. "Artificial Intelligence"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "SatNEx School Bradford"@en . . . . "SatNEx School 2023 - Bradford - Public events - University of Bradford"@en . "Bradford, UK" . "NaN" . "Presential"@en . "About the School\nThis SatNEx School, organised by the Bradford-Renduchintala Centre for Space AI on Tuesday 24th to Thursday 26th October 2023, is focused on the applications of AI in satellite systems. The School brings together highly qualified speakers from industry, research, and academic institutions to discuss emerging applications, computing technologies, and dynamic design/processing techniques relevant to AI in various aspects of satellite systems operation. The content is designed to provide PhD students, early career researchers, and industry professionals with a firm grasp of the start-of-the-art and emerging trends in the subject.\n\nArtificial Intelligence (AI) for Satellite Systems\nInterest in the application of AI in various aspects of society has exploded within the last decade, and the field of satellite systems (and more generally space technologies) is no exception.\n\nAI enables optimal decisions and resource management to be achieved within a complex and dynamic space environment. AI facilitates the detection of historical patterns to predict what is likely to happen next (for example solar storms, intense rain events, traffic demand, etc).\n\nThis is important because it enables the instigation of proactive rather than reactive measures to avoid disruption and ensure service reliability and quality as well as system resilience.\n\nIn-orbit deployment of AI to extract essential information from the huge amount of raw data collected in space provides the option of transmitting only the most relevant data subset down to earth. This would greatly reduce the amount of signal power and radio spectrum required for data transmission from space to earth, thus enabling us to use space more sustainably and intelligently.\n\nThese and other benefits and applications of AI in satellite systems (e.g, for ground segment operations and payload design) will be explored in detail along with discussions of related topics of federated learning, edge computing, and distributed satellite systems." . "0.15" . "NaN"@en . . . "University of Bradford"@en . "Bradford, UK"@en . "no data" . "no data" . "149"^^ . "no data"@en . . "English"@en . . "Spacecraft Engineering"@en . . . . . . . . . . . . . . . . .