SYSTEMS AND METHODS FOR BABY BOTTLE MANUFACTURING

Smart overview of the Invention

The disclosed invention focuses on customizing baby bottle nipples by replicating the shape of a user's nipple using advanced technology. The process begins with scanning the user's nipple through a computing device to create a scan image. This image is processed using a machine learning engine to identify and highlight the nipple's features. A genetic algorithm is then applied to this output to generate a 3D image, which serves as the profile for the custom baby bottle nipple. This 3D image is transmitted to another device for 3D printing, resulting in a bottle nipple that closely replicates the user's own.

Field of Invention

The invention pertains to feeding devices for infants, with an emphasis on creating customized nipples for baby bottles. This customization addresses common challenges such as latching difficulties and other feeding issues that may arise due to health reasons or when caregivers other than the mother are feeding the baby.

Methodology

The method employs machine learning and genetic algorithms to accurately replicate the user's nipple. The machine learning engine, once trained with relevant images, identifies the nipple within scan images or videos. If identification is unsuccessful in any frame, users are prompted to rescan. A point cloud is created by stitching these frames together, and genetic processes refine this into a precise 3D model oriented along specific axes for optimal replication.

Technological Integration

Artificial intelligence plays a crucial role in optimizing the scanning and replication process. Various types of neural networks such as convolutional neural networks are used for object detection within the scans. The scanning process can be conducted at home using mobile devices equipped with structural light sensors, leveraging facial recognition technology to ensure accurate and comprehensive scans.

Applications and Embodiments

The invention provides solutions to mitigate nipple confusion in infants by making bottle nipples resemble natural ones more closely. It offers platforms that enhance scan quality and integrate AI-driven techniques for precision. The invention's modular nature allows for combining various embodiments without deviating from its core objectives, ensuring flexibility and adaptability in different use cases.