An Empirical Analysis of Various Techniques of Solving Obstacles through Artificial Intelligence

In the space sector, artificial intelligence (AI), and especially machine learning (ML), is becoming more and more popular. These days, ML algorithms are extensively used in many different contexts, including operational control of satellite constellations, autonomous navigation, and spacecraft health monitoring. There are two main types of surveys that are now available on AI applications in space missions, each with certain drawbacks. Generally speaking, the first category is out of date since it does not include more recent advancements like Deep Learning (DL) and bioinspired AI algorithms. On the other hand, the second group tends to be too detailed and concentrates only on certain AI approaches, which can put off those who are looking for a more comprehensive knowledge, especially those with technical expertise in other subjects. In order to rectify these deficiencies, we provide a succinct summary that provides a thorough understanding of the uses and difficulties of AI in the space sector. Our study covers classical AI approaches used in several space mission disciplines, emphasizing their usefulness in real-world applications rather than going into formal methodologies. We also investigate bioinspired AI algorithms and point out possible uses for them. Beyond technical obstacles, we recognize and talk about significant legal ramifications of using AI in space projects. We expand our evaluation to include developments in Blockchain and Internet of Things (IoT) technology in the consideration of future directions. Specifically, we highlight how AI and Blockchain are convergent and pinpoint three major application fields in the space community that stand to gain a great deal from this convergence. These areas include satellite communications, spacecraft data security, and the Internet of Things in Space (IoST). Our review strives to be a useful tool for anyone interested in learning more about the complex world of artificial intelligence applications in space by looking at both regulatory and technological developments.