Child Presence Detection for Child Safety with Deep Neural Networks

Sidiq Syamsul Hidayat; Dita Aprilia; Sindung Hadwi; Irfan Mujahidin; M. Cahyo Adi Prabowo; Fikri Arif Rakhman

doi:10.30591/jpit.v10i2.6540

Child Presence Detection for Child Safety with Deep Neural Networks

Sidiq Syamsul Hidayat, Dita Aprilia, Sindung Hadwi, Irfan Mujahidin, M. Cahyo Adi Prabowo, Fikri Arif Rakhman

Abstract

Accidents and injuries to children often occur due to lack of supervision. This research develops a child presence detection system using Computer Vision technology and the Age Estimation method to improve child safety in dangerous areas. The system was tested with a Canon EOS M50 camera at various distances, camera heights, and light intensity. The analysis using anova obtained a data confidence level of 95% for light intensity, and the age estimation method showed performance with a success of 84.72%. This research can be applied to supervise and improve safety in children, especially outdoors.

Keywords

Computer Vision, Age Estimation, Child-Object Detection, Child Safety

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DOI: https://doi.org/10.30591/jpit.v10i2.6540