About this book:

*From Sensors to Decisions: End-to-End Architectures for Real-Time AI in Combat Systems* is a comprehensive technical guide for developing high-stakes artificial intelligence within the unique constraints of the battlefield. The book argues that combat AI cannot be treated as a collection of isolated components; instead, engineers must adopt an end-to-end perspective that prioritizes latency, reliability, and fidelity from the moment a sensor captures data to the final human decision. The text explores the physical phenomenology of diverse sensors—including Radar, EO/IR, LiDAR, and acoustic modalities—and emphasizes the foundational necessity of precise time synchronization, georegistration, and standardized data schemas to enable effective multi-modal fusion.

The technical core of the book details the specialized infrastructure required at the tactical edge. It examines the trade-offs of edge compute hardware through the lens of Size, Weight, and Power (SWaP-C), the use of Real-Time Operating Systems (RTOS) to guarantee deterministic scheduling, and the deployment of publish-subscribe middleware like DDS for resilient communication. On the modeling side, the author discusses sophisticated techniques for low-latency AI, such as model pruning, quantization, and knowledge distillation, alongside strategies for managing training data scarcity through synthetic data and digital twins. These models feed into complex tracking and decision engines that must navigate ambiguity and adversarial deception.

A significant portion of the work is dedicated to the relationship between the machine and the human operator. The book highlights human-machine teaming (HMT) and explainable AI (XAI) as essential for building trust and ensuring that operators can intervene in automated processes. It also addresses the critical challenge of maintaining functionality in contested and degraded environments (DDIL), where communications are often jammed or intermittent. The book outlines robust security measures, including zero-trust architectures and hardware roots of trust, to protect the entire AI lifecycle from data poisoning or cyber intrusion.

The final chapters move from engineering to implementation and ethics. Through case studies in air, maritime, and ground domains, the book illustrates practical applications such as cognitive electronic warfare and autonomous reconnaissance. It concludes with a rigorous examination of governance and the Law of Armed Conflict (LOAC), asserting that all combat AI must adhere to the principles of distinction, proportionality, and accountability. Ultimately, the book serves as a blueprint for creating fast, resilient, and responsible AI systems that augment human judgment in the unforgiving environment of modern warfare.

What You'll Find Inside:

• End-to-end system perspective emphasizing latency, reliability, and fidelity across the entire sensor-to-decision loop as the core measure of success
• Unique constraints of tactical edge environments including severe SWaP-C limits, intermittent communications, and adversarial conditions that fundamentally shape all design decisions
• Critical importance of precise time synchronization and georegistration for enabling accurate multi-sensor fusion and robust tracking in dynamic battlespaces
• Specialized techniques for optimizing AI models for edge deployment including low-latency architectures, quantization, pruning, and distillation to meet strict real-time constraints
• Human-machine teaming principles where AI augments rather than replaces operators, requiring explainability, appropriate autonomy levels, and trust-building interfaces

Who's It For:

This book is intended for engineers, system architects, and technical leads working on real-time AI systems for combat applications who must design and deploy solutions that transform heterogeneous, high-rate sensor data into timely, trustworthy decisions under severe tactical constraints. It is particularly valuable for professionals dealing with the unique challenges of contested environments where traditional enterprise AI assumptions about abundant compute, stable connectivity, and generous latency budgets do not apply. Readers will benefit from the book's focus on practical patterns, checklists, and mental models for building resilient, responsible end-to-end architectures that meet the demanding requirements of air, maritime, and ground combat systems.