Smart IoT-based water treatment with a Supervisory Control and Data Acquisition (SCADA) system process

IF 4.3 4区 环境科学与生态学 Q2 ENGINEERING, ENVIRONMENTAL Water Reuse Pub Date : 2023-08-14 DOI:10.2166/wrd.2023.052
Dwarakanath B., Kalpana Devi P., Ranjith Kumar, A. S. M. Metwally, G. A. Ashraf, Bheema Lingaiah Thamineni
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引用次数: 0

Abstract

Water treatment is necessary to ensure the availability of clean and safe water for various uses. Integrating Internet of Things (IoT) technology with water purification systems has shown enormous potential in recent years for enhancing the efficiency and efficacy of the treatment process. Monitoring the disposal of sewage in treatment facilities is the primary obstacle. As a result, a Supervisory Control And Data Acquisition (SCADA) system, including the IoT, has been proposed to ensure the proper operation of these sewer systems and limit the risk of overflow and malfunction. In this paper, we suggest a novel approach that blends Deep Belief Networks (DBNs) with an IoT-based water treatment system equipped with a SCADA system for increased monitoring and control. An IoT–SCADA system can be implemented at various wastewater collection and treatment phases. Secondly, incorporating DBNs enhances the system's predictive capabilities, enabling proactive maintenance and decision-making to prevent potential failures and optimize resource allocation. The proposed technique computes the efficacy of the effluent treatment facility and ensures that chemical emissions do not exceed permissible limits. Furthermore, Complex Event Processing (CEP) can be utilized to evaluate and analyze the massive influx of real-time data sets provided by IoT sensors.
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基于智能物联网的水处理与监控和数据采集(SCADA)系统过程
水处理是确保各种用途的清洁和安全用水的必要条件。近年来,将物联网技术与水净化系统相结合,在提高处理过程的效率和功效方面显示出巨大的潜力。监测污水在处理设施中的处置是主要障碍。因此,提出了包括物联网在内的监控和数据采集(SCADA)系统,以确保这些下水道系统的正常运行,并限制溢流和故障的风险。在本文中,我们提出了一种新的方法,将深度信念网络(dbn)与基于物联网的水处理系统相结合,该系统配备了SCADA系统,以增强监测和控制。物联网scada系统可以在不同的废水收集和处理阶段实施。其次,集成dbn增强了系统的预测能力,实现了主动维护和决策,防止潜在故障,优化资源配置。所建议的技术计算出水处理设施的效率,并确保化学物质的排放不超过允许的限度。此外,复杂事件处理(CEP)可用于评估和分析物联网传感器提供的大量实时数据集。
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来源期刊
Water Reuse
Water Reuse Multiple-
CiteScore
6.20
自引率
8.90%
发文量
0
审稿时长
7 weeks
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