Capstone Projects
MAIDE: A MOTHER’S AIDE IN RECOGNIZING AND ANALYZING BABY CRIES USING MACHINE LEARNING
- Item sets
- College of Computer Studies
- Title
- MAIDE: A MOTHER’S AIDE IN RECOGNIZING AND ANALYZING BABY CRIES USING MACHINE LEARNING
- Author(s)
- Jessa Abadilla
- Kylah M. Ostia
- Affiliation
- Misamis University
- Misamis University
- Contributor
- Orong, Markdy Y. - Adviser
- Caroro, Roseclaremath A. - Panel Chairman
- Talirongan, Florence Jean B. - Panel Member
- Talirongan, Hidear - Panel Member
- Year
- 2024-11
- Abstract
- Recognizing and analyzing baby cries is crucial for identifying specific needs such as hunger, discomfort, belly pain, burping, or sleepiness. This study developed a tool, MAide, to address these challenges of recognizing baby cries and interpreting their meaning. The system integrated a real-time detection device that captures and processes baby cries, transmitting data to a mobile app. This device was developed using the Agile methodology and the Scrum framework, where modeling was used, Teachable Machine Learning, a platform built on TensorFlow, which implements a pre-trained Convolutional Neural Network (CNN) to classify and analyze baby cries based on a labeled dataset. The dataset utilized in this research comprises samples from Kaggle, GitHub, Splann, and Donate-a-Cry database. Nevertheless, the researchers had to examine these datasets closely to guarantee their accuracy and dependability. The MAide allows mothers to register devices and add their baby's information to detect baby cries and receive instant notifications about their baby's needs. This solution enhanced caregiving by enabling timely responses, reducing stress for new parents, and improving confidence in infant care. The system was evaluated and received high functionality, accuracy, and usability ratings. The MAide platform demonstrated that the IoT-enabled system significantly enhanced infant care by recognizing and analyzing baby cries, providing mothers with a reliable and efficient tool for understanding and promptly responding to their baby's needs.
- Keywords
- Baby Cry Recognition
- Convolutional Neural Network
- IoT
-
Teachable Machine Learning
- TensorFlow