Wang, E., Attard, S., Everingham, Y., Philippa, B., and Xiang, W. (2018) Smarter irrigation management in the sugarcane farming system using internet of things. In: Proceedings of the 40th Annual Conference of the Australian Society of Sugar Cane Technologists (40) pp. 117-122. From: ASSCT 2018: 40th Annual Conference of the Australian Society of Sugar Cane Technologists, 17-20 April 2018, Mackay, QLD, Australia.

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Abstract

Irrigation management is a considerable time investment for many sugarcane farmers. Better irrigation practices can lead to improved yields through less water stress, and reduce water usage to deliver economic benefits for farmers. The reduced runoff and deep drainage from excess irrigation can also deliver benefits to the environment.

The Internet of Things (IoT) is about allowing things to sense, to communicate, and thus creating opportunities for more direct integration between the physical world and computer-based systems. IoT has been transforming all spheres of life into smart homes, smart cities, and smart healthcare. Today’s farms can leverage IoT to remotely monitor sensors, manage and control harvesters and irrigation equipment, and utilise artificial intelligence based analytics to quickly analyse operational data combined with third party information, to provide new insights and improve decision-making.

This project focuses on improving irrigation management by integrating the auto-irrigation system (e.g., WiSA) and IrrigWeb (a sugarcane irrigation scheduling tool) to provide a smarter irrigation solution using IoT. The system generates a two-way communication channel between these two platforms, which allows them to share data. Specifically, the uplink program (WiSA to IrrigWeb) was developed and deployed in a Burdekin farm. It connects the farmer’s WiSA to IrrigWeb, by uploading irrigation data automatically. The farmer’s irrigation records are automatically loaded into IrrigWeb. This saves the farmer time and makes the scheduling more efficient. Another benefit is that the farmer can now see the exact amount being applied to each field, and make modifications to the irrigation management, if required. Moreover, automating the data transfer from WiSA to IrrigWeb will greatly improve the potential for uptake and use of technologies like IrrigWeb. On the other hand, the downlink program (IrrigWeb to WiSA) will be developed to automatically apply scheduling from IrrigWeb to WiSA. Combining the uplink and downlink programs, a smarter irrigation management system can automatically control sugarcane irrigation, and ultimately make sugarcane irrigation fully autonomous.

Item ID:	53364
Item Type:	Conference Item (Research - E1)
ISSN:	0726-0822
Keywords:	near infrared, quality, machine learning, SVM, PLS
Related URLs:	Organisation
Funders:	Sugar Research Australia, James Cook University (JCU)
Projects and Grants:	JCU PhD Project 2015/072
Date Deposited:	02 May 2018 00:33
FoR Codes:	30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300201 Agricultural hydrology @ 50% 40 ENGINEERING > 4009 Electronics, sensors and digital hardware > 400908 Microelectronics @ 50%
SEO Codes:	82 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 8203 Industrial Crops > 820304 Sugar @ 70% 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890201 Application Software Packages (excl. Computer Games) @ 30%
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