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Intelligent frost prediction and active protection through cyber-physical systems in the agricultural sector

Project Member(s): Lipman, J., Abolhasan, M.

Funding or Partner Organisation: Food Agility CRC Limited (Food Agility CRC)
Food Agility CRC Limited (Food Agility CRC)

Start year: 2020

Summary: To mitigate yield reduction due to frost, this research proposes an intelligent frost prediction system to provide predictions with high temporal resolutions. Utilising these predictions, a cyber-physical system (CPS) could be built to control existing protection methods. The CPS would connect the frost prediction intelligence with protection actuators to achieve automated smart farming. This is a Food Agility CRC Scholarship for Ian Zhou.


Zhou, I, Lipman, J, Abolhasan, M & Shariati, N 2023, 'Intelligent spatial interpolation-based frost prediction methodology using artificial neural networks with limited local data', Environmental Modelling & Software, vol. 165, pp. 105724-105724.
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Zhou, I, Lipman, J, Abolhasan, M, Shariati, N & Lamb, DW 2020, 'Frost Monitoring Cyber–Physical System: A Survey on Prediction and Active Protection Methods', IEEE Internet of Things Journal, vol. 7, no. 7, pp. 6514-6527.
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Makhdoom, I, Tofigh, F, Zhou, I, Abolhasan, M & Lipman, J 1970, 'PLEDGE: An IoT-oriented Proof-of-Honesty based Blockchain Consensus Protocol', 2020 IEEE 45th Conference on Local Computer Networks (LCN), 2020 IEEE 45th Conference on Local Computer Networks (LCN), IEEE, Australia, pp. 54-64.
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FOR Codes: Climate Change Models, Knowledge Representation and Machine Learning, Machine learning