Abstract: Journal of Agricultural, Earth and Environmental Sciences

Abstract:
According to the World Health Organization (WHO), each year, approximately 1.8 million people die from diarrheal diseases caused by contaminated water. Consuming contaminated water can transmit various diseases such as cholera, diarrhoea, dysentery and typhoid. This pressing global challenge of water contamination has shown the need for innovative solutions for the detection of harmful bacteria present in water sources. LOWEL AI (Learning from Observations to Improve Water Efficiency and Life) is emerging as a technological innovation aimed at revolutionizing water quality assessment by developing a machine learning model that can detect harmful bacteria present in water samples. This paper discusses the potential of LOWEL AI, an emerging research work that outlines the integration of machine learning algorithms, bioluminescent sensors and microscopic cameras to detect harmful bacteria present in water and predict future water conditions by the measurement and observation of certain molecules related to bacteria.