A Unified Approach for Detection of Children Emotion, Physiological and Security Using IoT

This research addresses the pressing global concern of child security, focusing on mitigating risks such as environmental pollution in school zones and potential incidents of harassment. The proposed implemented system incorporates key quantitative components, including an ESP32 microcontroller, MQ135 air quality sensor, Max30102 heartbeat sensor, LCD display, GPS module, buzzer, and data analytics through IoT integration with ThingSpeak. The device employs a comprehensive approach to ensure the safety of children in various settings. Quantitative results demonstrate the effectiveness of the system in monitoring children's movements from school. In instances of panic attacks, the device accurately detects the child's heart rate, providing realtime updates to the cloud. These updates, including precise heart rate values and the child's current position, are instantly transmitted to the parent's phone. The integration of data analytics through ThingSpeak enhances the overall reliability and functionality of the system. Parents can receive immediate and quantifiable information about their child's well-being, ensuring a prompt response to any potential threats or emergencies. The inclusion of quantitative measures strengthens the study's contribution to child security, providing concrete evidence of the system's efficacy in safeguarding children from both environmental hazards and unethical behavior.