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

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)

Publication Date

2020

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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Disciplines

Electrical and Computer Engineering

Keywords

Wireless sensor networks; Internet of things; Precision farming; Artificial intelligence

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