Version 1
: Received: 31 March 2023 / Approved: 11 April 2023 / Online: 11 April 2023 (10:24:24 CEST)
How to cite:
Aboneh, T.W.; Rorissa, A. Fusion of Multiple Sensors to Implement Precision Agriculture using IoT Infrastructure. Preprints2023, 2023040119. https://doi.org/10.20944/preprints202304.0119.v1
Aboneh, T.W.; Rorissa, A. Fusion of Multiple Sensors to Implement Precision Agriculture using IoT Infrastructure. Preprints 2023, 2023040119. https://doi.org/10.20944/preprints202304.0119.v1
Aboneh, T.W.; Rorissa, A. Fusion of Multiple Sensors to Implement Precision Agriculture using IoT Infrastructure. Preprints2023, 2023040119. https://doi.org/10.20944/preprints202304.0119.v1
APA Style
Aboneh, T.W., & Rorissa, A. (2023). Fusion of Multiple Sensors to Implement Precision Agriculture using IoT Infrastructure. Preprints. https://doi.org/10.20944/preprints202304.0119.v1
Chicago/Turabian Style
Aboneh, T.W. and Abebe Rorissa. 2023 "Fusion of Multiple Sensors to Implement Precision Agriculture using IoT Infrastructure" Preprints. https://doi.org/10.20944/preprints202304.0119.v1
Abstract
Precision Agriculture is the ability to handle variations in productivity within a field and maximize financial return, optimize resource utilization and minimize impact of the environment. It is also the process of automated data collection, cloud storage and utilization to build robust decision support system. In case of Ethiopia, due to poor communication infrastructure coverage and absence of the state-of-the-art technology in the agriculture sector, implementing precision farming system is a challenging tasks in the domain area. In this work, we proposed a fusion of multiple sensors using IOT and IIOT infrastructure to collect critical data from farming fields to develop precision farming facility for decision makers. The main purpose was to monitor weather variability, automate irrigation process, extract critical soil properties. In addition, we have used time series data collected from sensor devices to build forecasting model. Fusion of multiple IoT device provide a mechanism in the agriculture area to deal with real-time monitoring of crops. It is cost-effective technology and required low-energy with edge computing sensor device. We employed the Message Queuing Telemetry Transport (MQTT) protocol to connect the Industrial/Internet of Things (I/IoT) to the cloud server. The communication between system user and sensor device has been done via cloud using Node-RED platform, web android APIs. The cloud-based Eco-system allows us to aggregate, visualize, and analyze live streams output from each sensor in real-time manner. Finally, we have built time series forecasting model using records collected by each sensor device. Using the multi-variate time series data-set, we have obtained about 99 forecasting accuracy on some important variables. Finally, we have developed mobile and web-based application for the end-user to monitor the proposed system remotely.
Keywords
Sensor Fusion; IIOT; IOT; Precision Agriculture; Time Series data; Predictive model
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
