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SPECIAL SEMINAR (teaching) Kriti Bhargava, Research Presentation, "Leveraging sensor-based analytics to improve efficiency of Internet of Things applications"

Event Type
Lecture
Topic
special seminar
Sponsor
Illinois Computer Science
Location
2405 Siebel Center
Date
Feb 19, 2020   11:30 am - 12:30 pm  
Cost
Free
Contact
Candice Steidinger
E-Mail
steidin2@illinois.edu
Views
229

Abstract:
With rapid developments in Information and Communication Technologies along with design of micro-services, Wireless Sensor Networks (WSN) present themselves as a powerful tool for real-time monitoring/surveillance and have been identified as the key enabler of the Internet of Things paradigm. As a result, significant attention has been given to improve the design and capabilities of WSN over the past decade. Conventionally limited to sense and send, certain tasks assigned to these devices, today, are of relatively higher computational intensity (e.g. data fusion) and incorporate some level of intelligence. This talk will discuss the design of an autonomous WSN system capable of integrating, processing and managing data from different sensors to deliver real-time, application-specific services. In particular, the talk will focus on the design of a suite of analytic techniques suitable for sensor-based implementation, development of cooperative frameworks for distributed analysis within WSN, and address the issues relating to flexibility and resource management in WSN. The suitability of research will be presented in the context of Precision Farming and Humanitarian Engineering applications.

 

Biography:
Kriti Bhargava received Bachelor’s (Hons.) and Master’s in Technology (dual degree) in Computer Science from The LNM Institute of Information Technology, India, in 2014, and Ph.D. degree in Computer Science from Waterford Institute of Technology, Ireland, in 2019. Dr. Bhargava is a Research Fellow with the School of Computing, Electronics and Mathematics at Coventry University, UK. Her research interests include edge computing, sensor networks, machine learning and wireless networking. She is particularly interested in the application of concepts of edge computing and machine learning for development of intelligent wireless sensor networks.

 

Faculty Host: Matthew Caesar

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