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- W2332122987 abstract "The difficulty in monitoring sensor networks is not only due to their inherently distributed nature but also the need for mechanisms to address their harsh operating conditions such as unreliable communications, faulty nodes, and extremely constrained resources. Researchers have proposed different monitoring models to overcome these difficulties with the ultimate goal of making monitoring easy while making full use of available data. Life- environmental monitoring is mostly composed of air quality, water quality and eco-tourism sensing data. In case of separate communication it gives high energy loss because there is requirement of some mechanism that can select multiple communications in single communication. This kind of merging is called data aggregation. Aggregation process is itself efficient process that uses the improved greedy approach. In this study, we present a secure and authentication approach for the life-environmental data aggregation. The user authentication is performed using secure hash algorithm. It will reflect participating node over the communication final stage is proposed work of neural network for checking bad packet communication over the network. The derived result showed the presented work which is more reliable and efficient than existing approach." @default.
- W2332122987 created "2016-06-24" @default.
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- W2332122987 date "2014-04-15" @default.
- W2332122987 modified "2023-10-05" @default.
- W2332122987 title "Life-Environmental Sensor Data Aggregation Based on Neural Network" @default.
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- W2332122987 doi "https://doi.org/10.14257/astl.2014.47.47" @default.
- W2332122987 hasPublicationYear "2014" @default.
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