A Computer Vision-Based Water Level Monitoring System for Touchless and Sustainable Water Dispensing

Abstract

In recent years, the need for contactless and sustainable systems has become increasingly relevant. The traditional water dispensers, which require contact with the dispenser and often involve single-use plastic cups or bottles, are not only unhygienic but also contribute to environmental pollution. This paper presents a touchless water dispenser system that uses artificial intelligence (AI) to control the dispensing of water or any liquid beverage. The system is designed to fill a container under the nozzle, dispense water when the container is aligned with the flow, and stop dispensing when the container is full, all without requiring any physical contact. This approach ensures compliance with hygiene regulations and promotes environmental sustainability by eliminating the need for plastic bottles or cups, making it a “plastic-free” and “zero waste” system. The prototype is based on a computer vision approach that employs an RGB camera and a Raspberry Pi board, which allows for real-time image processing and machine learning operations. The system uses image processing techniques to detect the presence of a container under the nozzle and then utilizes AI algorithms to control the flow of liquid. The system is trained using machine learning models and optimized to ensure accuracy and efficiency. We discuss the development and implementation of the touchless water dispenser system, including the hardware and software components used, the algorithms employed, and the testing and evaluation of the system. The results of our experiments show that the touchless water dispenser system is highly accurate and efficient, and it offers a safe and sustainable alternative to traditional water dispensers. The system has the potential to be used in a variety of settings, including public spaces, hospitals, schools, and offices, where hygiene and sustainability are of utmost importance.