Water-Quality-Assessment-using-Machine-Learning

For public health, safe and easily accessible water is important, whether it is consumed for drinking or consumed domestically, or used for food production or recreational activities. The improvement of water supply and sanitation as well as the better management of water resources can boost economic growth as well as alleviate poverty. A lack of, an insufficient, or a poorly managed water and sanitation system can result in transmission of diseases such as cholera, diarrhoea, dysentery, hepatitis A, typhoid, and polio. The proposed water assessment device has many sensors like pH , turbidity and TDS sensor which provides the parameters required for water quality assessment. These sensor data is sent to the microcontroller unit(Node-MCU) which sends the data to the firebase database. Google's mobile app development platform, Firebase, contains a number of services for managing data from iOS, Android, and web applications. In firebase with the help of ML kit we can deploy the machine learning models for water quality assessment and purity. The ML Kit mobile SDK provides Google's machine learning capabilities to Android and iOS apps in a sophisticated yet simple-to-use package. Whether you're new to machine learning or a seasoned pro, you can get the functionality you need with only a few lines of code. To get started, you don't need a lot of experience with neural networks or model optimization. If you're a seasoned machine learning developer, on the other hand, ML Kit provides easy-to-use APIs for integrating your bespoke TensorFlow Lite models into your mobile apps. This helps us to prevent people from having contaminated water and thereby help us to prevent a lot of water borne diseases.