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DOI | 10.1109/ACCESS.2024.3384607 |
Blockchain-Orchestrated Intelligent Water Treatment Plant Profiling Framework to Enhance Human Life Expectancy | |
发表日期 | 2024 |
ISSN | 2169-3536 |
起始页码 | 12 |
卷号 | 12 |
英文摘要 | Water quality degradation has turned out to be of crucial importance due to various factors over the past decade. Pollution, climate change, and population growth are the factors that affect water quality. Contaminations such as microorganisms, heavy metals, and excessive nitrogen and phosphorous disrupt water pH levels, posing significant health risks. Despite the innovation in the Internet of Things(IoT), allowing balancing the pH by adding chlorine and fluoride after the disinfection step, several security issues(e.g., distributed denial of service, data manipulation, and session hijacking) manoeuvre the operational performance of the water treatment plants. This causes people to consume polluted water, which has many adverse effects on human health and reduces life expectancy. To address this critical concern, we propose a novel approach integrating artificial intelligence(AI) and blockchain technology into water treatment plant management. Our methodology utilizes a standard water quality dataset, which has features such as pH and total hardness, which is used for binary classification, indicating water as potable or not potable. We employ various AI classifiers such as stochastic gradient descent classifier (SGDC), decision tree (DT), Naive Bayes (NB), K nearest neighbours (KNN), and logistic regression (LR). Furthermore, an InterPlanetary File System(IPFS)-based public blockchain is integrated to resist the data manipulation attack, where the potable water sample is securely stored in the blockchain's immutable ledger. The proposed model is evaluated using various performance metrics such as confusion matrix analysis, learning curve assessment, training accuracy, and blockchain scalability. Notably, the DT model emerges as the best-performing classifier with an accuracy of 99.41% and scalability of 35 with 120 data transactions. |
英文关键词 | Artificial intelligence; water treatment plants; water profiling; blockchain; Internet of Things (IoT); IPFS |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
WOS类目 | Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications |
WOS记录号 | WOS:001199997200001 |
来源期刊 | IEEE ACCESS
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文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/299351 |
作者单位 | Nirma University; Universita Kore di ENNA; University of Johannesburg; King Saud University; King Saud University |
推荐引用方式 GB/T 7714 | . Blockchain-Orchestrated Intelligent Water Treatment Plant Profiling Framework to Enhance Human Life Expectancy[J],2024,12. |
APA | (2024).Blockchain-Orchestrated Intelligent Water Treatment Plant Profiling Framework to Enhance Human Life Expectancy.IEEE ACCESS,12. |
MLA | "Blockchain-Orchestrated Intelligent Water Treatment Plant Profiling Framework to Enhance Human Life Expectancy".IEEE ACCESS 12(2024). |
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