This research addresses the intersection of low-power microcontroller technology and binary classification of events in the context of carbon-emission reduction. The study introduces an innovative approach leveraging microcontrollers for real-time event detection in a homogeneous hardware/firmware manner and faced with limited resources. This showcases their efficiency in processing sensor data and reducing power consumption without the need for extensive training sets. Two case studies focusing on landfill CO (Formula presented.) emissions and home energy usage demonstrate the feasibility and effectiveness of this approach. The findings highlight significant power savings achieved by minimizing data transmission during non-event periods (94.8–99.8%), in addition to presenting a sustainable alternative to traditional resource-intensive AI/ML platforms that comparatively draw and produce 20,000 times the amount of power and carbon emissions, respectively.
Xiangcheng Sun of the Rochester Institute of Technology will talk about fluorescent probes for single molecule polymerization imaging and chemical sensing from 3:30-4:30 p.m. on Friday in CHEM 144.
In a paper recently published in the journal Advanced Functional Materials, researchers reviewed the recent developments in 2D van der Waals heterostructure (VDWH)-based chemical sensors, providing an overview of the sensing techniques, challenges, and future opportunities.
Perimeter Chemical Sensing: What is it and Why is it Needed? azosensors.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from azosensors.com Daily Mail and Mail on Sunday newspapers.