A Hybrid Data Acquisition Model using Artificial Intelligence and IoT Messaging Protocol for Precision Farming

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.