No abstract
Internet of Things (IoT) is a system to which innumerable smart gadgets are associated, and in the end incorporate the objective world with the information world.IoT is able to greatly improve the resource utilization of smart devices and promote the harmony between man-made and natural environments. The Internet of Things (IoT) is a paradigm in which smart objects actively collaborate among them and with other physical and virtual objects available in the Web form high-level tasks for the benefit of end-users. IoT resources are utilized as resources with which to run a composite service that supports user tasks.This heterogeneous device interaction causes difficulties to interact with the devices while gathering real time information management and monitoring from the environment. We propose technique to improve resource utilization in IoT and also propose resource management system, in which all smart devices are accessed on a single platform and handle these difficulties, real time information, monitoring of smart devices.
IoT (Internet of Things) services are emerging and the bandwidth requirements for rich media communication services are increasing exponentially. We propose a virtual edge architecture comprising computation resource management layers and path bandwidth management layers for easy addition and reallocation of new service node functions. These functions are performed by the Virtualized Network Function (VNF), which accommodates terminals covering a corresponding access node to realize fast VNF migration. To increase network size for IoT traffic, VNF migration is limited to the VNF that contains the active terminals, which leads to a 20 % reduction in the computation of VNF migration. Fast dynamic bandwidth allocation for dynamic bandwidth paths is realized by proposed Hierarchical Time Slot Allocation of Optical Layer 2 Switch Network, which attain the minimum calculation time of less than 1/100.
Sun power is a standout amongst the most productive yet clean wellsprings of vitality we approach. There are no expanded fuel expenses or conditions, no connections to toxins, and it's both dependable and reasonable. Obviously, keeping in mind the end goal to bridle sun oriented power you require access to particular innovation. This tech depends on either little scale sun oriented photovoltaic (PV) systems but in main problem of photovoltaic (PV) system soil and dust particles accumulating on photovoltaic (PV) panels reduce the solar energy getting the cells, thereby falling overall power performance. We are solving the problem of this cleaning the PV panels is a problem of great practical engineering interest in solar PV power generation cleaning the photovoltaic (PV) panels is a problem of great practical interest in solar PV power creation. We are solve this problem discuss the methods for dust removal system using the Internet of things IoT .We are developing the simple and useful dust cleaning device and developed novel architecture of dust cleaning system for PV panel using IoT. the main motive for this system is developed system for dust cleaning for PV system using IoT and maintaining the clean PV panel efficiency.
From the last few years, the use of social media has increased resulting into the rise of fake news and their spreading on a large scale. Recent political events have increased the spread of fake news. As seen by the widespread impact of the huge beginning of fake news, people are inconsistent in the absence of effective fake news detectors. This work has made an attempt to automate the fake news detection process by employing the logistic regression (LR) and latest and modified word embedding technique. In this paper, we worked on the fake news recognition mechanism for 2 different datasets, viz. dataset comprising online traditional news articles and news collected from a wide range of sources. The results are compared with long short-term memory (LSTM) and traditional machine and deep learning methods for both the datasets. It reveals that the traditional mechanism for attention does not function as expected. With the help of word2vec embedding, we modified the original attention mechanism, which is more effective in dealing with this issue. The proposed method is compared with several outstanding approaches and the results are presented. Our work outperforms these methods in many parameters. This approach has created a framework that captures various fake news indicators and classifies the news as genuine or fake and makes decisions.
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