The potential of energy harvesting and batteryless sensing promises a future where IoT devices will become sustainable, long-lasting, and maintenance free. Given the significant challenges involved with building and programming such devices, it is reasonable to question whether energy harvesting based IoT can replace existing wearables (fitness trackers, smartwatches, or medical devices), while providing a reliable user experience. Hence, an important question arises: “What role can energy harvesting based sensing play in the age of AI and deep learning?” While energy harvesting based sensors can unlock new applications in wearables and personalized data analytics, the path towards integrating them into the modern deep learning landscape requires substantial intellectual innovation. This workshop aims to bridge multiple perspectives in wearable sensing and data analytics in the modern age of AI.

We invite prospective authors to submit extended abstracts (2 pages) covering existing or new research (or position papers) related to AI for energy harvesting devices and systems. Accepted papers will be presented via brief presentations during the workshop. Topics of interest include, but are not limited to:

-AI and algorithms (e.g. deep learning architectures) for energy harvesting

-AI applications with energy harvesting-based wearables

-Energy harvesting-based wearables (e.g. new devices or case studies)

-Batteryless devices

-Efficient sensing and communication

-Energy neutral operation

-Systems/networks of energy harvesting sensors

-Multimodal and new energy harvesting modalities

-Simulation tools and frameworks for energy harvesting

-Datasets for energy harvesting based wearables

Submission Guidelines

-The submitted abstracts (short papers) should be 2 pages long.

-Authors should use the IEEE template for the submission.

Contact

Geffen Cooper: geffen@utexas.edu

Ganapati Bhat: ganapati.bhat@wsu.edu