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一种利用物联网传感器和机器学习实现优化育儿护理的新型智能婴儿摇篮系统。

A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care.

作者信息

Chandnani Kunal, Tripathy Suryakant, Parbhakar Ashutosh Krishna, Takiar Kshitij, Singhal Urvi, Sasikumar P, Maheswari S

机构信息

School of Electronics Engineering, Vellore Institute of Technology, Vellore, India.

School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India.

出版信息

Sci Rep. 2025 May 30;15(1):19080. doi: 10.1038/s41598-025-02691-8.

Abstract

The IoT Smart Cradle for Baby Monitoring System & Infant Care is introduced as an innovative solution to address critical gaps in contemporary infant care. This system integrates Internet of Things (IoT) technology, machine learning, and smart automation to offer a safer, more responsive, and comfortable environment for babies. A significant challenge in current infant care is the limitations of traditional monitoring systems. These systems often fail to provide comprehensive, real-time monitoring of essential environmental parameters and lack automated responses to an infant's immediate needs, potentially increasing parental anxiety and compromising infant safety and well-being. This smart cradle is designed to overcome these limitations by employing a comprehensive network of sensors-including temperature, humidity, gas, noise sensors, and a cry-detection microphone-to monitor the baby's needs and environmental conditions in real time. Microcontrollers like Raspberry Pi and NodeMCU use intelligent machine-learning algorithms to process the collected data and trigger adaptive responses. These responses include regulating temperature and humidity, filtering harmful gases, and activating a motorized rocking mechanism to soothe the infant. A dedicated mobile application offers parents secure, real-time monitoring and control over the cradle's functions. The system demonstrates high accuracy in sensor readings, with temperature and humidity measurements reaching approximately 99.6% accuracy, and cry detection achieving approximately 93.2% accuracy. User feedback indicates that 95% of parents found the interface easy to use, and 87% reported a positive impact on their parenting experience. In contrast to traditional solutions that often require manual intervention or provide limited automation, this smart cradle uses predictive analytics to proactively address potential discomforts and hazards, thus presenting a more reliable, intelligent, and user-friendly solution for modern parenting.

摘要

物联网智能婴儿监护与护理摇篮作为一种创新解决方案被引入,以填补当代婴儿护理中的关键空白。该系统集成了物联网(IoT)技术、机器学习和智能自动化,为婴儿提供一个更安全、响应更及时且更舒适的环境。当前婴儿护理中的一个重大挑战是传统监护系统存在局限性。这些系统往往无法对关键环境参数进行全面、实时的监测,并且缺乏对婴儿即时需求的自动响应,这可能会增加父母的焦虑,并危及婴儿的安全和健康。这款智能摇篮旨在通过采用包括温度、湿度、气体、噪音传感器以及哭声检测麦克风在内的综合传感器网络来克服这些局限性,实时监测婴儿的需求和环境状况。诸如树莓派和NodeMCU之类的微控制器使用智能机器学习算法来处理收集到的数据并触发适应性响应。这些响应包括调节温度和湿度、过滤有害气体以及启动电动摇摆机构来安抚婴儿。一款专用的移动应用程序为父母提供对摇篮功能的安全、实时监测和控制。该系统在传感器读数方面具有很高的准确性,温度和湿度测量的准确率约为99.6%,哭声检测的准确率约为93.2%。用户反馈表明,95%的父母认为界面易于使用,87%的父母表示对他们的育儿体验有积极影响。与传统解决方案往往需要人工干预或自动化程度有限不同,这款智能摇篮使用预测分析来主动解决潜在的不适和危险,从而为现代育儿提供了一个更可靠、智能且用户友好的解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aaf/12125208/f762b97e555f/41598_2025_2691_Fig1_HTML.jpg

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