武汉工程职业技术学院学报2026，Vol.38Issue(1)：41-46,6.
基于边缘智能的自适应农业物联网系统
Adaptive IoT System for Smart Agriculture Based on Edge Intelligence
程利 1胡智 2李青松2
作者信息
- 1. 武汉铁路职业技术学院智能制造学院 湖北 武汉:430200
- 2. 湖北工业职业技术学院智能工程学院 湖北 十堰:442000
- 折叠
摘要
Abstract
The decision-making of traditional agricultural monitoring and control systems relies on cloud computing,which has significant shortcomings in terms of energy consumption,latency,and sus-tainability.To address the above issues,this study designs an edge-intelligent adaptive environment mo-nitoring and control system based on ESP32+TinyML(Tiny Machine Learning).The system deploys a lightweight TinyML model on the node side for environmental trend prediction and anomaly recognition,which can effectively reduce redundant energy consumption and communication load.The system adopts a"solar energy and supercapacitor"solution for energy optimization design,combining deep sleep and on-demand wake-up.After experimentation,the system has achieved adaptive monitoring,trend prediction of node environmental information,and autonomous regulation.This study provides a feasible path for a low-power,predictive,and sustainable smart agricultural IoT system.关键词
边缘计算/TinyML/自适应监测/物联网/智慧农业Key words
edge computing/TinyML/adaptive monitoring/Internet of Things/smart agriculture分类
信息技术与安全科学引用本文复制引用
程利,胡智,李青松..基于边缘智能的自适应农业物联网系统[J].武汉工程职业技术学院学报,2026,38(1):41-46,6.
