The AI-assisted removal and sensor-based detection of contaminants in the aquatic environment

Publisher:
Elsevier
Publication Type:
Chapter
Citation:
Artificial Intelligence and Data Science in Environmental Sensing, 2022, pp. 211-244
Issue Date:
2022-01-01
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3-s2.0-B9780323905084000058-main.pdfPublished version1.4 MB
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The most valuable resource on the planet is water, and the survival of life on earth is directly proportional to water, among other essential resources. Water also plays a critical role in the human body, wherein it adjusts the temperature of the body, cushions joints, conveys oxygen and nutrients to cells, defends tissues and organs, and eliminates wastes. While water covers 70% of the earth’s surface, nearly 97% of water resources are saline and inappropriate for direct human consumption. Around 2% is out of the way in glaciers and ice caps. Thus, it leaves only about 1% of total water resources available for human needs, such as farming, housing, industrial, municipal, and private necessities. Artificial intelligence (AI) is defined as the exhibition of human intelligence by machines, where machines can think and act like humans. AI was invented by John McCarthy in 1956 and obtained the greatest successes in the 90s and early 21st century, and now it is considered one of the emerging sciences. There are six general subsets for AI, i.e., machine learning, deep learning, robotics, expert systems, fuzzy logic, and natural language processing. Among those subsets, machine and deep learning and fuzzy logic have been more applied in water process engineering. The AI-assisted procedures can be applied in different aspects of process engineering for maintenance and operation, design, plant planning and optimization, configuration, training, computer-aided instruction, operator decision support, process control, simulation, alarm management, troubleshooting, and scheduling. Since there is quick simultaneous progress in both AI and molecular sciences, more importantly, there is a considerable convergence between these two fields; water process engineering is experiencing an unexpected transition from traditional procedures to AI-assisted procedures. In this chapter, the use of AI-assisted removal and sensings for four main emerging and traditional water contaminates including per- and polyfluoroalkyl substances, endocrine-disrupting chemicals/pharmaceuticals, disinfection by-products, and heavy metals will be discussed.
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