Electricity theft detection issue has drawn lots of attention during last decades. Timely identification of the electricity theft in the power system is crucial for the safety and availability of the system. Although sustainable efforts have been made, the detection task remains challenging and falls short of accuracy and efficiency, especially with the increase of the data size. Recently, convolutional neural network-based methods have achieved better performance in comparison with traditional methods, which employ handcrafted features and shallow-architecture classifiers. In this paper, we present a novel approach for automatic detection by using a multi-scale dense connected convolution neural network (multi-scale DenseNet) in order to capture the long-term and short-term periodic features within the sequential data. We compare the proposed approaches with the classical algorithms, and the experimental results demonstrate that the multiscale DenseNet approach can significantly improve the accuracy of the detection. Moreover, our method is scalable, enabling larger data processing while no handcrafted feature engineering is needed.
Wireless sensor networks (WSN), which consist of randomly deployed tiny sensors, data processing unit, and communicating components, have a wide range of applications, such as industry, agriculture, business, military, and health. Because power supply might be impossible, it is the key problem to find an efficient energy strategy for prolonging network' s lifetime. This article made a detailed introduction for energy management of WSN, analyzing energy strategies used for WSN. Keywords-wireless sensor network (WSN); power-saving strategies; network protocol; energy management 1. Foreword Sensor networks is quite different form traditional wireless networks [1 .Wireless networks like Ad hoc, cellular, Bluetooth, their chief design target is to provide high QoS. Because mobile node can get incessant power supply, node energy can be put in a less important position. But severe energy restriction exists in sensor nodes which is enormous widespread and can not get energy supply. Using node energy efficiently, prolonging network surviving time (life cycle) became chief design objective. This essay will analyzes and explains the primary energy-saving strategy of wireless sensor network. Low power consumption designand hardware structure design Ultra-low power consumption design is a technology which is an integration of hardware and software technology. In wireless sensor node which is composite of micro control unit (MCU) and radio-frequency module, reduce power consumption can save electric power greatly, and simplify electrical source design. 1) Reducing power consumption starts from the selection of MCU, low power consumption MCU should be considered at first.2) Choosing chip with low standby current and steady transceiving current for Radio frequency module. 3) Power source with low output voltage and low consumption power itself. 4) Reducing system operating frequency can lower current consumption effectively. 5) Lowering system operating voltage influences system power consumption. So under the premise of system credibility, make sure that system is in lower operating voltage. 6) Use interrupt to make the processor into deep sleep.As we all know, sleep and power down mode will lower operating current greatly. 7) Dynamic Power Management (DPM)[6]. Whenthere is nothing interesting happened around, some modules are idle, switching to low energy consumption state (sleeping mode). This event-driven energy management is very important to enhancing life cycle of sensor node. 8) DynamicVoltage Scaling (DVS) [6].When calculated load is low, reduce working voltage and frequency of MCU and thereby reduce processing capacity, can reduce power consumption of MCU. 9) Reduce starting time Of Sending and receiving module. Energy-saving Software DesignIf system software like operating system, application layer and network protocol etc. has been specially optimized on power consumption, the surviving time of WSN will extend. The most proper way is to use DPM and DVS in operating system. Because OS attains performance demand of all...
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