Publication Date


Document Type


Committee Members

Yong Pei, Ph.D. (Committee Co-Chair); Nia S. Peters, Ph.D. (Committee Co-Chair); Mateen M. Rizki, Ph.D. (Committee Member)

Degree Name

Master of Science (MS)


Real-time distributed systems constitute computing nodes that are connected by a network and coordinate with one another to accomplish a cooperative task, combining the responsiveness, fault-tolerance and geographic independence to support time-constrained collaborative applications, including distributed Human-Machine Teaming. In this thesis research the viability of real-time distributed collaborative technologies is demonstrated through the design, development and validation of prototype systems that support two human-machine teaming scenarios namely, ACE-IMS (Affirmation Cue based Interruption Management Systems) and ReadMI (Real-time Assessment of Dialogue in Motivational Interview). ACE-IMS demonstrates how a combination of AI capabilities and the cloud and mobile computing infrastructure can be leveraged to extend and improve human-machine collaboration through intelligent interruption dissemination to reduce the potential disruptiveness to the human, while ReadMI demonstrates how AI based technologies like Automatic Speech Recognition and classification algorithms can be augmented into a real-time video conferencing system to enhance user interaction and leverage the computation and decision making capabilities of computers to improve provider fidelity of Motivational Interviewing skills among healthcare professionals.

Page Count


Department or Program

Department of Computer Science and Engineering

Year Degree Awarded


Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.