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User Activity Recognition for Energy Saving in Smart Home Environment

机译:智能家居环境中节能的用户活动识别

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In recent years, the consumption of electricity has increased considerably in the industrial, commercial and residential sectors. This has prompted a branch of research which attempts to overcome this problem by applying different information and communication technologies, turning houses and buildings into smart environments. In this paper, we propose and design an energy saving technique based on the relationship between the user's activities and electrical appliances in smart home environments. The proposed method utilizes machine learning techniques to automatically recognize the user's activities, and then a ranking algorithm is applied to relate activities and existing home appliances. Finally, the system gives recommendations to the user whenever it detects a waste of energy. Tests on a real database show that the proposed method can to save up to 35% of electricity in a smart home.
机译:近年来,工业,商业和住宅区的电力消耗增加了很大。这促使了一项研究的分支,试图通过将不同的信息和通信技术,将房屋和建筑物应用于智能环境来克服这一问题。在本文中,我们提出了基于用户活动与智能家庭环境中的电器之间的关系的节能技术。该方法利用机器学习技术来自动识别用户的活动,然后应用排名算法来涉及活动和现有家用电器。最后,每当检测到能量浪费时,系统向用户提出建议。在真实数据库上测试表明,该方法可以在智能家中节省高达35%的电力。

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