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.
A Coupled CH4, CO and CO2 Simulation for Improved Chemical Source Mode by Beata Bukosa, Jenny A Fisher et al
uow.edu.au - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from uow.edu.au Daily Mail and Mail on Sunday newspapers.
Delhi CM Arvind Kejriwal write to PM Narendra Modi, give suggestion for Corona Vaccine | Arvind Kejriwal ने पीएम मोदी लिखी चिट्ठी, Corona Vaccine को लेकर दिया ये बड़ा सुझाव
india.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from india.com Daily Mail and Mail on Sunday newspapers.