring, and wildfire surveillance. The overall objective of this research is to establish and demonstrate intelligent mobile surveillance systems through swarming UAVs that significantly augment existing ground surveillance systems by providing enhanced sensing quality, short response time, and intelligent decisions to users.

Recent News:

  • Dr. Dai serves as an advisor for the Women in Science and Engineering (WISE) Research Experiences for Women Undergraduates (REWU) program in Summer 2017. Jingyi Zhu, an undergraduate in the Joint Co-op Institute program with Chongqing University, has co-authored two conference papers with MNC Lab members through the WISE program.

  • Dr. Dai gives a seminar entitled “Multimedia Sensor Systems: Theories and Applications in Healthcare” in the Biomedical Informatics Hutton Lecture Series at Cincinnati Children’s, March 2017.

  • PhD student Lingchao Kong presents his paper in the Best Paper Session of IEEE International Symposium on Multimedia (ISM) in December 2016. The paper entitled “Temporal-Fluctuation-Reduced Video Encoding for Object Detection in Wireless Surveillance Systems” is coauthored by Lingchao Kong and Dr. Dai.

  • Kevon Scott defends his MS thesis entitled “Occlusion-Aware Sensing and Communication in Unmanned Aerial Vehicle (UAV) Networks” on November 10, 2016.