How AI is Making Planes Safer
For many years, planes have always been made by humans, from the outer design and safety of the plane to the code inside the planes. But with the sudden trend of artificial intelligence, especially in many types of jobs, there could be a lot of positive outcomes to using artificial intelligence more than people. Instead of this being a terrible thing, there could be a lot of positive outcomes from using AI to improve both the safety and security of planes. Let’s explore the positive outcomes AI has on the world of airlines.
AI in the Travel Industry
History of AI
First, let’s start with the history of AI. The idea of artificial intelligence (AI) has been around for centuries, dating back to the ancient Greeks. In the 4th century BC, Aristotle wrote about creating machines that could think and reason like humans. Yet, it wasn’t until the 20th century that AI began to make significant progress.
In 1950, Alan Turing published a paper called “Computing Machinery and Intelligence,” which introduced the Turing test. The Turing test measured a machine’s ability to display human-like intelligence. The term “artificial intelligence” was coined by John McCarthy in 1956 at the Dartmouth Summer Research Project on Artificial Intelligence.
The early years of AI research focused on developing algorithms that could solve problems that were difficult or impossible for humans. In the 1960s, AI programs were developed that could play games like chess and checkers and solve mathematical problems. The 1980s saw a shift towards machine learning, leading to advancements in neural networks and modern AI. This progress in machine learning and data mining continued into the 1990s and enabled the development of AI programs capable of tasks like image recognition, natural language processing, and speech recognition.
Today, AI is used in various applications, including healthcare, finance, transportation, and manufacturing. AI is being used to develop new products and services, such as self-driving cars and virtual assistants. AI is also becoming increasingly important in the travel industry.
AI and the Travel Industry
By the 2000s, AI had seamlessly integrated into various areas of the travel industry, simplifying the experiences of global travelers. In airports, typical applications include facial recognition systems and advanced security scanning devices. AI is also being used for:
- Personalized recommendations: AI can analyze customer data and preferences to provide personalized recommendations for destinations, activities, and accommodations. Airbnb aims to create the ultimate AI concierge by leveraging data about guests and hosts, providing tailored travel recommendations. Online travel agencies like Booking.com and Expedia are incorporating chatbots to offer real-time suggestions and optimize the booking experience for customers.
- AI for Travel Itineraries: The ultimate goal is an AI-powered chatbot capable of planning and booking trips with minimal user input. While this vision has yet to be fully realized, companies like Expedia are working towards it. AI systems need improvement to provide up-to-the-minute information for optimal travel bookings, but the trajectory suggests a future where AI significantly streamlines trip planning processes.
- Dynamic pricing: AI can adjust prices for flights, hotels, and other travel services in real time based on demand and other factors.
- Fraud detection: AI can be used to detect fraudulent transactions and protect customers from scams.
- Operational efficiency: AI can automate tasks such as booking flights, checking in to hotels, and managing luggage. One of the first AI applications in travel was chatbots, computer programs that simulate conversation with humans. Travel companies now widely use chatbots to provide customer service and support.
AI in Aircrafts
Aircraft Systems
Older aircraft systems are typically mechanical or electromechanical. They are often heavy, bulky, and require a lot of maintenance. These systems are also prone to failures, which can lead to accidents.
One example of an older aircraft system is the hydraulic system. Hydraulic systems power various aircraft components, such as the landing gear, flaps, and brakes. Hydraulic systems are reliable, but they are also heavy and complex.
Another example of an older aircraft system is the electrical system. Electrical systems power various aircraft components, such as lights, radios, and navigation instruments. Electrical systems are relatively simple but can be susceptible to failures, such as short circuits.
New AI-powered aircraft systems are designed to be more efficient, reliable, and safer than older ones. These systems are typically based on software and electronics, which are lighter and more compact than mechanical or electromechanical systems. AI-powered systems are also less prone to failures, which can help to improve safety.
Benefits of AI in Aircraft
AI being used in aerospace can have many benefits, but nothing comes without a few cons. Starting with the good, introducing AI to aerospace can bring many problems related to manufacturing to a more precise consistency for starters. Also, using AI to analyze large amounts of data from the aircraft system sensors to find errors, predict failure, and be able to raise a maintenance flag before the issues occur can boost efficiency and safety standards for flights. Let alone save money in the process.
Problems with AI in Aircraft
But as I stated, nothing good can come without a little setback. Considering how machine learning works and the precise data that AI algorithms depend on to be accurate, if companies have inadequate or biased data, errors in predictions or incorrect decisions will be flagged. Another example would be if there were attacks on the AI, this could pose substantial security risks. Thankfully, we have already been establishing cybersecurity fields dedicated to these things.
Testing of AI in Aircraft
Some companies have been implementing these types of testing and AI into their aerospace travel already, such as Swiss International Airlines, who last year reported that they could optimize more than half of their flights and save five million Swiss francs. Another company, GE Aerospace, has been implementing their AI technology, “digital twins,” which allows them to analyze data in real-time from the aircraft, predict component degradation, prepare early planning for maintenance, and avoid critical failures and unexpected disruptions.
Safety and Error Prevention
AI-Powered Flight Systems
AI has become a game-changer in the aviation landscape, fundamentally altering how pilots navigate and control aircraft, especially with a keen focus on safety and error prevention. Autopilot systems, intricately crafted with the prowess of AI, provide innovative solutions for efficient flight planning and navigation, even in the face of challenging conditions like turbulence or adverse weather. A prime example of this paradigm shift is in Boeing’s Cognitive Decision Support System (CDSS), a cutting-edge system employing AI to analyze real-time sensor data. It furnishes pilots with critical information and recommendations, proving instrumental in decision-making regarding flight planning, navigation, and aircraft control.
Aircraft Health Monitoring through AI
Integrating AI into aircraft health monitoring systems is pivotal in pre-emptively identifying potential issues and mitigating the risk of in-flight malfunctions. Noteworthy in this domain is GE Aviation’s Digital Twin, an exemplar of AI application that creates a digital replica of aircraft engines. Through AI simulations, it predicts component failures, introducing a proactive approach to maintenance. This strategic shift enables meticulous scheduling, ultimately reducing downtime and elevating safety standards.
AI-Driven Weather Prediction for Safer Flights
In the pursuit of safer flights, the integration of AI with weather prediction systems holds paramount importance. AI-powered weather prediction systems excel in processing and analyzing extensive datasets from diverse sources, generating more precise and timely forecasts than traditional methods. This sophisticated tool empowers pilots to navigate away from hazardous weather conditions, ensuring not only passenger safety but also a smoother and more predictable travel experience.
Enhancing Aircraft Safety Through AI
Comprehensive aircraft safety hinges on the seamless collaboration between reliable autopilots and state-of-the-art AI technologies. At the forefront of this collaboration are researchers developing algorithms capable of real-time error identification and correction, fortifying autonomous systems against unforeseen challenges. The analytical prowess of AI, adept at scrutinizing extensive datasets, facilitates the detection of patterns and potential issues that might elude human operators. This capability significantly contributes to predictive maintenance and proactive error mitigation, heralding a future where safety is not merely reactive but anticipatory. The synergy between AI and aviation safety is poised to redefine security standards in the skies at a college level of sophistication.
Implications for the Future of Aircraft
Improved Safety Measures
As AI becomes more advanced, improved safety measures will be implemented. The airlines will be immediately alerted to any maintenance problems before they cause a safety hazard or potential delay, which is a nuance for both airlines and consumers. Being quickly alerted to a problem allows more time to fix the issue, causing less lag.
Implementing AI in aircraft can give passengers peace of mind, knowing that the plane is functioning well. This could lead to more traveling, boosting the economy and benefiting everyone.
Enhanced Fuel Efficiency
AI can analyze flight patterns and adjust the course and fuel output accordingly to maximize fuel efficiency. Avoiding storms and finding the most optimal path to burn less fuel. This will save money and time and improve safety through weather predictions.
Burning less fuel is important for the environment and the future of the plane industry. Right now, planes are necessary to fly longer distances, but when an alternative to planes is made, the argument will be that the alternative is better for the environment. For the industry to survive, they have to optimize their fuel use and burn less of it.
Reduced Operational Costs
As mentioned previously, introducing AI to aerospace can reduce problems related to manufacturing, which has a massive positive effect on reducing operational costs. All other factors play into this; operational costs decrease when airplanes are more fuel-efficient. As well as money saved from no longer needing to give refunds for flight cancellations when imperative unforeseen maintenance repairs needed to be made.
Reduced costs benefit the airlines but may not be reflected in airline prices. The AI systems may initially cost more money to implement than will be saved, but over time, it will create a significant impact. The gap between different airlines’ resources will become prominent because if only a few utilize AI systems, they could have the advantages and not have to lower prices to compete. Instead, they can reinvest the money and expand, providing better service. So even though flight prices might not decrease, customer satisfaction will.
Takeaway
AI can be used in many ways to make planes safer, including in the travel industry and aircraft. The future of aircraft is filled with promise as AI is introduced in necessary systems to improve safety, fuel efficiency, and cost. Which directly benefits consumer travel and the environment. AI has and will continue to impact the aerospace and travel industries substantially.