AI is also a suitable tool for space and aerospace technology.

AI is also a suitable tool for space and aerospace technology.

The potential for language models or chatbot-AI is impressive. The ability to give commands by using natural spoken language is the thing that makes many things easier. And one place where that thing is extremely great advanced space technology. If operators can give satellites orders to change trajectories or avoid something that thing makes it easier to control satellites.

It's possible. That satellites can have the AI that warns them of incoming space debris. The same system can warn and make satellite do the evasion and escape maneuvers if the suspected killer satellite or some other ASAT system comes too close or approach the satellites. The satellite that can automatically avoid impacts with debris can avoid impacts with ASAT weapons or at least kinetic energy ASAT. The AI is the tool that makes the satellite recognize dangerous situations and avoid them.

And one of the biggest threats to those satellites is space debris or ASAT weapons. The impact of space debris can destroy satellites always. And it's the same if it's an accident or made for purpose. In some scenarios, the other satellites will driven to impact course to GPS and strategic communication satellites.

In longer distances, the AI is a necessary tool. Space probes that operate in the asteroid belt and farther require advanced AI that makes them detect the right asteroid. The networked space probes can cooperate in those missions. One will make the close passing.

"SONATE-2, a nanosatellite developed by JMU, is scheduled for launch in March 2024 to test novel AI technologies and other advanced systems in space. Managed from JMU’s Mission Control Centre, it aims to enhance autonomous space exploration capabilities, with significant student involvement in its development and operation". (ScitechDaily.com/SONATE-2’s Space Odyssey: Testing AI’s Limits in Space)

The nanosatellites swarm can observe things like Van Allen belts and the magnetosphere. The swarm of nanosatellites can observe large land areas. Those satellites can detect the ICBM launches. The miniature satellites can also detect military satellites and terminate those satellites by impacting them.

And others follow that action over longer distances. The interaction and cloud-neural applications allow other probes can share their calculation power with close-flying probes. That makes the operation more effective. Also, the data that the longer distance probes share can help to make the probe make more accurate maneuvers and search the most interesting places on the asteroid's surface.

In space, the deep neural network can interconnect satellites in its entirety. Other satellites in that entirety can search and follow the satellite that is under threat. If impact happens the image analysis allows us to make conclusions if the satellite is destroyed on purpose or accidentally. If something stresses the low-orbiting satellites the other satellite can point its camera to the point, where the stress comes from.

The deep neural network can make aviation safer. The idea is that all aircraft and ground-based systems that share the airspace can share information. That makes the system interactive and more flexible. It can share information if some other aircraft approaches the same runway. The system can check the fuel and other things and then order the lower-risk aircraft to make a couple of extra runs around the approach pattern. The idea is that also other aircraft get information about surprisingly happening things.

In Aerospace technology the AI can detect things that can risk the aircraft. The AI can use advanced cameras and communication technology. That allows it to recognize the runway. If there is a lidar- or targeted radar system at the runway that measures the distance and altitude of the aircraft and same time, tells what runway the aircraft approaches that denies the risk of landing on the wrong runway.

This kind of system has two-way sensors. The sensors in aircraft. And ground-based sensors. Those systems can communicate with each other, which gives the error detection ability to that interactive system. If the numbers and other values between those systems match the aircraft is in the right position.

The AI can tell pilots if the runway is not right or the same that is marked in flight plans. Then system can ask wish pilot to continue, and then it can send the right engine and azimuth values to the aircraft. This kind of situation could be very risky. But the deep neural network will send information about that error, and then the system guides the other aircraft to the runway.

https://scitechdaily.com/sonate-2s-space-odyssey-testing-ais-limits-in-space/

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Interesting and futuristic innovations

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