Low Energy Sensor Platform – Leveraging Machine Learning (ML) at the Network Edge

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Low Energy Sensor Platform – Leveraging Machine Learning (ML) – Wednesday, February 21st
Abstract: Applications of embedded AI, specifically ML (Machine Learning) and object classification have been growing exponentially as decision logic moves to the edge. Proven advantages of low energy consumption, low costs, and independent target classification drive this implementation and are transforming smart city management, agriculture, medical, health care, bridge and building structure health management (SHM), and smart logistics just to name a few game-changing applications.
Several specific ML applications will be discussed including a vision ML application applied to logistics, and a remote visual cargo classification smart sensor (currently in production). Challenges of a small vs. large CNN model when improving object identification and accuracy will also be discussed and why ML at the network edge is a game-changer. Finally, we will compare and contrast the AI categories of large language models and the energy-constrained tiny ML sensor models.
The speaker, Joe Jesson, co-founded & was CTO of a General Electric business, Asset Intelligence, a GE business that designed and sold remote IoT sensors for the logistics and energy sectors. Machine learning and LPWAN sensor communication became an integral part of the remote monitoring and management of mobile and remote assets. An ongoing research goal is to reduce the smart energy costs where 100% of the power is generated by energy harvesting techniques. Joe is currently CEO of RF Sigint Group and has over 25+ years of engineering and management experience with Motorola APD, Oak Technology, BP, and General Electric. Master's degree from DePaul University & working on a Ph.D. defense. No need to register, For any questions, email [email protected]
Co-sponsored by: TCNJ IEEE Student Chapter President Samantha Potomic – [email protected]
Room: ARM102, Bldg: Armstrong Engineering Building, The College of New Jersey, Metzger Dr, Ewing, New Jersey, United States, 08618

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