A hybrid data acquisition model using artificial intelligence and IoT messaging protocol for precision farming

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ID: 283994
2020
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Abstract
The emergence of the Internet-of-Things (IoT) technology had widened the application of the existing technologies we have been using. This paper then uses the IoT technology in the form of wireless sensor network (WSN) specifically designed and developed for smart farming applications. The advancement of communications is determined to be highly by artificial intelligence (AI). Nevertheless, messaging protocols must be considered to avert false node location and minimize redundant data. This paper proposes a hybrid of two novel algorithms namely, Multi-objective Message Queue Telemetry Transport (MMQTT) and Deep Neural Network based routing algorithm (DNNRA) and compress their performance with the Baseline. The experimental outcomes show that the proposed method is found capable of improving the energy efficiency of wireless sensor network, sensor cluster node selection and deployment, detection capability, jitter/delay at actual smart aquaponic setup validation.
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persistent_1760650342_68f164662d98d Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Dadios, Elmer P.
Journal Malay Journal
Year 2020
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