Author ORCID Identifier

Danny Scott https://orcid.org/0000-0002-5042-283X

Matthew Bringle https://orcid.org/0000-0003-1457-8519

Imran Fahad https://orcid.org/0009-0006-3734-3535

Gaddiel Morales https://orcid.org/0009-0002-7263-3176

Azizul Zahid https://orcid.org/0009-0008-0981-5798

Sai Swaminathan https://orcid.org/0009-0009-5055-2632

Document Type

Article

Publication Date

9-2024

DOI

https://doi.org/10.1145/3678529

Abstract

In this research, we introduce NeuroCamTags, a battery-free platform designed to detect a range of rich human interactions and activities in entire rooms and floors without the need for batteries. The NeuroCamTag system comprises low-cost tags that harvest ambient light energy and utilize high-frequency modulation of light-emitting diodes (LEDs) for wireless communication. These visual signals are captured by an available neuromorphic camera, which boasts temporal resolution and frame rates an order of magnitude higher than those of conventional cameras. We present an event processing pipeline that allows simultaneous localization and identification of multiple unique tags. NeuroCamTags offer a wide range of functionalities, providing battery-free wireless sensing for various physical stimuli, including changes in temperature, contact, button presses, key presses, and even sound cues. Our empirical evaluations demonstrate impressive accuracy at long ranges up to 200 feet. In addition to these findings, we consider a range of applications such as battery-free input devices, tracking of human movement, and long-range detection of human activities in various environments such as kitchens, workshops, etc. By reducing reliance on batteries, NeuroCamTags promotes eco-friendliness and opens doors to exciting possibilities in smart environment technology.

Download
Files over 3MB may be slow to open. For best results, right-click and select "save as..."

Share

COinS