From Drones to Data: Unveiling Edge Computing as a New Warfighting Domain

Barshan Karmakar
Barshan Karmakar
Intern - Policy & Advocacy, CyberPeace
PUBLISHED ON
Oct 22, 2025
10

Introduction

In real-time warfare scenarios of this modern age, where actions occur without delay, the relevance of edge computing emerges as paramount. By processing data close to the source in the battlefield with the help of a drone or through video imaging from any military vehicle or aircraft, the concept of edge computing allows the military to point targets faster and strike with accuracy. It also enables local processing to relay central data, helping ground troops get intelligence inputs to act rapidly in critical mission scenarios.  

As the global security landscape experiences a significant transformation in different corners of the world, it presents unprecedented challenges in the present scenario. In this article, we will try to understand how countries can maintain their military capabilities with the help of advanced technologies like edge computing. 

Edge Computing in Modern Warfare

Edge computing involves the processing and storage of data at the point of collection on the battlefield, for example, through vehicles and drones, instead of relying on centralized data centers. This enables faster decision-making in real-time. This approach creates a resilient and secure network by reducing reliance on potentially compromised external connections, supporting autonomous systems, precision-based targeting, and data sharing among military personnel, drones, and command centers amidst a challenging environment.

A report released by the US Department of Defence in March 2025 found a crucial reality surrounding the operation of hardware relying on outdated industrial-age processes in the digital era. In the case of applications with video, edge computing helps to deliver significant advantages to a wide range of crucial military operations, which include: 

  • Situational awareness with real-time data processing that provides improved battlefield visibility and proper threat detection. 
  • Autonomous warfare systems such as drones, which use a tactical edge cloud computing to get the capability to navigate faster. 
  • Developing a strong communication and networking capability to secure low-latency communication for troops to stay connected in challenging environments. 
  • Ensuring predictive maintenance with the help of effective sensors to carry out edge detection and attrition at an early point, thereby reducing equipment failures. 
  • Developing effective targeting and weapons systems to ensure faster processing to enable precision-based targeting and response, besides a strong logistics and supply chain that can provide real-time tracking to improve delivery accuracy and resource management. 

This report also highlighted that the DoD is rapidly updating its software and investing in AI enablers like data sets or MLOps tools. This also stresses the breaking down of integration barriers by enforcing MOSA (Modular Open Systems Approaches), APIs (Application Programming Interface), and modular interfaces to ensure interoperability across platforms, sensors, and networks to make software-defined warfare an effective strategy.  

Developing Edge with Artificial Intelligence for Future Warfare

A significant insight from the work of the US Department of Defense is its emphasis on the importance of edge computing in shaping the future of warfare. In that context, the Annual Threat Assessment Report highlights a key limitation of traditional AI strategies that rely on centralised cloud computing, since these might not be suitable for modern battlefields with congested networks and limited bandwidth. The need for real-time data processing requires a distributed and edge-based AI solution to address contemporary threats. This report also directly supports the deployment of effective edge with AI in a defined, disrupted, intermittent, and limited-bandwidth (DDIL) environment. In that case, when the communication networks fail, the edge servers at the edge of the network offer crucial advantages that cloud-dependent systems cannot. This ability to analyse data and make decisions without consistent connectivity and operate with limited computational resources is a strategic necessity. 

The scenario of warfare is a phenomenon that requires maintaining a strong strategic and tactical approach, which, in the present times, is being examined through the domain of digital platforms. Modern warfare patterns demand faster decision-making and edge computing deliveries by shifting the power of distant servers to the frontlines. The US military is already moving in the direction of deploying edge-enabled systems to prove the nature of sensors and networks to compute at the tactical edge to transform warfighting.

However, it can be understood with the help of an example, as creating fusion in the skies with F-35s. As they have showcased the capability of edge computing by fusing sensor data with MADL (Multi-Functional Advanced Data Link) to create a unified picture, making the squadrons a force multiplier. An example of this was visible when an F-35 relayed real-time tracking data, enabling a navy ship to neutralise a missile beyond its range.

Conclusion: The Way Ahead 

As the changing nature of warfare moves towards adopting software-defined systems, where edge computing thrives as a futuristic military technology, it calls for the need for integration across all domains of warfighting. But at the same time, several imperatives do emerge, such as: 

  • Developing an open architecture that enables both flexibility and innovation. 
  • Ensuring an effective connectivity that actually combines a confluence of legacy systems. 
  • Developing interoperability among the systems that can function in synergy with all platforms and can function across all domains. 
  • Prioritising edge-native AI development systems, where it is also necessary to ensure the shift to adopting cloud-based AI models to create solutions optimised from the ground up for edge deployment. 
  • Investing in edge infrastructure to establish a robust edge computing infrastructure that enables rapid deployment by testing and updating AI capabilities across diverse hardware platforms. Like the way the military training academies in India are developing training infrastructures for training officer cadets or personnel to handle drones and all forms of advanced warfare tactics emerging in this age. 
  • Fostering talent and expertise by embracing commercial solutions where software talent could be enabled across the enterprises with expertise in edge computing capabilities and AI. In this case, the role of the commercial sector can help to drive innovations in edge AI, and the only way to move in this direction is by leveraging these advances through partnerships and collaborative efforts. 

Taking the example of the ARPANET, which once seeded the modern internet, edge computing can also help to create a transformative network effect within the digital battlespace. In conclusion, future conflicts will be defined by the speed and accuracy provided by the edge, as nations integrating AI and robust edge infrastructures can hold a strong advantage in the multi-domain battlefields in the future.

References 

PUBLISHED ON
Oct 22, 2025
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