Application of Artificial Intelligence in Wastewater Treatment
This book offers a comprehensive exploration of the integration of artificial intelligence (AI) techniques in addressing challenges and optimizing processes within wastewater treatment. The coverage of the book spans a spectrum of applications, including AI-driven monitoring and control systems, pre...
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| Format: | Electronic eBook |
| Language: | English |
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Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| Edition: | 1st ed. 2024. |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-031-69433-2 |
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| 245 | 1 | 0 | |a Application of Artificial Intelligence in Wastewater Treatment |h [electronic resource] / |c edited by Shikha Gulati. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2024. | |
| 300 | |a 1 online resource (XIX, 319 p. 89 illus.). |b 81 illus. in color. | ||
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| 337 | |a computer |b c |2 rdamedia | ||
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| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
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| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
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| 505 | 0 | |a Introduction -- Overview of AI Application in diverse fields -- Fundamentals of Artificial Intelligence in wastewater treatment -- Potential of AI optimization in wastewater treatment processes -- Real Time Analysis for Smart Sensor -- Automated Water Control System in Wastewater Treatment plants -- Predictive Modeling for Pollutant removal: Machine learning -- Algorithms for Predictive Analysis -- Case Studies and Success Stories of AI Implementation in Wastewater Treatment -- Environmental Sustainability, Compliance & Life Cycle -- Assessment of AI-Integrated Systems -- Emerging AI Technologies in Wastewater Treatment -- Regulatory framework and standards for adapting AI Systems, Interplay between AI and Environmental policies -- Recommendations for implementation of AI, Steps toward industry wide Adoption -- Conclusions and future prospects of AI in wastewater treatment. | |
| 520 | |a This book offers a comprehensive exploration of the integration of artificial intelligence (AI) techniques in addressing challenges and optimizing processes within wastewater treatment. The coverage of the book spans a spectrum of applications, including AI-driven monitoring and control systems, predictive modeling for pollutant removal, and the development of smart sensor networks for real-time data analysis in wastewater treatment plants. By amalgamating AI methodologies with wastewater treatment processes, the book provides insights into enhancing efficiency, reducing costs, and mitigating environmental impacts. In the current research scenario, the theme of the book is highly pertinent as it responds to the pressing need for sustainable and efficient wastewater treatment solutions. The book defines the theme by elucidating how AI technologies, such as machine learning algorithms and data analytics, can revolutionize wastewater treatment processes by enabling proactive decision-making, optimizing resource allocation, and predicting potential system failures. This intersection of AI and wastewater treatment not only addresses operational challenges but also contributes to the broader goal of achieving environmentally conscious and economically viable solutions. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Water. | |
| 650 | 0 | |a Hydrology. | |
| 650 | 0 | |a Refuse and refuse disposal. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Sustainability. | |
| 650 | 0 | |a Environmental management. | |
| 650 | 1 | 4 | |a Water. |
| 650 | 2 | 4 | |a Waste Management/Waste Technology. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Sustainability. |
| 650 | 2 | 4 | |a Environmental Management. |
| 700 | 1 | |a Gulati, Shikha. |e editor. |0 (orcid)0000-0002-1894-9842 |1 https://orcid.org/0000-0002-1894-9842 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
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| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031694325 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031694349 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031694356 |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-69433-2 |
| 912 | |a ZDB-2-EES | ||
| 912 | |a ZDB-2-SXEE | ||
| 950 | |a Earth and Environmental Science (SpringerNature-11646) | ||
| 950 | |a Earth and Environmental Science (R0) (SpringerNature-43711) | ||