Cloud Based Software Platform for Big Data Analytics In Water Reservoir Level Forecasting
| Autor: | S. Pandiaraj, J. Jagadeesan, Prashant Shrivastava |
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| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | IOSR Journal of Computer Engineering. 16:17-20 |
| ISSN: | 2278-0661 2278-8727 |
| DOI: | 10.9790/0661-16271720 |
| Popis: | Advanced technology solutions will help in scaling implementation, to accommodate a lot of data and data analysis capabilities while not affecting the performance. Data analytics in the field of water resource management is been seen as the new area of study that may facilitate in optimally managing the provision of water based on availability. Cloud platform will reduce the cost of maintenance singly in isolated environments and with the application of big data will help in activity the data analytics fast. Exploitation technologies to display user friendly analytics results graphically and serving to in foretelling add feather in the cap for this architecture. Reservoirs forms the rear bone of the facility inside cities will significantly help the facility department’s team in formulating advanced attending to manage the facility optimally if forecasted properly. The projected solution in this article helps in building a scalable software system platform for water reservoirs levels data analysis for foretelling future levels exploitation cloud based platform through massive data technologies landscape. The aim of this study is to develop models for predicting water levels in any reservoir. It applies Autoregressive Integrated Moving Average (ARIMA) algorithmic rule for creating predictions. It stores the historic huge data set inside massive information storage and uses big data technologies to review behavior and predict the future levels by applying data-driven analytics and data mining concepts. |
| Databáze: | OpenAIRE |
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