Original article was published by Dharatikapase on Artificial Intelligence on Medium
state of the art in intelligent aviation system
Artificial intelligence has played a major role in developing the aerospace industry by providing precious information that might otherwise be difficult to obtained via conventional methods. globally the market for artificial intelligence in airlines is increasing day by day it is expected to touch USD 2.2 billion by 2025. Different used cases for AI adoption across the manufacturing companies are gradually taking shapes. The most common one are chatbots are becoming very sophisticated in resolving passengers queries. some airlines are looking for more benefits beyond the chatbots, for example a leading asian airline is using AI to estimate the average lifespan of the parts on its planes. The airline has been able to quicken inspections, optimize the inventory for parts and improve operational efficiency. Most of the airlines are also using AI along with predictive analysis to create personalized promotional campaigns to improve upsell/ crossell opportunities. Airline revenue management is one area in which AI and machine learning are expected to drive transformation in the long term.In this article, I try to cover some of the applications and key areas where this technology is having a significant effect
Reasons why aviation companies are not implementing advances in AI –
Business and technologies grows hand in hand. today airlines are facing to many problems one of them is in implementation of technological advancement in their business. Advances in AI could help aerospace companies to optimize their manufacturing processes. however, there is limited adoption of machine learining techniques in the aviation companies and the main reason for this are lack of access to high quality data, increased dependability on simple models as compared to complex models ,lack of skilled workforce, lack of partners to implement it effectively.
Areas in which AI can be implemented in aviation companies –
among this rising technologies artificial intelligence is still at an initial stage in the aviation business. Advances in AI are reshaping the future for airlines.
Smart maintenance — Aircrafts are having multiple sensors that are helpful to pilot for measuring speed, air pressure, and altitude and they are used to collect information like temperature, moisture, and pressure in different parts of an aircraft. AI models are trained to analyze the collected information to identify the abnormal behavior of the aircraft components. As an example sensors installed in the turbines can collect the information about rotation speed, air pressure, and temperature of the component. The collected information is used to trained the AI models about normal behavior of the turbine. By analyzing this data AI models can identify and notify concerned personnel about possible defect. Hence airlines can identify defective aircraft components and repair them. Aircraft maintenance is a tough task, and if done incorrectly it may cost very much to the airlines. It requires extensive planning and scheduling. AI based predictive maintenance is slowly becoming a trend in the market. Predictive maintenance allows for faster identification and reporting of potential failures in real time it predicts the repair timeline and ensures that the process schedule is smoother and faster . a huge amount of data is given as input and with the help of AI and predictive maintenance solutions, data points and meaningful insights are deduced as output. It helps to engineers to predict failures before that actually happen.
Product design — In every Aviation industry lightweight and durable components are prefered for an aircraft with the help of generative process along with AI algorithms manufacturer can develop. Generative design is the process where engineers or designers use design goals as an input along with constraints and parameters like materials available resources and allocated budget to develop . generative designs is process along with AI algorithms manufacturer can develop the required design . In combination with AI, generative design software can enable product designers to explore numerous design options in short span of time. AI enabled generative design coupled with 3D printing can be used to produce aircraft components such as turbines and wings.
Optimized flight performance — AI is helping pilots during flights by anlaysing critical data like the fuel system, system status ,weather conditions as well as other major parameters that can be accessed in real time to optimize a flight path. And AI also helps in time consuming activities aerospace industries and paves the way to better human machine collaboration. Globally the commercial airlines use billions of gallons of fuel every year. Hence conserving fuel is major concern for entire aerospace field. With the help of AI aerospace organizations can improve their fuel efficiency. An airplane uses lots of fuel in climb phase. AI models can analyze how much fuel is used in climb phase of the different aircraft and by multiple pilots to develop climb phase profiles for every pilot. These profiles can optimize the use of fuel in climb phase. By using AI generated climb phase profiles , pilots can effectively conserve the fuel while flights.
Training — Artificial intelligence can be used to enhance pilot training facilities with pilots being provided with a realistic simulation experience with the help of AI enabled simulators coupled with virtual reality systems. These simulators can also be used to collect and analyze several data with regards to training for creating personlised training data with biometrics to track an individual’s performance.
Customer service — The implementation of AI in industries can enable commercial airlines to offer enhanced to customer service. For this purpose, commercial airlines can use AI-powered chatbots that are capable of resolving customer queries. Using chatbots, they can provide 24/7, automatic customer support. These chatbots can guide customers while booking as well as canceling tickets. Also, AI-powered chatbots constantly learn by having interactions with various customers to improve their ability to understand a customer’s context in conversations and replicating human responses.
Conclusion — AI is being explored in the commercial airlines segment of the aviation industry and is being integrated across multiple areas including customer service, airport and flight operations. In passenger identification, facial recognition may make errors that can lead to delays and unreliable security decisions. To sum up, these AI applications cannot function autonomously and require human intervention. However, with further research and development, AI may be capable of carrying out several tasks autonomously and may become a crucial part of autopilot systems.We will continue to monitor how AI emerges throughout the industry as we anticipate wider implementation in the coming years.