首页|Research from Najran University Reveals New Findings on Machine Learning (Multim odal Framework for Smart Building Occupancy Detection)
Research from Najran University Reveals New Findings on Machine Learning (Multim odal Framework for Smart Building Occupancy Detection)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news reporting originating from N ajran, Saudi Arabia, by NewsRx correspondents, research stated, “Over the years, building appliances have become the major energy consumers to improve indoor ai r quality and occupants’ lifestyles.” Funders for this research include Deanship of Scientific Research At Najran Univ ersity For Funding This Work Under The Distinguished Research Funding Program.The news journalists obtained a quote from the research from Najran University: “The primary energy usage in building sectors, particularly lighting, Heating, V entilation, and Air conditioning (HVAC) equipment, is expected to double in the upcoming years due to inappropriate control operation activities. Recently, seve ral researchers have provided an automated solution to turn HVAC and lighting on when the space is being occupied and off when the space becomes vacant. Previou s studies indicate a lack of publicly accessible datasets for environmental sens ing and suggest developing holistic models that detect buildings’ occupancy. Add itionally, the reliability of their solutions tends to decrease as the occupancy grows in a building. Therefore, this study proposed a machine learning-based fr amework for smart building occupancy detection that considered the lighting para meter in addition to the HVAC parameter used in the existing studies. We employe d a parametric classifier to ensure a strong correlation between the predicting parameters and the occupancy prediction model.”
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