Turning Data into a Weapon Through Advanced Battle Plans

By John Reardon, COTS Journal

It has become clear that the future American warfighter will require advanced Artificial Intelligence or AI that stretches from military headquarters to the raging battlefield. This will be required in a seamless, adaptable, secure, and ruggedized form. As the defenses become more connected, the need for a highly distributed computing ability at the edge becomes a must. Beyond systems that are adapted to extreme environments, however, the engineers at SECO have identified and are focused on providing three key capabilities that are needed. These are complex, applica- tion-specific algorithms, curated data, and computing infrastructure.

Curated data refers to data that has been carefully gathered, sifted, chosen, and organized for its use in military decision-making. It must be so organized and formatted that it can readily be used by all present and future algorithms in the system. Algorithms must of course also be written so that they can readily work with the curated data. The computing infrastructure must be rugged and readily configurable from the command center to a single soldier’s sensor on the edge of the battle.

The engineers at SECO have identified seven technologies that are relevant in addressing these stated goals:

1. Rugged commercial off-the shelf (COTS), modified COTS, and custom designed embedded electronics that interface with and process data from diverse types of sensors.

2. Computer Vision algorithms which identify and classify threats accordingly.

3. Machine Learning which acquires knowledge from curated examples and training.

4. Natural Language Processing or NLP that performs speech and text recognition to extract from enemy communications relevant intelligence on troop position and other key data.

5. Scheduling and resource allocation that optimize the response.

6. Rule-based solutions that create a large library of “if this, then that” solutions.

7. Robotics allowing an embedded system the ability to interact with the environment.

The Department of Defense has been riddled with false starts and countless acronyms in pursuit of a connected battlefield. The latest acronym that has been built on its predecessors is Joint All-Domain Command and Control (JADC2). The important part is the C2 command and control. The Joint All-Domain means that it covers all branches of service and their assets on the battlefield. Simply put they want to have all assets/sensors talking to each other and a solution to be employed based on a compendium of data – or in other words artificial intelligence.

In recent years the predictability of how certain actions will be responded to has left us vulnerable as certain responses are baked into the strategy. The enemy in knowing our playbook may be anticipating our response to any aggression. Employing AI will bring about situational awareness that provides an asymmetrical response leaving the adversaries surprised. Not knowing a programmed response and thus being unable to quickly choose an effective reaction will cause the enemy to pause as their sacrifice will be unknown. Time can be a real killer.

Based on a long experience of solving discrete applications with rugged computing solutions, SECO quickly recognized the large data sets, and the complex theaters of operation would inevitably lead to project creep. With each additional connection, this potential grows exponentially and will inevitably lead to a crippling complexity. The SECO approach is to use an array of building blocks that can be connected for a unified solution. This enables a single element such as a Hummer or Joint Light Tactical Vehicle (JLTV) to act on its own as well as to contribute sensor data up the command structure.

The vastness of a connected battlefield goes beyond land, sea, air, and space to include command structures and policies. It also includes cyber security threats that can do everything from spoofing a sensor to crip- pling whole networks. Building from their experience, SECO uses a portfolio of off-theshelf and customized software and hardware solutions to allow them to address varied applications. An example of a SECO success is the DCD or deck control device, used to control the in-development MQ-25 Stingray ™ unmanned aerial refueler while on an aircraft carrier flight deck.

The defense world is fraught with numerous unforeseen issues that range from traditional systems that do lend themselves to being connected to political mandates that prohibit certain branches of the service from reacting to certain kinds of incidents. An example of the first is the reliance on verbal communication to control the airspace. Transitioning from this to an AI-based solution would require a complete overhaul of the rules and policies that have been used for decades. Another example is reflected by the narrow charter between services. Do you deploy a Navy ship, a Coast guard cutter, or a Harbor Patrol boat from the nearest municipality in pursuit of a threat of a boat entering American waters? These are two of the many potentially difficult hurdles to overcome in bringing the past into the present.

In developing connected solutions, the engineers have come to recognize that it isn’t enough to automate the past. Solutions need to be looking towards the future. This is never more important than in the defense of the country. Today’s connected battlefield will have to draw upon open-source data sets from sources such as those available from social media. In balancing the needs of the past and future, SECO has gathered a team of leading AI minds in the Bay Area of California and other locations to create software solutions that tame the beast into more manageable chunks with complex algorithms and an interpretive user interface. As algorithm and data analysis experts, SECO collaborates with its customers to define and implement intelligent algorithms to meet operational parameters, including sensor bandwidths, available processing power, latency, accuracy, autonomy, and more. The customer then refines the resulting software, including the use of specific training data sets and setting operational parameters, and then deploys it in theater. Operational uses include access, intelligence, plans, training, and interoperability.

SECO believes that AI advancements will be more driven by the need for data interpretation to recognize and measure threats.

Tasks like intelligence analysis and predictive maintenance will be integral and done discretely, for example, predicting the likelihood of encountering an Improvised Explosive Device (IED) and determining its location. The fear of some runaway automated nuclear launch sequence is not something that should be dismissed, but the primary focus of the US and China is on data interpretation and how it might contribute to a country’s defense.

SECO set out to reduce the complexity at the edge by creating an easily deployable and customizable AI/IoT software platform known as CLEA. CLEA runs on edge devices, orchestrating sensor data collection, providing edge-located intelligent algorithms, and managing optional communication of data and/or results through the cloud. The platform enables developers to utilize a library of algorithms, and also to develop proprietary algorithms and applications as needed. The cloud connectivity aspects of CLEA facilitates operations center real-time device monitoring, analytics, infrastructure management, predictive maintenance, secure remote software updates, and more.

The objective of CLEA, which can run on SECO’s or other embedded computing hard- ware, is to offer a computing solution at the edge that can endure the rigors of the environment and yet still offer a competent AI computing engine running autonomously at the edge or utilizing additional resources available via a private cloud. This simple and elegant solution enables low latency, autonomous decision making at the edge while reducing the raw data from the front for effective battlefield management. The propensity of the warfighter to believe that their instincts are more dependable and consequently they might want to override the system are mitigated by the CLEA. This occurs through the use of field-actionable data.

The interoperability of systems leads to greater complexity and thus more vulnerability to intrusions or potential faults. The hurdle of interoperability facilitated by a command center is more complex with each additional connection. It is for this reason that SECO’s approach of putting the most advanced or time-critical AI solutions at the edge ensures that latency and response times are reduced. This combination of data analytics and redundancy aids in affirming that sensors have not been spoofed and are correctly reporting the data. This enables compound queries to be executed more safely and securely by using processing at the edge and identifying irregularities with encryption keys and data sets.

Image - An example of how strategically important the idea of network sensor-to-shooter is to the Department of Defense is the next-generation long-range strike bomber, the B21 Raider. Although its primary function is to be a long-range bomber, the Air Force also wanted the plane to act as an intelligence collection platform for battle management. The first pictures of the plane were released to the public in Early December 2022.

The 21st century warfighter will rely on solutions that draw upon knowledge gleaned by analyzing data from all assets available. This will require a speed that outstrips our adversary’s communication structure and produces an asymmetrical response that is surprising and unsuspected. These solutions will be built upon discrete activities defined using off-the-shelf solutions in a way that builds confidence. From a complex response that may seem non-sensical to the warfighter to the identification of security breaches, AI at the edge will be integral to a superior defense.