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<p>Infant kidnapping has a significant impact on public safety. After the massive phenomenon of abduction, a system is established for Monitoring and tracking of the infants discharged from the Sick Newborn Care Unit (SNCU). Even with the help of surveillance cameras, the kidnappers abduct the infants by disguising themselves as nurses and doctors. So, it is necessary to ensure the safety of infants in hospitals. Infants sometimes fall sick due to temperature and other health related problems and hence it is necessary to track the basic health parameters. The infant health monitoring system measures ambient temperature and humidity with the help of DHT11 to provide comfort and health. A pulse oximeter built into a wristband continuously tracks oxygen saturation (SpO₂) and pulse rate, and real-time data is displayed on an OLED screen and cloud-based monitoring system. The proposed solution uses Internet of Things technology to track the infant’s health status, monitor the infant’s safety by preventing abduction by strangers and cry analysis system using machine learning. The proposed infant monitoring system evaluated health parameters with a high accuracy of 99.37%. Reliable categorization was achieved by cry analysis, which demonstrated an accuracy of 94.6%. It also notifies the parents and doctors when any of the health parameters falls below the clinical threshold through Global System for Mobile Communication and warns them when there is an attempt to abduct the infant thereby ensuring two-layer security.</p>

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IoT Enabled Infant Safety and Health Monitoring System with Integrated Cry Analysis

  • 期刊论文

  • 发表日期：

    2026年4月10日

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  • K. Radhakrishnan,
  • J. S. Leena Jasmine,
  • David Neels Ponkumar,
  • S. Sruthi

摘要

Infant kidnapping has a significant impact on public safety. After the massive phenomenon of abduction, a system is established for Monitoring and tracking of the infants discharged from the Sick Newborn Care Unit (SNCU). Even with the help of surveillance cameras, the kidnappers abduct the infants by disguising themselves as nurses and doctors. So, it is necessary to ensure the safety of infants in hospitals. Infants sometimes fall sick due to temperature and other health related problems and hence it is necessary to track the basic health parameters. The infant health monitoring system measures ambient temperature and humidity with the help of DHT11 to provide comfort and health. A pulse oximeter built into a wristband continuously tracks oxygen saturation (SpO₂) and pulse rate, and real-time data is displayed on an OLED screen and cloud-based monitoring system. The proposed solution uses Internet of Things technology to track the infant’s health status, monitor the infant’s safety by preventing abduction by strangers and cry analysis system using machine learning. The proposed infant monitoring system evaluated health parameters with a high accuracy of 99.37%. Reliable categorization was achieved by cry analysis, which demonstrated an accuracy of 94.6%. It also notifies the parents and doctors when any of the health parameters falls below the clinical threshold through Global System for Mobile Communication and warns them when there is an attempt to abduct the infant thereby ensuring two-layer security.