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1 Jul 24, 2020
Classification of The Plant Leaf Disease using Fine-Tuning of The 12 Layers of Deep Convolution Neural Network

In this paper, we proposed the various plant leaf disease classification and identification based model on an improved feature of the Deep CNN (Deep Convolution Neural Network). The model of a deep CNN is using the 5 various types of plant leaf disease identification and classification. These models improved the feature of deep CNN and compare the performance accuracy of different batch sizes and compare the performance of feature extraction techniques of augmentation and without augmentation. The proposed model is the training of different iteration, changing the batch size, and variation of dropouts values at regular intervals. The proposed model is achieved the best accuracy is 98.69% as compared to the most popular classification methods. This technique of variation of the feature is helpful to identification and classification of various plant leaf diseases in various environment and future create simulator early identification of the leaf disease of color variation using the color feature enhancement....

Authors: Mohan Durvey,Rajeev Kumar Singh.

2 Jul 24, 2020
Internet of Things (IoT) for Construction Smart Home System

Internet of Things (IoT) is an emerging technology that is making our world smarter. The idea of connected world cannot be imagined without IoT. An IoT based Smart Home is one such example. In IoT enabled Smart Home environment various things such as lighting, home appliances, computers, security camera etc. In current electric energy statistics, the largest power is consumed by heating and cooling air conditioners, which are widely used in residential and commercial buildings. Hence, reducing energy consumption of air conditioners is vitally important for improving power utilization efficiency in global energy perspective. To save electricity consumption of air conditioners, this paper proposes an Internet of Things (IoT)- based smart controlling system including smart meter, smart gateway, and cloud computing modules. We manufacture a smart meter to control the compressor operation of air conditioners based on the specified temperature. Meanwhile, it is able to monitor the real-time power consumption datasets, which are delivered to a cloud server via a wireless gateway. Using Zigbee communication protocol, our developed gateway enables automatic detection of smart meter by a broadcasting method. After gathering the IP addresses of connected smart meters, the gateway dispatches controlling signals to relevant meters. We developed a general programming interface to control the operation of this smart gateway so as to support flexible and extensible IoT development. The collected electricity consumption datasets are transmitted to a cloud server in real time via Internet. Meanwhile, the remote operation signals of smart meters are transmitted to the cloud. An extreme learning machine is implemented to analyze the energy distribution for energy consumption prediction. Based on the analysis results and operation signals, the cloud generates an energy-saving decision to control the distributed air conditioners by the smart meters, which are linked to the Internet through the gateways. This way, an individual smart meter controls cooling and heating operations of its corresponding compressor to realize local energy management. Besides, the energy saving strategy eases power grid burden and decrease load of power station. Thus, our proposed system has positive influence on greenhouse gas reduction....

Authors: Ravikant Singh Lodhi, Ashok Verma.

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