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BB category SCOTT:SW component  +
Baseline This Building Block will start from the CoThis Building Block will start from the Context-aware and reasoning module developed in DEWI, which included the following main components: communications interface (RESTful API, JSON); Big Data storage (HDFS Hive); distributed computing (Spark); Big Data Analytics (Spark MLLib, H2O); alerts engine (WSO2 Complex Event Processor); and front-end (AngularJS, NodeJS, SailsJS). DEWI applied machine learning techniques based on deep learning to predict future measurements and to detect anomalies. SCOTT will adapt the platform’s communication interfaces; data preparation modules; and data analytics techniques according to the new use cases needs. In addition, SCOTT will extend this platform with further data analytics techniques for optimization purposes.tics techniques for optimization purposes.  +
Current TRL 4. In this Building Block, different SW components designed in DEWI will be integrated and adapted to new use cases, and extended with new functionality.  +
Description This building block will develop a ContextThis building block will develop a Context-aware and reasoning platform based on Big Data cloud architecture able to store and process large amounts of data collected by sensors. The platform will apply and adapt the suitable Big Data services for data analytics, essentially based on machine learning techniques, to predict future sensors measurements, to detect anomalies on current sensors measurements, and to optimize processes or configurations of devices.ze processes or configurations of devices.  +
Lead partner Instituto Tecnologico de Informatica  +
Leader Antonio Lagarda  +
Main output This building block will be a software plaThis building block will be a software platform able to ingest data collected by sensors, analyse them and provide the analyses results to external applications. This platform will be composed of different components, integrated and modified to achieve the expected result in the destination scenarios and use cases. It will integrate scalable, robust and reliable technologies to store and process large amounts of data. Machine learning techniques will be applied for future values prediction, data anomalies detection, and optimization. The prototype will be tested and demonstrated in some use cases.tested and demonstrated in some use cases.  +
Page Title BB24.D Big Data Analytics  +
Partner Instituto Tecnologico de Informatica  +
Target TRL 6. A prototype Big Data Analytics platform will be implemented and demonstrated in selected use cases.  +
Technology Line SCOTT:Distributed Cloud Integration  +
Title Big Data Analytics  +
Workpackage SCOTT:WP07  + , SCOTT:WP09  + , SCOTT:WP11  + , SCOTT:WP15  +
Creation dateThis property is a special property in this wiki. 16 June 2017 20:08:39  +
Categories Building Block  +
Modification dateThis property is a special property in this wiki. 13 July 2017 17:45:38  +
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