Propositional modelling of a modus operandi to conduct manned mission to Venus apropos Beнepa Program data

The second-largest terrestrial object in the solar system is Venus, the second planet closest to the Sun. Up until a few of its mysteries were discovered by astrophysics in the mid-twentieth century, the terrain of Venus was indeed a matter of conjecture. Images taken by the Венера (Venera) space probes in 1975 and 1982 showed a surface that was coated in mud and had rather angular rocks. Venus has much more volcanism compared to any other planet within the Solar System, and they dominate its surface. 90% of its surface is made of basalt, and roughly 65% of the globe is covered in a tapestry of molten lava expanses, showing that magmatism was a significant factor in forming the stratosphere. There has been volcanism on Venus over the past 2.5 million years, however, there is no concrete evidence that a recent eruption of a volcano has occurred. A NASA plan from 1967–1968 called for sending three humans to Venus in an Apollo-derived spacecraft in 1973–1974 for a flyby mission, with a gravity assist to speed up the return trip to Earth. But, due to certain preparatory fallacies, the mission was not conducted. Recent advances in Deep Learning, Machine Learning, and Artificial Intelligence have greatly boosted technology. One of the most important contributions of this technique to mankind is Imagery Analysis. Data from the Soviet’s Venera space probes show the presence of volcanoes on the Venusian terrains. Subjecting to these, in this article, we would devise a model that could predict the presence of a Volcano on the patch of a surface on Venus. This would allow us to successfully conduct manned mission to Venus. The space probe would capture images of Venusian Terrain on reaching the Venusian Atmosphere and feed that to the pre-trained model for prediction. Thus, the region having chances of a volcano could be defied easily.