Neuromorphic Computing for Smart Agriculture

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.

Authors

Institutions

Publication Details

Journal
Agriculture
Published
2024-11-04
DOI
https://doi.org/10.3390/agriculture14111977
Citations
25
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
5.22
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Neuromorphic Computing for Smart Agriculture

Siyi Lu, Xinqing Xiao
25 citations
Agriculture
Advanced Memory and Neural Computing
5.22
article

Neuromorphic Computing for Smart Agriculture

Siyi Lu, Xinqing Xiao
article en
25 citations

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.

AgricultureVol. 14(11)
Liaoning Technical University (CN), Ministry of Agriculture and Rural Affairs (CN), China Agricultural University (CN)
Zero hunger
Openalex Percentile: Top 4%
Advanced Memory and Neural Computing
5.22
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Neuromorphic Computing for Smart Agriculture — Siyi Lu, Xinqing Xiao · Agriculture (2024) | TGRS Research Map | TGRS