Abstract:
It's critical for the growth of the fetus as well as the health of the mother to get enough
nutrients throughout pregnancy. Women need special attention throughout pregnancy.
Maintaining a balanced diet and sufficient nutrient intake are essential. Unfortunately, a
significant percentage of Bangladeshis are unaware of this issue. The people that suffer the
most are new moms, as they have never encountered this circumstance before. Major
pregnancy issues might result from an unbalanced diet and incorrect fruit consumption at
this period. To overcome this challenge, we applied a deep learning technique called You
Only Look Once (YOLOv8) to identify and categorize various fruit varieties. A varied
dataset of foods pertinent to prenatal nutrition is used to modify and train the YOLOv8
model, which is well-known for its real-time object identification skills. The system's goal
is to make it easier for expectant mothers to keep an eye on their food consumption and
encourage a nutritious, well-balanced diet for the duration of their pregnancy. We have
separated our eight fruit classes into two main groups according to whether they are
avoided or useful. We obtained data about fruit eating during pregnancy from online health
journals and papers as well as gynecologists. Reading our article will help people
understand which of our eight fruit types to consume and which to avoid. Pre-trained
YOLOV8 models were implemented. This study contributes to the field of maternal
healthcare by providing expectant mothers with a novel tool that facilitates informed
dietary decisions. The YOLOv8-based food detection technology enhances maternal and
fetal health outcomes while also increasing knowledge of nutrition. Further research
endeavors might concentrate on enhancing the efficacy of the model, integrating
customized nutritional suggestions, and investigating its utilization in more comprehensive
healthcare settings.
