artificial intelligence, military, fighter jets, uav, indian air force


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The Indian Air Force has become the first of the services to establish a dedicated center of excellence for artificial intelligence. In the context of military modernization, these digital tools radically redefine the technological elements and these shortcomings are widely discussed. Artificial intelligence is rapidly altering supply logistics, intelligence gathering, sensors, and military robots through the application commonly referred to as the Internet of Battlefield Things (IoBT).

The IAF Center of Excellence for Artificial Intelligence under the UDAAN (Unit of Digitization, Automation, Artificial Intelligence and Application Networking) was inaugurated by Marshal Sandeep Singh, Vice Chief of Air Staff (VCAS), on July 09, 2022 at Air Force Station Rajokri, New Delhi.

A Big Data Analytics and Al platform has been commissioned at the IAF Al Centre, to handle all aspects of analytics, machine learning, natural language processing, neural networks and deep learning algorithms. High-end computing requirements would be supported by the latest GPU-powered servers.

Addressing the gathering, VCAS said the IAF has taken proactive steps to integrate Industry 4.0 and Al-based technologies into its combat processes. He reaffirmed that the AI ​​COE with high-end computing and big data storage capabilities, combined with full-spectrum AI software suites, would significantly improve the operational capability of the IAF.

According to officials, Al-based applications are developed with in-house expertise in coordination with various PSUs, MSMEs and leading universities in the field of artificial intelligence.

Artificial intelligence (AI) in air combat

The next generation of combat aircraft relies heavily on software-centric for its combat operations. Engagement elements are based on data from target detection, tracking and combat operations. In the case of the only operational fifth-generation combat aircraft – F 22 and F 35 – target engagement activities are so heavily software-generated, covering up to 95% of all combat activity. The cockpit is so full of sensors and computer processors that algorithms are already flying planes. Data received from multi-sensor subsystems forms the basis for such engagement. But it is also the greatest challenge for a pilot to read and process data at high speed in a complex air combat environment. It is the core of AI-based decision support systems (DSS) that can basically process such a complex environment and analyze sensory data through processors.

While the algorithm already flies planes, the AI ​​is now more interested in how to fight its own and how to get pilots to trust the AI. It focuses on the OODA loop – the decision cycle of steer, observe, decide and act. What are the fundamental basics of the AI ​​and OODA loop? In a well-reported dogfight where the American F-86 fighter won against the Russion MiG-15, the victories were based on the American pilots having a much shorter OODA loop in the sighting phase and of combat operation action. The F-86 had a much wider field of view and easier hydraulic controls that allowed them to get past the Russian pilots’ OODA loops. Thus, the role of AI is to process this information, which is difficult to achieve in a shorter time frame. AI can significantly reduce the OODA loop.

In addition, AI is also being considered in the C4I management system (command, control, communication, computers and intelligence). Research in this area is happening at breakneck speed to achieve a MIL-grade standard and using AI in a SaaS (software as a service) model.

AI for autonomous vehicle

AI is driving the explosive growth of innovative applications of unmanned aerial vehicles (UAVs) and its military applications. AI applications in drones are spreading in an impressive variety of fields, including ISR (intelligence, surveillance and reconnaissance) and targeting, film, agriculture, logistics, engineering and disaster response . Worldwide, militaries are spending heavily on artificial intelligence computer vision capability for activities such as detecting and tracking submarines, detecting enemy intrusion, or decoding messages using intelligence capabilities. machine learning.

The application of AI also plays a crucial role in the development of anti-combat drone solutions. In a recent development, an American start-up Epirus has developed Leonidas, a technology that can disable a hostile drone while leaving a friendly drone a few meters away unscathed. Using super-dense gallium nitride power amplifiers based on AI algorithms, Leonidas uses direct energy at precise frequencies that can knock out both large fixed-wing drones and small quadcopters.

Furthermore, the IAF has been a pioneer of AI in the field of aircraft maintenance. IAF has significantly digitized its fleets on electronic maintenance management systems. IAF has also digitized the entire inventory management system which works on an AI-based formulation to come up with predictive maintenance or predictive threat scenarios or red flags.

Challenges for AI

While AI is under development, some of the challenges are critical, especially in its military applications. some questions need to be answered for this – whether algorithms can be trained to perform mission planning behaviors efficiently in unpredictable scenarios; can machines be taught combat strategies; could sufficiently generalized representations be constructed to capture the richness of the planning problem itself through the matrix of threats.

“The answers to these questions will help us to strengthen our specifications, which will essentially be a starting document with regard to the expected results. If we tend to use AI heavily in combat aviation, we may have to redefine or even abandon some traditional principles,” said former IAF chief RKS Bhadauria.

AI is not only a tactical advantage but has become a necessity. Countries like China, the United States, and Russia, and many others, are already investing heavily in AI. The need for unbiased data to train and test combat systems will be necessary for the IAF. Data collection, assimilation and analysis will drive AI for the next generation. The integration of AI into military strategies will be the cornerstone of the defense sector. AI is the only way to navigate this new paradigm of warfare.

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