A team of scientists selected by NASA last year has just submitted a report with recommendations for studying unidentified aerial phenomena. She advises in particular to improve data collection and increase sources in order to be able to use AI to detect anomalies.
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Last year, NASA announced the formation of a team of 16 experts working in different fields to look into what it calls unidentified anomalous phenomena (UAP). In French, the term used is unidentified aerospace phenomenon (PAN), and notably includes UFOs. The NASA team has just made a report who is interested in ways to study these phenomena scientifically.
The report recommends the use of artificial intelligence to analyze data collected around these phenomena. The idea is to build a model of all phenomena considered normal which would be used to train a neural network, and then use this AI to report any deviations. However, this approach currently faces a data quality problem.
Insufficient data quality to fully use artificial intelligence
The report indicates that one of the problems is that these phenomena are most often detected by instruments which were not designed for this use, and therefore do not provide the necessary data which would allow them to be identified. In addition, the archiving and curation of this data is most often insufficient. The team recommends the use of “ open source resources, extensive technology expertise, data analysis techniques, federal and commercial partnerships, and Earth observation tools to build a better and more robust dataset for understanding future NAPs “. In other words, NASA should create a system to collect and combine data from its own satellites as well as commercial satellites.
Finally, the scientists also suggest that NASA should rely on reports from commercial pilots and develop an application to allow witnesses to share images and data from other sensors on their smartphone in order to multiply sources.
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