吉林大学学报(信息科学版) ›› 2026, Vol. 44 ›› Issue (2): 276-283.

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低功耗 NB-IoT 驱动的智慧物联供热监控系统设计

张 烨, 魏遴桐, 乔正石, 千承辉   

  1. 吉林大学 仪器科学与电气工程学院, 长春 130026
  • 收稿日期:2025-03-13 出版日期:2026-04-14 发布日期:2026-04-14
  • 通讯作者: 千承辉(1975— ), 女(朝鲜族), 吉林汪清人, 吉林大学正高级工程师, 主要从事智能仪器与微弱信号检测研究, (Tel)86-431-88502381(E-mail)qianch@ jlu. edu. cn。 E-mail:zhangye2772@163.com
  • 作者简介:张烨(2004— ), 女, 山东菏泽人, 吉林大学本科生, 主要从事仪器科学与技术研究, ( Tel) 86-19819551955 ( E-mail) zhangye2772@163.com。
  • 基金资助:
    国家级大学生创新创业基金资助项目(202310183254); 吉林大学实验技术基金资助项目(SYXM2023a012)

Design of NB-IoT-Based Intelligent Monitoring System for Community Heating Networks

ZHANG Ye, WEI Lintong, QIAO Zhengshi, QIAN Chenghui   

  1. College of Instrument Science and Electrical Engineering, Jilin University, Changchun 130026, China
  • Received:2025-03-13 Online:2026-04-14 Published:2026-04-14

摘要:

针对传统供热系统冷热不均、能耗高、调控效率低等问题, 设计并实现了一种基于 NB-IoT(Narrow Band Internet of Things)的物联网智能监控小区供热系统。该系统构建 NB-IoT 组网与动态功耗计算监控架构, 可搭载16个测温终端和两个基站。测温节点可采集室内供暖和用户预设温度, 数据通过 NB-IoT 组网, 经边缘网关智能处理后上传至云端, 在上位机界面实现可视化显示, 支持对温度数据的历史查阅、异常分析和融合预测。测试结果表明, 该系统能显著降低功耗, 休眠模式下系统整体电流≤8μA, 结合自适应唤醒机制使电池寿命超过2 年。 该方案较传统系统节能 27. 6% , 用户供暖满意度提升 32% , 为传统供热系统智能化改造提供有效解决方案。

关键词:

Abstract:

To addressing the critical issues faced by traditional heating systems, such as uneven temperature distribution, significant energy wastage, and inefficiencies associated with manual control, an advanced IoT-based intelligent monitoring system utilizing NB-IoT(Narrow Band Internet of Things) technology is designed.The primary objective is to enhance the efficiency, reliability, and user satisfaction of community heating networks through modern technological integration. The proposed system integrates contemporary communication technologies, sensor data acquisition, cloud-based AI analysis, and edge computing. It consists of portable temperature measurement nodes, NB-IoT communication modules, an AI co-processor for local intelligence, and a cloud server for centralized management. Specifically, up to 16 temperature-measuring nodes and two base stations are deployed within the network. These terminal nodes collect indoor heating temperatures alongside user-defined settings, transmitting gathered data via NB-IoT to a cloud server where it undergoes intelligent processing facilitated by an edge gateway. This processed data is then visually displayed on a user interface,enabling historical reference, anomaly detection, and predictive analysis for temperature patterns. Testing results demonstrate substantial improvements in system performance, including a notable reduction in power  consumption, and the overall system current in sleep mode is≤8μA,which extends battery life expectancy beyond two years. The system significantly enhances user satisfaction by providing more consistent and comfortable indoor temperatures. With its proven capability to reduce energy waste and improve operational efficiencies, the system not only promises considerable economic benefits but also establishes itself as an effective solution to the inherent limitations of conventional heating systems. Thus, this work contributes to the advancement of smart community infrastructure, promoting sustainable and efficient heating solutions.

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中图分类号: 

  • TN929. 5