智慧城市中基于物联网的废水管理

Dr. Shwetha V, Keerthana S
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引用次数: 0

摘要

从排水或废水中提取和提炼污染物,使其能够在对环境造成最少负面影响的情况下回收到供水系统中的过程被称为废水管理。当前,环境状况日益恶化,因此有必要制定新的战略和策略,以确保智慧城市中安全、智能的废水管理系统。物联网(IoT)和无线传感器网络是处理废水的潜在技术。综合文献综述为基于物联网(IoT)的智慧城市污水管理系统(IoT- WMS)开发了一个利用区块链技术的概念框架。目前正在利用区块链技术存储信息,以创建一个促进废水再利用的激励计划。在智慧城市中,与回收废水的数量和质量相关的代币被分配给家庭和企业。然而,这经常会促使人们篡改用于发放这些代币的数据,以获得特殊利益。为了确定是否有证据表明物联网传感器数据被篡改,我们采用了异常检测技术。为了根据用户在小区的使用情况促进最有效的水分配,本研究提出了一种基于物联网和数据分析的水分配和综合管理系统。除了防止水资源浪费外,所建议的方法还有助于为宏观研究和城市规划收集用水统计数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IOT Based Wastewater Management in Smart Cities
The process of extracting and refining contaminants from drainage or wastewater so they can be recycled back into the water supply with the least amount of negative environmental impact is known as wastewater management. The current declining environmental condition necessitates the development of new strategies and tactics to guarantee safe and intelligent wastewater management systems in smart cities. The Internet of Things (IoT) and wireless sensor networks are potential technologies for treating wastewater. The comprehensive literature review develops a conceptual framework utilizing blockchain technology for an Internet of Things (IoT)- based wastewater management system in smart cities (IoT- WMS). Information is now being stored using blockchain technology to create an incentive scheme that promotes the reuse of waste water. In smart cities, tokens related to the quantity and quality of recovered wastewater are distributed to homes and businesses. However, this frequently promotes manipulating the data used to award these tokens in order to incorporate particular benefits. To determine whether there is evidence of altered IoT sensor data, anomaly detector techniques are employed. In order to facilitate the most efficient distribution of water depending on user usage at the plot holding level, this study suggests a water distribution and integrated management system based on the Internet of Things (IoT) and data analytics (DA). In addition to preventing water waste, the suggested approach would assist in gathering consumption statistics for macro-level research and town planning
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