Mosaic Warfare
Overview: The Internet of Military Things encompasses a large range of devices that possess intelligent physical sensing, learning, and actuation capabilities through virtual or cyber interfaces that are integrated into systems. These devices include items such as sensors, vehicles, robots, UAVs, human-wearable devices, biometrics, munitions, armor, weapons, and other smart technology. In general, IoMT devices can generally be classified into one of four categories (but the devices are meant to be ubiquitous enough to form a data fabric):

Data-carrying device: A device attached to a physical thing that indirectly connects it to the larger communication network.
Data-capturing device: A reader/writer device capable of interacting with physical things.
Sensing and actuating device: A device that can detect or measure information related to the surrounding environment and converts it into a digital electronic signal or a physical operation.
General device: A device embedded with processing and communication capabilities that can exchange information with the larger network.
In addition to connecting different electronic devices to a unified network, researchers have also suggested the possibility of incorporating inanimate and innocuous objects like plants and rocks into the system by fitting them with sensors that will turn them into information gathering points. Such efforts fall in line with projects related to the development of electronic plants, or e-Plants.
Proposed examples of IoMT applications include tactical reconnaissance, smart management of resources, logistics support (i.e. equipment and supply tracking), smart city monitoring, and data warfare. Several nations, as well as NATO officials, have expressed Interest in the potential military benefits of IoT technology.

History: Advancements in IoMT technology largely stemmed from military efforts to bolster the development of sensor networks and low-power computing platforms during the 1960s for defense applications. During the Cold War, the U.S. military pioneered the use of wireless sensor network technologies to detect and track Soviet submarines. One example was the Sound Surveillance System (SOSUS), a network of underwater acoustic sensors, i.e. hydrophones, placed throughout the Atlantic and Pacific Oceans to act as underwater listening posts for above-ground facilities. Much of the sensor and networking technologies that the U.S. Department of Defense (DoD) developed during this time period ultimately served as the foundation for modern IoT systems. Critically, the DoD helped set the stage for future IoT research in the late 1960s with the creation of ARPANET, an early precursor to the Internet that geographically-dispersed military scientists used to share data.
In the 1980s, the Defense Advanced Projects Agency (DARPA) formally partnered with academic researchers at the Massachusetts Institute of Technology (MIT) and Carnegie Mellon University to further develop distributed, wireless sensor networks. From there, research into wireless sensor technologies spread throughout the civilian research community and eventually found use for industrial applications such as power distribution, wastewater treatment, and factory automation. During this time period, the DoD also invested heavily in the miniaturization of integrated circuits in order to embed various objects with tiny computer chips. As a result of their funding, the commercial microelectronics industry was able to recover when it faced potential decline at the time.
By the late 1990s, the Department of Defense had announced plans for “network-centric” warfare that integrated the physical, information, and cognitive domains to enhance information sharing and collaboration. Examples of projects guided by this goal include the Nett Warrior (formerly known as the Ground Soldier System or Mounted Soldier System) and the Force XXI Battle Command Brigade and Below communication platform, both of which were prevalent in the early 2000s.
However, interest in IoT research in the military started to wane as commercial industry surged ahead with new technology. While DoD continued research into advanced sensors, intelligent information processing systems, and communication networks, few military systems have taken full advantage of the IoT stack such as networked sensors and automated-response technology largely due to security concerns. As of 2019, research in modern IoT technology within the military started to regain a considerable amount of support from the U.S. Army, Navy, and Air Force.

Programs: Several initiatives were formed by the Department of Defense in order to bolster IoT research in the military domain as well as to reduce the current gap in progress between military and industry applications.

The Connected Soldier: The Connected Soldier project was a research initiative supported by the U.S. Army Natick Soldier Research, Development and Engineering Center (NSRDEC) that focused on creating intelligent body gear.  The project aimed to establish an internet of things for each soldier by integrating wideband radio, biosensors, and smart wearable systems as standard equipment.  These devices served not only to monitor the soldier's physiological status but also to communicate mission data, surveillance intelligence, and other important information to nearby military vehicles, aircraft, and other troops.

Internet of Battlefield Things (IoBT): In 2016, the U.S. Army Research Laboratory (ARL) created the Internet of Battlefield Things (IoBT) project in response to the U.S. Army's operational outline for 2020 to 2040, titled “Winning in a Complex World.” In the outline, the Department of Defense announced its goals to keep up with the technological advances of potential adversaries by turning its attention away from low-tech wars and instead focusing on combat in more urban areas. Acting as a detailed blueprint for what ARL suspected future warfare may entail, the IoBT project pushed for better integration of IoT technology in military operations in order to better prepare for techniques such as electronic warfare that may lie ahead.
In 2017, ARL established the Internet of Battlefield Things Collaborative Research Alliance (IoBT-CRA) to bring together industry, university, and government researchers to advance the theoretical foundations of IoBT systems.
According to ARL, the IoBT was primarily designed to interact with the surrounding environment by acquiring information about the environment, acting upon it, and continually learning from these interactions. As a consequence, research efforts focused on sensing, actuation, and learning challenges. In order for the IoBT to function as intended, the following prerequisite conditions must first be met in regard to technological capability, structural organization, and military implementation.

Communication: All entities in the IoBT must be able to properly communicate information to one another even with differences in architectural design and makeup. While future commercial internet of things may exhibit a lack of uniform standards across different brands and manufacturers, entities in IoBT must remain compatible despite displaying extreme heterogeneity. In other words, all electronic equipment, technology, or other commercial offerings accessed by military personnel must share the same language or at least have “translators” that make the transfer and processing of different types of information possible. In addition, the IoBT must be capable of temporarily incorporating available networked devices and channels that it does not own for its own use, especially if doing so is advantageous to the system (e.g. making use of existing civilian networking infrastructure in military operations in a megacity). At the same time, the IoBT must take into consideration the varying degree of trustworthiness of all the networks it leverages.
Timing will be critical in the success of IoBT. The speed of communication, computation, machine learning, inference, and actuation between entities are vital to many mission tasks, as the system must know which type of information to prioritize. Scalability will also serve as an important factor in the operation since the network must be flexible enough to function at any size.

Learning: The success of the IoBT framework often hinges on the effectiveness of the mutual collaboration between the human agents and the electronic entities in the network. In a tactical environment, the electronic entities will be tasked with a wide range of objectives from collecting information to executing cyber actions against enemy systems. In order for these technologies to perform those functions effectively, they must be able to not only ascertain the goals of the human agents as they change but also demonstrate a significant level of autonomous self-organization to adjust to the rapidly changing environment. Unlike commercial network infrastructures, the adoption of IoT in the military domain must take into consideration the extreme likelihood that the environment may be intentionally hostile or unstable, which will require a high degree of intelligence to navigate.
As a result, the IoBT technology must be capable of incorporating predictive intelligence, machine learning, and neural network in order to understand the intent of the human users and determine how to fulfill that intent without the process of micromanaging each and every component of the system.
According to ARL, maintaining information dominance will rely on the development of autonomous systems that can operate outside its current state of total dependence on human control. A key focus of IoBT research is the advancement of machine learning algorithms to provide the network with decision-making autonomy. Rather than having one system at the core of the network functioning as the central intelligence component dictating the actions of the network, the IoBT will have intelligence distributed throughout the network. Therefore, individual components can learn, adapt, and interact with each other locally as well as update behaviors and characteristics automatically and dynamically on a global scale to suit the operation as the landscape of warfare constantly evolves. In the context of IoT, the incorporation of artificial intelligence into the sheer volume of data and entities involved in the network will provide an almost infinite number of possibilities for behavior and technological capability in the real world.
In a tactical environment, the IoBT must be able to perform various types of learning behaviors to adapt to the rapidly changing conditions. One area that received considerable attention is the concept of meta-learning, which strives to determine how machines can learn how to learn. Having such a skill would allow the system to avoid fixating on pretrained absolute notions on how it should perceive and act whenever it enters a new environment.