SMARTHEP · Synergies between Machine leArning, Real Time analysis and Hybrid architectures for efficient Event Processing and decision making

SMARTHEP: Synergies between Machine leArning, Real Time analysis and Hybrid architectures for efficient Event Processing and decision making

The analysis of data plays a huge role in decision-making for many industries and continual advances means that in order to stay competitive, many organisations rely on using data to make more informed decisions about their customers, competitors, products and services. Organisations leveraging data available to them can be the difference between them keeping up with their competitors and remaining relevant to their customers. The volume of data available to research and industry is increasing at an exponential rate. The increase in data collection is not always matched by comparable data storage, utilisation and analysis capabilities. This means that most data produced is either discarded, not recorded or recorded and stored without being analysed. High Energy Physics (HEP) experiments have the ability to produce hundreds of gigabytes of data per second. Current resources and the time taken to make decisions about the data are not scaled to adequately process and utilise this data. In order to make the most of the data in a cost-effective way, data-taking and data-analysis needs to become more efficient. The training of a new generation of researchers to work towards Real-Time Analysis is part of the solution needed to deliver this paradigm shift. Synergies between Machine learning, Real-Time analysis and Hybrid architectures for efficient Event Processing and decision making (SMARTHEP) is a European Training Network (ETN) with the aim of training a new generation of Early Stage Researchers (ESRs) to use real-time decision-making effectively leading to data-collection and analysis becoming synonymous. SMARTHEP brings together scientists from the four major collaborations which have been driving the development of Real-Time analysis (RTA) and key specialists from computer science and industry. By solving concrete problems as a community, SMARTHEP will bring forward a more widespread use of RTA techniques, enabling future HEP discoveries and generating large-scale impact to industry.In addition ESRs will contribute to European growth exploiting their hands-on work to produce concrete commercial deliverables in fields that can most profit from RTA, such as transport, manufacturing, and finance.

Data: CORDIS, © European Union