Abstract：
The two main things needed to fulfill the world\'s impending need for water in the face of the widespread water crisis are collecting water and recycling. To do this, the present study has placed a greater focus on water management strategies used in a variety of contexts areas. To distribute water effectively, save it, and satisfy water quality requirements for a variety of uses, it is imperative to apply intelligent water management mechanisms while keeping in mind the population density index. The present review unveiled the latest trends in water and wastewater recycling, utilizing several Artificial Intelligence (AI) and machine learning (ML) techniques for distribution, rainfall collection, and control of irrigation models. The data collected for these purposes are unique and comes in different forms. An efficient water management system could be developed with the use of AI, Deep Learning (DL), and the Internet of Things (IoT) structure. This study has investigated several water management methodologies using AI, DL and IoT with case studies and sample statistical assessment, to provide an efficient framework for water management.
摘要：
面对广泛的水危机，要满足世界对水的迫切需求，需要做的两件主要事情是收集水和循环利用。要做到这一点，本研究更加关注各种环境领域中使用的水管理策略。为了有效地分配水，拯救它,满足各种用途的水质要求，必须在牢记人口密度指数的同时应用智能水管理机制。本次审查揭示了水和废水回收的最新趋势，利用几种人工智能(AI)和机器学习(ML)技术进行分发，雨水收集,和灌溉模型的控制。为这些目的收集的数据是独特的，形式不同。可以使用AI开发有效的水管理系统，深度学习(DL)和物联网(IoT)结构。这项研究调查了几种使用人工智能的水管理方法，具有案例研究和样本统计评估的DL和物联网，为水管理提供有效的框架。
