Effects of Water Quality Deterioration and the Application of Artificial Intelligence and Blockchain Technology

In the recent past, water quality deterioration has emerged as a more pressing concern than before because of pollution, climate change, and population increment among others. Among them are; Since microorganisms, heavy metals and tests of nitrogen and phosphorus alter the PH levels of water it becomes a significant health hazard. Even though some IoT innovation, such as pH balancing with chlorine & fluoride after disinfection is available, water treatment plants’ security threats include, DDoS, data tampering, session hi-jacking. These vulnerabilities contribute to the provision of contaminated water that has a negative health implication to man, and hence shortens his/her lifespan. To address these issues, this paper presents an innovative approach where AI combining with blockchain addresses the problems with water treatment management.This idea entails employing a standard water quality dataset that contains features like pH and total hardness and the target variable being a binary classification of water as either potable or non-potable. Our AI classifiers at hand include Stochastic Gradient Descent Classifier (SGDC), Decision Tree (DT), Naive Bayes (NB), K-Nearest Neighbours (KNN), and Logistic Regression (LR). Moreover, an Interplanetary File System (IPFS) based public blockchain is also embedded to mitigate data manipulation attack where potable water data is stored in the blockchain’s public ledger. Among the evaluation criteria, it is possible to name the confusion matrix analysis, the evaluation of the learning curve, the training accuracy, and the scalability of the blockchain. Also, it is evident that the Decision Tree (DT) classifier reveals the highest results with a score of 99. 40% and scalability that would allow 120 data transactions with a score of 35.