Machine Learning Ideas for Sensor Networks

#AI #ML #sensor #networks #IoT #optimization #efficiency #communications #networking #futurenetworks #ieee

Special Presentation by Dr. Ayush Dwivedi (Tampere U., Finland)

Hosted by the Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group

Date/Time: Thursday, December 19^th, 2024 @ 12:00 UTC

Topic:

Machine Learning Ideas for Sensor Networks

Abstract:

This talk explores the application of machine learning (ML) techniques to address the challenges in scaling sensor networks while maintaining accuracy and energy efficiency. First, we discuss ML-based approaches to optimize data transmission, significantly reducing communication overhead and extending battery lifetimes. Second, we examine the impact of such optimizations on enhancing overall network capacity. Finally, the role of ML in sensor calibration is analyzed, highlighting its potential to improve accuracy and scalability.

Speaker:

Dr. Ayush Dwivedi a postdoctoral research scholar at Tampere University, Finland, with a PhD from the International Institute of Information Technology, Hyderabad, India. His research focuses on next-generation wireless communication, including non-terrestrial networks, stochastic geometry, satellite-based IoT, and sensor networks for smart cities. He has been an active member of the IEEE INGR Satellite Working Group for several years, contributing to ideas on satellite-based sensor networks.