AI Modeling and Water Quality Sensing Technique Proffers Water Security: An Open Review

Water Quality Sensors (WQSs) are becoming a promised tool in water quality data assessment and scientific value of aquatic structure. Such sensors are broadly used to produce live results by evaluating major water quality parameters and components. Artificial intelligence (AI) based WQSs and machine learning (ML) algorithms primarily enable long term operations for real time detention of water quality information at different time periods. Messaging services, alarms, alerts and other proper warnings are given to water quality managers or assessing communities while the quality deterioration occurs at the particular water quality checking sites. A good number of impressive challenges are identified in hosting the variety of sensors to manage, warehouse and analyze incessant water quality information that they generate periodically. This paper places interests in highlighting lack of suitable assessment standards and determine logistical deliberations for fruitful implementations together with transportation, storage services and appropriate trustworthy communication. The main objective is to identify the designs targeting water security that support to monitor, reassure and protect the water resources all the way through uninterrupted quality supervision in addition to AI features. This open review also discusses a variety of applications in water quality sensors, AI modeling, electronic tongues and indices, hence results the knowledge of improvement required for upgrading the quality in water resources through computer technologies and models.