A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care
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 responsiv...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-02691-8 |
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| author | Kunal Chandnani Suryakant Tripathy Ashutosh Krishna Parbhakar Kshitij Takiar Urvi Singhal P. Sasikumar S. Maheswari |
| author_facet | Kunal Chandnani Suryakant Tripathy Ashutosh Krishna Parbhakar Kshitij Takiar Urvi Singhal P. Sasikumar S. Maheswari |
| author_sort | Kunal Chandnani |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-042e40a7333e4604a1c6ff7de0d3475c |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-042e40a7333e4604a1c6ff7de0d3475c2025-08-20T03:22:07ZengNature PortfolioScientific Reports2045-23222025-05-0115112610.1038/s41598-025-02691-8A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental careKunal Chandnani0Suryakant Tripathy1Ashutosh Krishna Parbhakar2Kshitij Takiar3Urvi Singhal4P. Sasikumar5S. Maheswari6School of Electronics Engineering, Vellore Institute of TechnologySchool of Electronics Engineering, Vellore Institute of TechnologySchool of Electronics Engineering, Vellore Institute of TechnologySchool of Electronics Engineering, Vellore Institute of TechnologySchool of Electronics Engineering, Vellore Institute of TechnologySchool of Electronics Engineering, Vellore Institute of TechnologySchool of Computer Science and Engineering, Vellore Institute of TechnologyAbstract 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.https://doi.org/10.1038/s41598-025-02691-8Smart cradleIoTBaby comfortCry detectionMachine learningInfant monitoring |
| spellingShingle | Kunal Chandnani Suryakant Tripathy Ashutosh Krishna Parbhakar Kshitij Takiar Urvi Singhal P. Sasikumar S. Maheswari A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care Scientific Reports Smart cradle IoT Baby comfort Cry detection Machine learning Infant monitoring |
| title | A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care |
| title_full | A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care |
| title_fullStr | A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care |
| title_full_unstemmed | A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care |
| title_short | A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care |
| title_sort | novel smart baby cradle system utilizing iot sensors and machine learning for optimized parental care |
| topic | Smart cradle IoT Baby comfort Cry detection Machine learning Infant monitoring |
| url | https://doi.org/10.1038/s41598-025-02691-8 |
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