artificial intelligence

Everybody has a dream. Our dreams drive us to what we want to do in life. We must work hard, be dedicated, and committed to what we do to achieve our life dreams. Since my childhood, I have had only two goals. One goal was to become a pilot and the second one was to become a NASA astronaut. I worked hard, despite many people failing to believe in me and my dream. Only my parents believed in me. I even remember that my Grade 1 junior school teacher could not believe in my imagination. Through my hard work, dedication, and commitment, I achieved my first dream of becoming a successful pilot. And not just that I even became an airline captain at just an age of 24. The second dream which is remaining is becoming a NASA astronaut. I firmly believe that I must join a Ph.D. program in unmanned systems applications to accomplish this second dream.
My firm intention to become a better professional and to continue developing in the sphere I have chosen years ago never stopped. I remember myself playing with paper airplanes and pretending to be a pilot as a child. Many of my friends did the same. Our paper aircrafts competed, formed flying squadrons, and participated in important air missions. Years passed by, and while my friends moved on with their dreams and changed the love for the games in the air for other interests, I realized that my passion for aviation and space is a lifetime crush. My hobbies, which originated in early childhood, have developed, and brought me to fulfill my dreams. However, it also means that I cannot stop what I have already achieved, and I should keep pushing myself to new professional heights.
My experience is characterized by success in whatever I do. For instance, I passed all my exams and FAA checkrides without any failure ever. I even successfully passed the FAA Certified Flight Instructor rating checkride in first attempt, whereas only 20% of applicants can pass it in their first try. Today I appreciate being part of the United States military’s best branch, the Air Force. My rank with Air Force Reserves for now is Airman First Class(A1C) and my next goal is to become a United States Air Force officer and an Air Force pilot as soon as I am eligible to do it. From my childhood, I always want to improve myself and be career-driven. I am always focused on achieving more than what other people can even imagine. The desire to do more differentiates me from others because success is a product of our headwork. I strongly believe that success is a continuous process, and we should never put a full stop in it. For you to succeed, you must work hard and smart. I am highly motivated to do this program, and if I get proper guidance, I will be producing very high-quality research. My great desire is to get an opportunity to be administered in a Ph.D. program, which continues improving myself and opens doors for me to achieve my dream.
My potential interest area will be to show the people that how artificial intelligence or machines can learn from present-day pilots to make a perfect pilotless aircraft. Basically, main concern for any passengers entering a pilotless aircraft will be if it is as good as a real human. So with my research I want to show that if we take present day pilot actions and make sure that artificial intelligence learns all of them over next many years, we can make a pilotless aircraft in future where passenger can have a peace of mind that this aircraft can take actions as good as real pilots. My visualization is also that we do not need to have human pilots in future; instead, we will have machines that will, be doing human pilot work. In achieving this goal, artificial intelligence or machines must derive that knowledge from the current day’s experienced pilots and apply that knowledge in the future. The unmanned systems should fully use the software and hardware systems to automate aircrafts in future (Club, 2016). The system that can be developed to achieve these is an unmanned aircraft system. The system can gather knowledge and skills from the current pilots, making airplanes operated with no human pilot on board.
For the unmanned aircraft systems to operate, artificial intelligence must be installed in them. Artificial intelligence involves the simulation of human intelligence to machines designed to operate like human beings and mimic their actions (Siau & Wang 2018). The machines can think and work like a human if artificial knowledge is well simulated. The system can learn from human experience, speech reorganization, planning, and solve problems. For example, in the case of another traffic in the air, the systems can get an alternative to avoid the traffic conflict. If the different types of artificial intelligence such as reactive machines and self-awareness are combined, the theory is likely to result in unmanned aircraft. An efficient artificial intelligence should be implemented in aircraft to perform more complex and human-like tasks, and weak artificial intelligence, which is single task-oriented and simple.
Machine learning applications need to be installed in the unmanned aircrafts to automatically install artificial intelligence to facilitate learning and improvement from experience without definite programming. Machine learning enhances machines’ continuous progress to discover new experiences (Siau & Wang, 2018). Accessing new experiences requires machines to access data and uses it to learn for themselves. With machine learning, unmanned aircraft systems can access information from the database without relying on humans and acquiring new experiences. A new experience can aid the systems to solve problems and increase knowledge of operations. A machine learning program can extract and process information from big data, which can be used to automate aircraft. Various machines types of machine learning can be implemented in aircraft automation. They include supervised, unsupervised, and reinforcement learning (Sharma & Kumar, 2017). Supervised learning is task-driven, and unsupervised learning is data-driven, while reinforcement learning learns from errors. Incorporating these machines will enable the unmanned aircrafts to learn from day to day tasks, gather information from the data, and learn from the previous errors the plane made.