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Reduce Cost Smart Power Management System by Utilize Single Board Computer Artificial Neural Networks for Smart Systems

机译：通过利用单板计算机人工神经网络进行智能系统来降低成本智能电源管理系统

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The plan and usage of a smart power management system for household and buildings that control numerous electrical appliances in real time have been reported in this work. The system is based on using artificial intelligence with low-cost single board computer in order to design a smart power management system that can analyzed some aspects that can serve power management aspects such as, electricity consumption to reduce power consumption to lower limits as possible, temperature to control, and human activity to control lighting and power on/off some devises like TV. A Raspberry PI 3 version B has been utilized as a computer unit, in a fast and accurate way to control, for example, switching lighting/TV when human in or left the area. The system utilized some devises in that purpose that includes, a Raspberry Pi camera to streamed real-time video for detection the existence of human and his activity, an ultrasonic sensor to compute distance of human in area, temperature sensor to detect room temperature in home or buildings in order to control air conditioning systems and odor/gas sensors to control ventilation systems, power sensor to compute electricity consumption. The proposed system is programmed by a used Python programming language that manages all aspect at the same time. The recognition part is based on utilized conversational neural network (CNN) that optimized by used saliency object detection so as to improve the CNN in acknowledgment exactness and acknowledgment speed. The outcomes endorsed that the proposed system can manage the power in smooth and accurate that can serve both electrical consumption and lifestyle where all operation run in fast and automated way, furthermore, the recognition algorithm success in detect objects and isolate it from background with 100% accuracy and in fast time reach to 0.7 seconds.
机译：在这项工作中报道了家用和建筑物的智能电力管理系统的计划和用法，在这项工作中报告了实时控制众多电器的建筑物。该系统基于使用低成本单板计算机的人工智能，以设计智能电源管理系统，可以分析可以为电源管理方面的一些方面进行分析，例如，电力消耗降低功耗以降低限制，温度控制，人类活动控制照明和电源打开/关闭一些设计。覆盆子PI 3版B已被用作计算机单元，以快速准确的方式来控制，例如，当人类进入或离开该区域时切换照明/电视。该系统利用了一些设计，该目的包括覆盆子PI相机，用于流式传输实时视频以检测人类和他的活动的存在，超声波传感器，以计算区域的距离，温度传感器在家中检测室温。或建筑物为了控制空调系统和气味/气体传感器来控制通风系统，功率传感器来计算电力消耗。所提出的系统由二手Python编程语言编程，该语言同时管理所有方面。识别部分基于利用的对话神经网络（CNN），其通过使用的显着性对象检测优化，以便在确认精确度和确认速度中改善CNN。结果核准了所提出的系统可以以平稳和准确的方式管理电力，可以为电气消耗和生活方式提供服务，其中所有操作以快速和自动化的方式运行，此外，识别算法在检测对象中的识别算法成功并将其与100％的背景隔离准确性，快速时间达到0.7秒。

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