| Type of Material: | Thesis |
| Title: | investigation on desalination system through machine learning and internet of thing approach |
| Researcher: | Shrimali, Neelkumar Sumanlal |
| Guide: | Patel,Vijay K |
| Department: | FACULTY OF ENGINEERING AND TECHNOLOGY |
| Publisher: | Ganpat University |
| Place: | Mehsana |
| Year: | 2023 |
| Language: | English |
| Subject: | Engineering | Engineering and Technology | Engineering Electrical and Electronic | Electronics and Communication Engineering | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; FACULTY OF ENGINEERING AND TECHNOLOGY, Ganpat University, Mehsana; 2023; 20276351001 |
| Fulltext: | Shodhganga |
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| 001 | 455352 | |
| 003 | IN-AhILN | |
| 005 | 2024-09-25 09:50:11 | |
| 008 | __ | 240925t2023||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_455352 |
| 040 | __ | |aGANU_384012|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aShrimali, Neelkumar Sumanlal|eResearcher |
| 110 | __ | |aFACULTY OF ENGINEERING AND TECHNOLOGY|bGanpat University|dMehsana|ein|0U-0132 |
| 245 | __ | |ainvestigation on desalination system through machine learning and internet of thing approach |
| 260 | __ | |aMehsana|bGanpat University|c2023 |
| 300 | __ | |a8933 kb|dDVD |
| 500 | __ | |aDesalination; IoT; Machine learning; water; Sensors |
| 502 | __ | |cFACULTY OF ENGINEERING AND TECHNOLOGY, Ganpat University, Mehsana|d2023|o20276351001|bPhD |
| 518 | __ | |d2024|oDate of Award |
| 518 | __ | |oDate of Registration|d2020 |
| 518 | __ | |oDate of Viva-voce|d2023-12-30 |
| 518 | __ | |oDate of Notification|d2023-12-30 |
| 520 | __ | |aDesalination, which is the process of removing salt and other pollutants from seawater or brackish water in order to produce freshwater, is an essential component in the fight against water scarcity issues that are prevalent all over the world. In recent years, the incorporation of Machine Learning (ML) and the Internet of Things (IoT) technologies has revolutionized the desalination sector by increasing the efficacy and sustainability of desalination systems. This has led to a significant increase in the demand for desalinated water. This inquiry focuses on the application of machine learning (ML) and internet of things (IoT) in desalination operations, providing an in-depth analysis of their potential benefits and problems.Thesis starts off by reviewing the fundamental concepts of several desalination techniques, such as multi-effect distillation and reverse osmosis, and highlighting the essential aspects that affect the performance of these techniques, such as energy consumption, membrane fouling, and s |
| 650 | __ | |2UGC|aElectronics and Communication Engineering |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aEngineering |
| 653 | __ | |aEngineering and Technology |
| 653 | __ | |aEngineering Electrical and Electronic |
| 700 | __ | |aPatel,Vijay K|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/545474|yShodhganga |
| 905 | __ | |afromsg |
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