An AI system will process a data flood

Madrid and other parts of Spain are being filled with cameras with artificial intelligence (AI). The City Council of the aforementioned city has been expanding its ambitious video surveillance system, focusing on points of great influx of public roads. But the expansion of these technologies does not stop there. In parallel, Renfe is developing an intelligent security system, where algorithms play a key role. Cameras in more than 400 vicinity stations. The rail transport company The installation has ended of an intelligent video surveillance system in 415 seasons of vicinity throughout Spain. The same has several pieces, among which IP cameras, CCTV recorders, video analytics servers and, as we said, algorithms of AI that give life to what they have called “spaces of high predictive security.” How does the new Renfe smart video surveillance system work? Traditional video surveillance systems depend on human supervision: it is the operators who must identify situations that require intervention. However, technology is reliefing this load when analyzing images in real time and sending automatic alerts to security centers when necessary. In the case of Renfe, the cameras are connected to the analytical servers of each station, in charge of detecting maximum afor and agglomerations. In addition, they allow identifying those who try to sneak into the accesses, falls in platforms or roads, fires and acts vandalism such as graffiti or damage to the furniture. The alerts arrive directly to the 24 -hour Safety Center of Renfe, promising to speed up the response to incidents. The rail operator recognizes that her security system had been obsolete. Although it had thousands of cameras spread over hundreds of stations, they lacked the technology necessary to integrate into the new monitoring system. To solve this limitation, the RS3 project (Renfe Smart Security Station) was launched, whose first phase has just concluded and whose second phase will begin in March. A millionaire investment. The project has a budget of more than 32 million euros and aims to modernize 597 stations distributed among the 12 Cercanías and Rodalies nuclei. The first phase, already completed, has been an investment of 25.8 million euros, while the second, which will cover the renewal of the systems in 182 additional stations, will have a budget of 6.5 million euros. Financing comes from the NextGeration funds of the European Union. What about the data collected? Every time there is talk of data collection, the doubt about the impact on user privacy arises. This makes sense if we take into account that European legislation is very strict in this regard. Renfe’s new video analytics system manages a large amount of data, but the company says it has taken measures to comply with the existing regulations. The system collects video images anonymously. Does not capture or record audio. Nor is biometric data. Processing is performed automatically with AI. The data collected are eliminated after “milliseconds.” In the case of the standard video surveillance system, the images are preserved last a maximum period of one month. The company’s privacy policy for your video analytics system states that users can exercise their rights, including the right to oblivion, opposition, suppression or limitation of data processing, sending an email to rights.viajeros@renfe.es. In addition, it offers A detailed map with the stations that already have the new security system. Images | Renfe (1, 2, 3) In Xataka | Facial recognition has been expensive for an Alicante company: a fine of 220,000 euros for signing with biometry

We have dedicated six years to process images of a black hole to reach a conclusion: Einstein was right

Several years have passed since the Telescope of the Event Horizon (EHT) published the famous first image of a black holetaken in 2017. The photo has yes doquestioned by some researchersbut the EHT last year published a second image of the black hole M87*, taken in 2018. The new photo not only validated the original, but once again corroborates the Einstein’s general relativity theory. The largest radio telescope. To obtain the image of the black hole in the center of the Messier 87 galaxy, we needed to build a radio telescope about 10,000 kilometers in diameter. Since the land has a diameter of 13,000, the EHT took a more reasonable path: Extract data from different receptors, telescopes and radio antennas from all over the world and combine them by interferometry. The EHT produced 250 Petabytes of information in a one -week interval. It took a couple of years to process all the information and publish an image. But first, he added a new telescope to the project (the GLT of Greenland) and took the second image of M87* that saw the light in 2024. Six years processing. The second image of the black hole M87*, taken a year and ten days after the original, in April 2018, took six to process and publish, but it was worth it. On the one hand, proves that 2017’s observations were fine. The Persistence of the size of the central shadow In both images confirms the original estimate of the dimensions of the black hole, dissipating the criticisms about the simulations dependence to calculate this data. On the other, comparing the two images shows that the ring of matter around the black hole is rotating as expected. The brightest part has moved 30 degrees, which is consistent with the models of the hole. We are seeing what Einstein predicted. Located 55 million light years from us, M87* is a supermassive black hole in the center of an elliptical galaxy that manipulates the subject with its magnetic fields and expels the one that does not consume at speeds close to that of light. The image of 2018, like its predecessor of 2017, reflects this tumultuous activity with a bright ring around it. This validates the theory that the diameter of the event horizon, and therefore that of the black hole itself, is intrinsically linked to its mass, framing a central shadow that Albert Einstein’s equations predicted more than a century ago. Why it looks like a donut. That brilliant donut called accretion disc should be very fine, but we get very dispersed and unemployed. Throughout the trip he has made through space, his light has dispersed by the dust in interstellar space, which leads us to see it in this way. Despite the dispersion, the image is clear enough to confirm not only Black hole rotation but also the alignment of its rotational axis with a powerful stream of material (“relativistic jet”) that moves away from M87. The importance of reproducing results. Although it will take six years to arrive, this vindic confirmation the findings of the EHT and is seen as a milestone for global scientific collaboration, in addition to a robust confirmation that we are facing the shadow of a black hole and the matter that orbit it. Future data analysis will help better understand how magnetic fields and plasma flows within the accretion disc interact. In the next decade, we could even have videos of the evolution of M87* in time thanks to the next generation program of the EHT (NGEHT), which promises images of greater resolution and a broader range of frequencies. All thanks to the collaboration of observatories from all over the world. Image | Event horizon telescope In Xataka | A group of astrophysics has knocked down Kerr’s hypothesis. Black holes are still a source of surprises In Xataka | There is water since the beginning of time: NASA has found 140 billion oceans to 12,000 million light years *An earlier version of this article was published in February 2024

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