Big Data Analytics in IoT-Aided Smart Grid
The concept of a smart grid encompasses a network of intelligent devices managing and controlling the generation, transmission, and distribution components of power systems. Such components can be optimized based on environmental and economic constraints, allowing utilities to engage consumers in power generation at different levels. In this realm, bidirectional power exchange becomes a reality. What makes such grids "smart" is the extensive amount of data exchanged between the active components and the enterprise systems managing them.
This talk explores the crucial role of data exchange in controlling, monitoring, and coordinating the smart equipment within the grid subsystem. It is known that to achieve optimal performance, big data analytics emerge as a necessity, complemented by the application of artificial intelligence and machine learning techniques. Consequently, this talk also uncovers the diverse applications of big data analytics, the Internet of Things (IoT) technology, machine learning, and artificial intelligence in the smart grid, offering insights into the benefits, challenges, impacts, and problems associated with employing such techniques. Moreover, some intriguing approaches to computing and transmitting data will be unraveled.
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- Date: 12 Sep 2023
- Time: 10:00 AM to 11:30 AM
- All times are (UTC-04:00) Eastern Time (US & Canada)
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- Co-sponsored by Power and Energy Systems Research Laboratory
- Starts 27 June 2023 10:00 AM
- Ends 10 September 2023 11:59 PM
- All times are (UTC-04:00) Eastern Time (US & Canada)
- No Admission Charge
Speakers
Dr. Shivanjali Khare
Biography:
Shivanjali Khare is a dedicated Assistant Professor in the Computer Science department, specializing in the development of systems based on learning and the application of cryptography to empower and protect users in this technology-driven era. With a strong passion for research, she constantly strives to explore new areas within computer science that can maximize business, technology, and societal impact. Her expertise lies in teaching courses, such as Artificial Intelligence (AI) and Data Mining, where she aims to impart valuable knowledge and skills to the next generation of computer scientists. Through her teaching, she inspires students to delve into the fascinating world of AI and data analysis, fostering their growth and preparing them for future challenges in the field. Driven by a desire to make a positive impact, she is always eager to collaborate on cutting-edge research projects and explore new avenues that push the boundaries of computer science.
Shivanjali holds a Ph.D. in Computer Science from the University of Louisiana at Lafayette in 2021. Prior to that, she earned her M.S. degree in Computer Science from the same university in 2016. These academic achievements have equipped her with a strong foundation in computer science theory and research methodologies, enabling her to contribute significantly to the advancement of knowledge in her field.