Artificial Intelligence and the Space Industry
In short, artificial intelligence is all kinds of technologies that enable computers to simulate human intelligence, such as computers that analyze data or systems embedded in a self-driving vehicle. AI systems are usually taught by writing a huge amount of complex software to enable computers with this software to perform various intelligent tasks without any human intervention.
Artificial intelligence can also be achieved through machine learning, which trains machines to self-learn, and this method boils down to “training” a relatively simple algorithm that becomes more complex over time, where huge amounts of data are inserted into the algorithm that modifies and improves itself by developing artificial neural networks. There is also a specialized technique within machine learning called deep learning, in which a computer uses multi-layered artificial neural networks to train itself for complex tasks such as image recognition, online translation services, and navigation systems for self-driving cars or spacecraft.
Artificial intelligence is one of the most important areas of future science because it forms the basis of computer learning, which has become an essential part in the formation of modern devices, as these devices have the ability to analyze and absorb a huge amount of data and use their acquired intelligence to make decisions in a relatively short time compared to the time it takes for humans, so artificial intelligence touches all fields from medical discoveries in cancer research to the latest research in climate change and smart devices in cars, planes and spacecraft It’s hard to ignore the impact of AI on our daily lives.
Among the areas where AI applications are being used most intensively are space and satellite construction and management, which includes relative positioning, communications, end-of-life management of the moon and other complex operations. Machine learning systems are also commonly used in space applications to approximate complex representations of the real world, especially in the analysis of huge amounts of Earth observation data or telemetry data from spacecraft, as artificial intelligence has become an important role in facilitating and managing these processes efficiently and accurately. The presence of machine learning systems in space missions has become widespread, for example Red Planet surface exploration vehicles have used artificial intelligence to navigate on their own and carry out various exploration and analysis operations.
Artificial intelligence has important and strategic contributions to the sustainability of the space sector, as it is used in the design of space missions to clean the Earth’s orbits of space debris that has become an increasing threat to the safety of spacecraft, in addition to monitoring the movement of space debris and making special calculations to predict the date and place of its fall to Earth. An important example of the use of AI applications in the space industry is the European Space Agency (ESA) Evolutionary Computation, which involves writing algorithms in a way that takes all the options of developments, retains the best results and rejects the worst results, as in the biological evolution of living organisms. One application of this study was the calculation of space trajectories and planetary trajectories. Machine learning has also been used in the field of spacecraft guidance, navigation and control, and the use of intelligent data transmission software used aboard Mars vehicles to avoid the loss of valuable data from human interventions and limit human supervision of various tasks. In addition, the European Space Agency has gained extensive experience in using artificial intelligence to extract valuable information from huge amounts of data, and this technology is implemented in many applications in our daily lives such as monitoring the number of cars in shopping malls, and predicting the financial and commercial performance, monitor climate change, and support police forces in their efforts to apprehend perpetrators, maintain security and monitor the health of the elderly and heart patients.
Earth observation is one of the areas in which artificial intelligence is widely used, such as the use of artificial intelligence to monitor economic indicators by integrating satellite data and artificial intelligence to monitor changes in production at a car manufacturer in Germany and aircraft traffic at Barcelona airport.
About a year ago, the first European Earth observation satellite was launched, designed according to the best of artificial intelligence, in the form of an electronic chip “ɸ-sat-1 AI chip” to improve the efficiency of sending huge amounts of data to Earth. The German Aerospace Center is also working on developing artificial intelligence methods for space and Earth applications, as it launched in 2018 a smart assistant “CIMON” that uses artificial intelligence to support astronauts in their daily tasks aboard the International Space Station, and this assistant is able to see, speak, listen, understand and even fly!
In order to achieve great and distinguished achievements, NASA collaborated with Google to train its intensive artificial intelligence algorithms to effectively sift data from the Kepler mission to search for signals from the transit of an exoplanet in front of its parent star, and this successful collaboration led to the discovery of two new exoplanets that scientists could not discover beforehand. After its initial success, the project is sifting data from other missions and missions to continue the search for new planets. The European Artificial Intelligence for Data Analysis (AIDA) project is using ESA and NASA data from across the solar system to develop an intelligent system for reading and processing space data, with the aim of detecting distinctions, identifying components and identifying new discoveries.
Artificial intelligence has contributed to the evolution of emerging technologies such as Big Data, robotics and the Internet of Things (IoT), and AI will continue to be a key driver of limitless technological innovations in the future. It is worth noting that 18 percent of the inventions registered during 2018 were related to artificial intelligence.
In this article, it is good to recall what Marc Gyongyosi, founder and CEO of Intelligent Flying Machines-IFM, specifically said: “People need to learn programming just as they learn a new language, and they need to do it as soon as possible because it’s really the future. In the future, if you don’t know how to craft cryptocodes and coding, you don’t know programming, and things will get harder.”
This technology has evolved significantly over the past two decades, but there is still difficulty in using artificial intelligence to complicate the models and structures necessary for machine learning, and the difficulty of adapting and lack of reliability in new programs that still need to be improved before it becomes useful and widely used in the space industry. But AI is expected to have a lasting impact on all sectors, and its impact will increase in many different industries in the near future.
* By NSSA Aerospace Engineer : Reem Senan