Abstract:
With the rise of deep learning and the improvement of computer vision, object recognition
has become a popular study topic. This is mostly because of convolutional neural networks
(CNNs). By using a lot of labeled data, CNNs have shown that they are good at finding and
predicting things in pictures. This project uses this skill to solve a common health mistake made
by office workers: not drinking enough water every day. The Ministry of Health stresses how
important it is to drink enough water for your body weight. Still, many workers forget about this
health tip because they are too busy with their daily work.
The main goal of this project is to set up a real-time object recognition system that will tell
these people to drink water at the right time. Built on the flexible TensorFlow framework, the
system is designed to be as efficient as possible, so it can work even on machines with less
powerful hardware. The only thing you need to use it is a webcam, which makes it a useful and
easy-to-use option.
The project was inspired by real-life experiences during an internship. It also takes into
account the fact that workers often don't drink enough water because of their busy work schedules,
even though they work in air-conditioned settings that make thirst worse. This mistake can lead to
health problems like dehydration, heart problems, and stomach problems. The suggested system
is meant to fit right into their work surroundings, reminding them to drink water regularly and
helping them live a better life at work. By combining cutting-edge technology with a basic health
need, this program aims to get people to drink more water, which will improve their health and
comfort at work in the long run.
