In the recently held e-symposium Artificial Intelligence (AI) for Air Warriors, the Indian Air Force (IAF) Air Chief Marshal RKS Bhadauria and domestic and international experts explored AI-based solutions for air combat operations.
AI has grown significantly in the commercial sector and militaries across the world are pushing to deploy advanced technologies in their war-fighting facilities. Several initiatives to automate processes to improve the efficiency of aircraft maintenance operations have been launched. The sector has already digitised parts through electronic management systems. IAF is now focusing on AI-based applications on aircraft maintenance-related projects. Currently, IAF is working on predictive maintenance and the use of AI for predictive threat scenarios.
According to a C4I (command, control, communication, computers, and intelligence) expert, information received from heterogeneous sources is fused to enhance detection capabilities and identify targets. Multi-platform and multi-sensor data fusion is key. An AI-based decision support systems (DSS) architecture must be created for complex air combat operation environments. The latest generation of fighter jets are up to 90% software-centric for target detection, categorisation, tracking, and engagement activities. A human pilot cannot process the enormous amount of high-speed data being generated by multiple sensors. Only high-end processors that are manufactured for hard real-time architecture and run on a real-time operating system (RTOS) can process this data.
The net-centric tactical ISR information, combined with the joint operations in a combat mission requires information collection and transmission among net units (like satellites and air electronic warfare). Moving real-time information across multiple systems in the loop always diminishes the `real-time’ quotient within the information, making the data stale for use. Here, AI-driven, multi-access networking, and edge computing architecture are ideal communication solutions. Free-space optical (FSO) communication, 5G, and Satcom channels of communication can achieve flexible and assured bandwidth.
AI in unmanned aerial vehicles (UAVs) is the natural extrapolation, making the drones truly autonomous. These air-launched UAVs are capable of stand-off imaging and extended range communication. UAVs are expected to improve the decision support capabilities on the edge, making the DSS systems more efficient.
The use of AI for predictive maintenance is an already evolved field commercially. AI-based predictions maximise efficiency, reduce unplanned downtime, and increase equipment reliability. Coupled with a maintenance scheduler application, it provides the ability to manage, schedule, and execute maintenance programmes for thousands of machines. It also helps a user to manage the full asset lifecycle to aid intelligent strategic planning. It is possible to provide alerts via alarms, email triggers, or SMS notifications to prompt action. Aircrafts have a well-defined, structured, and strict maintenance schedule. The Ops Logistic Concept can be effectively implemented using similar AI-based predictive maintenance techniques.
The need for unbiased data to train and test combat systems is one of the biggest challenges for IAF. Also, security aspects like smart cloud servers available in India independently to provide data confidentiality and cybersecurity in support infrastructure needs to be addressed. AI solutions in air combat and predictive maintenance are expected to change the IAF standard operating procedures in the near future.
