家电科技 ›› 2022, Vol. 0 ›› Issue (3): 114-119.doi: 10.19784/j.cnki.issn1672-0172.2022.03.022

• 论文 • 上一篇    下一篇

基于用户大数据分析的物联网家电质量改善方法研究

张永勐1, 李红伟2, 周荣培1, 潘伟1   

  1. 1.美的集团IoT 广东佛山 528311;
    2.中国家用电器研究院 北京 100176
  • 出版日期:2022-06-01 发布日期:2022-06-20
  • 作者简介:张永勐,学士。研究方向:物联网质量管理。地址:广东省佛山市顺德区北滘镇美的总部大楼。E-mail:zhangym12@midea.com。

Research on quality improvement method of IoT appliances based on user big data analysis

ZHANG Yongmeng1, LI Hongwei2, ZHOU Rongpei1, PAN Wei1   

  1. 1. Midea Group IoT Foshan 528311;
    2. China Household Electric Appliance Research Institute Beijing 100176
  • Online:2022-06-01 Published:2022-06-20

摘要: 随着近几年智能家居行业的迅速发展,家电物联网化已成必然趋势,其服务质量和用户操作体验直接影响用户对智能家居的接受程度。传统的质量改善方法缺少对用户大数据主动采集分析机制,难以实现对家电质量问题的精确定位,也缺乏对家电服务质量的监控预警,因此无法实现对物联网家电质量的量化评价和闭环改善。通过研究基于用户大数据分析的物联网家电质量改善模型,融合家电行业传统质量分析方法和互联网的大数据分析方法,借助物联网质量管理平台,质量人员可以实现物联网家电质量数据的精准定位、量化评价、监控预警和闭环改善,最终实现物联网家电质量的全面改善。

关键词: 物联网, 大数据, 事件跟踪, 质量改善

Abstract: With the rapid development of smart home industry in recent years, networking of household appliances has become an inevitable trend, and its service quality as well as user operation experience directly effect the users' acceptance of smart home. The traditional quality improvement methods lack the active collection and analysis mechanism for users' big data, it is difficult to accurately locate the quality problems of appliances, and there is a lack of monitoring and early warning of the service quality of appliances. Therefore, it is impossible to realize the quantitative evaluation and closed-loop improvement of the quality of IoT appliances. By studying the quality improvement model of IoT appliances based on users' big data analysis, integrating the traditional quality analysis methods of the household appliance industry and the big data analysis methods of the Internet, with the help of the IoT quality management platform, quality personnel can realize the accurate positioning, quantitative evaluation, monitoring and early warning, closed-loop improvement of the quality data of appliances, and finally realize the overall improvement of the quality of IoT appliances.

Key words: Internet of Things (IoT), Big Data, Event tracking, Quality improvement

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