Neuromorphic Computing for Smart Agriculture

Shize Lu and Xinqing Xiao ()
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Shize Lu: Liaoning Key Laboratory of Radio Frequency and Big Data for Intelligent Applications, Liaoning Technical University, Huludao 125105, China
Xinqing Xiao: College of Engineering, China Agricultural University, Beijing 100083, China

Agriculture, 2024, vol. 14, issue 11, 1-26

Abstract: Neuromorphic computing has received more and more attention recently since it can process information and interact with the world like the human brain. Agriculture is a complex system that includes many processes of planting, breeding, harvesting, processing, storage, logistics, and consumption. Smart devices in association with artificial intelligence (AI) robots and Internet of Things (IoT) systems have been used and also need to be improved to accommodate the growth of computing. Neuromorphic computing has a great potential to promote the development of smart agriculture. The aim of this paper is to describe the current principles and development of the neuromorphic computing technology, explore the potential examples of neuromorphic computing applications in smart agriculture, and consider the future development route of the neuromorphic computing in smart agriculture. Neuromorphic computing includes artificial synapses, artificial neurons, and artificial neural networks (ANNs). A neuromorphic computing system is expected to improve the agricultural production efficiency and ensure the food quality and safety for human nutrition and health in smart agriculture in the future.

Keywords: neuromorphic computing; smart agriculture; artificial synapses; artificial neurons; artificial neural networks (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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