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Neuromorphic Computing for Smart Agriculture

Author

Listed:
  • Shize Lu

    (Liaoning Key Laboratory of Radio Frequency and Big Data for Intelligent Applications, Liaoning Technical University, Huludao 125105, China
    College of Engineering, China Agricultural University, Beijing 100083, China
    Key Laboratory of Equipment and Informatization in Environment Controlled Agriculture, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China)

  • Xinqing Xiao

    (College of Engineering, China Agricultural University, Beijing 100083, China
    Key Laboratory of Equipment and Informatization in Environment Controlled Agriculture, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China)

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.

Suggested Citation

  • Shize Lu & Xinqing Xiao, 2024. "Neuromorphic Computing for Smart Agriculture," Agriculture, MDPI, vol. 14(11), pages 1-26, November.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:11:p:1977-:d:1513589
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    References listed on IDEAS

    as
    1. Elisa Donati & Giacomo Valle, 2024. "Neuromorphic hardware for somatosensory neuroprostheses," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
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