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The Internet of Things (IoT) has become a pivotal force in modern technology, driving connectivity and automation across various sectors. By enabling everyday objects to connect and communicate, IoT is transforming industries, enhancing efficiencies, and creating new business models. One of the most fascinating applications of IoT is in the military domain, known as the Military Internet of Things (MIoT). This convergence of multiple technologies is not only revolutionizing civilian life but also reshaping military operations.
Understanding IoT and Its Impact
The Internet of Things (IoT) represents a revolutionary system of interconnected devices, from everyday objects to complex industrial machines, equipped with unique identifiers (UIDs) and the ability to transfer data over a network without human intervention. This ecosystem includes everything from smartwatches and home appliances to industrial robots and equipment monitoring systems. By 2025, the number of connected IoT devices is expected to reach an astounding 100 billion, reflecting the rapid growth and integration of this technology into our daily lives.
What is IoT?
The Internet of things (IoT) describes physical objects (or groups of such objects) with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks. This network can include anything from home appliances and wearable devices to industrial machinery and smart city infrastructures.
The increasing miniaturization of electronics has enabled tiny sensors and processors to be integrated into everyday objects, making them ‘‘smart’’, such as smartwatches, fitness monitoring products, food items, home appliances, plant control systems, equipment monitoring and maintenance sensors and industrial robots. By means of wireless and wired connections, they are able to interact and cooperate with each other to create new applications/services in order to reach common goals.
The Benefits of IoT
- Enhanced Efficiency: IoT enables automation and real-time monitoring, significantly improving operational efficiency.
- Data-Driven Decisions: The data collected by IoT devices can be analyzed to gain insights, leading to better decision-making.
- Improved Quality of Life: From smart homes to wearable health devices, IoT enhances the convenience and quality of everyday life.
- Cost Savings: By optimizing resource use and predicting maintenance needs, IoT helps in reducing operational costs.
The Convergence of Technologies in IoT
The IoT’s evolution is fueled by the convergence of multiple technologies, including ubiquitous computing, real-time analytics, machine learning, commodity sensors, and embedded systems. Traditional fields like wireless sensor networks, control systems, and automation also play a significant role in enabling the IoT, making it a dynamic and versatile system.
The rapid advancements in various technologies have facilitated the growth and expansion of IoT. Some of the key technologies converging to enable IoT include:
Sensors and Actuators
These are the building blocks of IoT devices, responsible for detecting changes in the environment and performing actions based on data received. At the core of IoT are sensors and actuators. Sensors respond to physical inputs from the environment, such as temperature, pressure, or motion, and convert them into signals that can be processed or transmitted.
Common IoT sensors include:
- Temperature Sensors: Detect and convert temperature levels into electrical signals.
- Pressure Sensors: Measure force per unit area and detect atmospheric or stored gas pressure.
- Motion Sensors: Use technologies like passive infrared (PIR) to detect movement.
- Level Sensors: Translate liquid levels into signals, commonly used in fuel gauges.
- Image Sensors: Capture and store digital images for processing, used in applications like facial recognition.
- Optical sensors respond to light that is reflected off of an object and generate a corresponding electrical signal for use in detecting or measuring a condition. These sensors work by either sensing the interruption of a beam of light or its reflection caused by the presence of the object. The types of optical sensors include:
- Through-beam sensors (which detect objects by the interruption of a light beam as the object crosses the path between a transmitter and remote receiver)
- Retro-reflective sensors (which combine transmitter and receiver into a single unit and use a separate reflective surface to bounce the light back to the device)
- Diffuse reflection sensors (which operate similarly to retro-reflective sensors except that the object being detected serves as the reflective surface)
- Proximity Sensors: Detect the presence or absence of objects using various technologies such as inductive or capacitive methods. These approaches include: Inductive technologies which are useful for the detection of metal objects; Capacitive technologies, which function on the basis of objects having a different dielectric constant than that of air; Photoelectric technologies, which rely on a beam of light to illuminate and reflect back from an object, or Ultrasonic technologies, which use a sound signal to detect an object nearing the sensor
- Chemical and Gas Sensors: Detect specific chemical substances or gases like carbon monoxide or chlorine. They are designed to detect the presence of specific chemical substances which may have inadvertently leaked from their containers into spaces that are occupied by personnel and are useful in controlling industrial process conditions.
- Gas sensors: Related to chemical sensors, gas sensors are tuned to detect the presence of combustible, toxic, or flammable gas in the vicinity of the sensor. Examples of specific gases that can be detected include: Bromine (Br2), Carbon Monoxide (CO), Chlorine (Cl2), Chlorine Dioxide (ClO2), Ethylene (C2H4), Ethylene Oxide (C2H4O), Formaldehyde (HCHO), Hydrazine(s): (H2NNH2, CH3NHNH2, [CH3]2NNH2), Hydrogen (H2) etc.
- Smoke sensors or detectors pick up the presence of smoke conditions which could be an indication of a fire typically using optical sensors (photoelectric detection) or ionization detection.
- Infrared (IR) Sensors: Measure infrared radiation to detect temperature without direct contact.
- Acceleration Sensors: Measure the rate of change of velocity of an object. While motion sensors detect movement of an object, acceleration sensors, or accelerometers as they are also known, detect the rate of change of velocity of an object. This change may be due to a free-fall condition, a sudden vibration that is causing movement with speed changes, or rotational motion (a directional change). One of several technologies that are employed in acceleration sensors include:
- Hall-effect sensors (which rely on measuring changes in magnetic fields.
- Capacitive sensors (which depend on measuring changes in voltage from two surfaces)
- Piezoelectric sensors (which generate a voltage that changes based on pressure from distortion of the sensor)
- Gyroscopic Sensors: Measure the rotation and angular velocity of an object.
- Humidity Sensors: Detect the relative humidity of the air, crucial for maintaining environmental conditions.
Water quality sensors sense and measure parameters around water quality. Some examples of what is sensed and monitored include:
- chemical presence (such as chlorine levels or fluoride levels)
- oxygen levels (which may impact the growth of algae and bacteria)
- electrical conductivity (which can indicate the level of ions present in water)
- pH level (a reflection of the relative acidity or alkalinity of the water)
- turbidity levels (a measurement of the number of suspended solids in water)
Connectivity: Technologies like 5G, Wi-Fi, and Bluetooth provide the necessary communication channels for IoT devices to connect and exchange data.
Edge Computing: This technology allows data processing at the edge of the network, reducing latency and improving response times.
Artificial Intelligence (AI): AI algorithms analyze vast amounts of data generated by IoT devices, enabling predictive analytics and intelligent decision-making.
Blockchain: Ensures the security and integrity of data transactions within IoT networks.
The Emergence of Military Internet of Things (MIoT)
What is MIoT?
The Military Internet of Things (MIoT) extends the principles of IoT to military applications. MIoT encompasses a network of interconnected military assets, such as vehicles, drones, wearable devices for soldiers, and various sensors deployed in the field. These devices collect, share, and analyze data to enhance situational awareness, improve decision-making, and increase operational efficiency.
MIoT leverages the foundational principles of IoT, integrating advanced sensors like mobile phone sensors, chemical/biosensors, EO/infrared sensors, and radar, into military applications. These sensors provide critical data for navigation, equipment monitoring, and situational awareness in the battlefield.
Actuators in MIoT, such as electric, hydraulic, and pneumatic devices, play a crucial role in applications like integrated fire control systems. Advances in MEMS, nanotechnology, and biotechnology are essential for developing nanoscale and energy-efficient sensors and actuators.
Key Applications of MIoT
- Battlefield Awareness: Real-time data from various sensors and devices provide commanders with a comprehensive view of the battlefield, enhancing situational awareness and decision-making.
- Logistics and Supply Chain Management: MIoT streamlines logistics by providing real-time tracking and monitoring of supplies, equipment, and personnel.
- Predictive Maintenance: IoT-enabled sensors monitor the health of military equipment, predicting maintenance needs and preventing unexpected failures.
- Enhanced Soldier Capabilities: Wearable devices equipped with sensors and communication tools improve the safety, health, and effectiveness of soldiers.
The Convergence of Technologies in MIoT
The successful implementation of MIoT relies on the convergence of several advanced technologies:
Advanced Sensors: High-precision sensors are crucial for monitoring various parameters in real-time, from environmental conditions to equipment status.
The sensors and actuators should be small size, low in cost, and generally have limited memory and computing capability. The advances in MEMS, Nanotechnology and Biotechnology need to be leveraged to develop nanoscale and energy efficient sensors and actuators. There is requirement for software such as operating systems that are deployable in low-power IoT devices and support device connectivity.
Sensor technology is evolving fast. EO/IR sensors, radar, sonars, motion or sound detectors have their capabilities augmented as the technology they incorporate improves. For example, EO/IR can see further, at much tougher climatic and atmospheric conditions, whether it is day or night, compared to just a few years ago.
Phased-array radars can multi-task, simultaneously collecting intelligence in the land, maritime or air domains without losing range coverage or accuracy. Moreover, subcomponent technology allows those sensors to be manufactured in miniature, allowing their integration in a multitude of platforms.
Therefore, developments in components technology increase the capabilities of IoMT backbones rapidly. It will also change the commercial landscape, as subsystem manufacturers will remain at the forefront of the market, closing the gap with platform manufacturers.
Robust Connectivity: Secure and reliable communication networks, such as military-grade 5G, ensure seamless data transmission in diverse and challenging environments. IoT’s effectiveness hinges on robust communication networks. Various protocols are used to ensure connectivity, including:
One of the main pillars of IoT is its connectivity. It consists of a huge network of elements, which are connected to gather and share information. In general, the information is gathered and used to automate or help make decisions. Due to the variety of data types and applications, different communication and network protocols are needed.
Bluetooth: This protocol works within the frequency of 2.4 GHz, and can be used for short-range (<100 m) applications. One step further into Its evolution is Bluetooth Low Energy (BLE), which presents a significant reduction in the power needed for this protocol. This type can be beneficial for the transmission of small amounts of data from sensors or wearables.
Cellular: Current cellular infrastructure can be also used to extend the communication capabilities of IoT nodes. Depending upon the chosen band and the specific technology, it can be adequate for low power applications (e.g., 2G) as well as for high data rates applications (e.g., LTE). Additionally, there are subtypes of cellular communications, such as the LTE-M and NB-IoT, which were born to provide more data bandwidth or lower power use, respectively.
LoRaWAN: it is a low-power, wide-area (LPWA) protocol designed for battery-powered systems. It operates in the sub GHz 433/868/915 MHz and within the 2.4 GHz. LoRaWAN networks generally follow star topologies, where the elements are: end nodes, gateways, and a set of servers.
Near field communications (NFC): NFC works in the frequency band of 13.56 MHz and the range is a few centimeters. This type of communication is used to extend close-contact communications. In NFC there is an active node (such as a smartphone) generating an RF field that energizes a tag. It works in the frequency band of 13.56 MHz and the range is a few centimeters.
Sigfox: Sigfox uses a technology-based ultra-narrow band (UNB) and it works in the ISM bands, requiring a dedicated infrastructure. It means that it can be globally used but a local operator is needed.
Wi-FI: Working in the frequency of 2.4 GHz and 5 GHz, Wi-Fi connectivity is widely chosen because of its pervasiveness and high data rates. Its main drawback is its high power consumption, so it is not frequently used in battery-powered applications.
Wi-Sun: Wi-Sun is a field area network (FAN) protocol created by the Wi-Sun Alliance and designed to have a low power consumption and latency. It operates in the sub GHz frequency bands as well as in the 2.4 GHz band through a mesh topology.
ZigBee: This communication protocol works in the 2.4 GHz band, for short-range (<100 m) in restricted areas. ZigBee is made for transmitting small amounts of information, namely where really low latency is needed and is widely used in the industry and consumer applications. The ZigBee RF4CE was made to replace IR remote controls (e.g., TVs and DVD systems) and remove the need of having a line of sight between the remote control and the device.
Z-wave: intended for home automation applications, working in ISM frequency bands and with a rate up to 100 Kbps. Its applications follow a mesh network topology performing up to 4 hopes.
MIoT Requires Robust Communication and Network Technologies
To fully harness the power of the Internet of Things (IoT) in military operations, devices must connect to global networks to transmit sensor data and receive actionable analytics. However, military networks, especially tactical ones, typically do not connect to the Internet or have restricted, limited, and expensive access, such as through SATCOM. Additionally, network services are often unavailable in remote terrains, deserts, oceans, and mountains. To overcome these challenges, the military should invest in resilient and flexible capabilities to extend Internet connectivity in denied areas using technologies like high-altitude communications relay platforms and microsatellites.
Communicating data between devices, especially through wireless means, is power-intensive. Therefore, new communication and routing protocols are needed to facilitate low-power, low-memory communication. These protocols must be robust against signal interference and network operation loss to ensure continuous and reliable communication.
Advanced Tactical Radios and Cognitive Radio Systems
MIoT requires robust communication technologies to ensure connectivity in challenging environments. Innovations like high-bandwidth radios, cognitive radio, and dynamic spectrum management are critical for overcoming communication challenges in military operations. Most battlefield military IoT networks operate over tactical radios. To make these integrated networks a reality, developing the next generation of high-bandwidth radios is essential. Cognitive radio and dynamic spectrum management techniques are required to automatically adapt to adverse conditions in the communications environment. These systems must be resilient to jamming, with capabilities to actively track jamming signals and implement automatic jamming avoidance measures.
Processing and Information Management for MIoT
To make sense of the vast amounts of data collected by IoT sensors, robust processing and information management systems are essential. IoT/Military IoT (MIoT) devices gather immense amounts of sensor data, necessitating substantial compute and storage resources for analysis, storage, and processing.
Cloud and Edge Computing
While cloud computing is currently the most common solution due to its massive data handling capabilities, scalability, and flexibility, it may not always meet the specific requirements of MIoT applications. Issues such as latency, reliability, and security concerns, particularly in resource-constrained military networks, limit its effectiveness. Real-time battlefield understanding and synthesis of actionable information from diverse data sources require near-real-time processing.
Emerging concepts like fog computing, which bring compute and storage resources closer to the edge of the network, are increasingly vital. An optimal MIoT application performance may require a hybrid approach, leveraging both fog and cloud computing.
Cognitive Load Management
Managing cognitive load for soldiers is another crucial aspect. Transmitting distracting, irrelevant, or deceptive information can negatively impact soldier performance and lead to incorrect actions. Therefore, methods to limit raw data processing and prioritize the transmission of the most critical information produced by analytics are necessary. Military networks must prioritize content transmission based on information quality and soldier needs.
Edge Computing in IoMT/IoBT
A sound edge architecture is crucial for Military IoT (IoMT) and IoBT (Internet of Battlefield Things). The architecture must handle the vast number of connected sensors and the large volumes of data they produce without overloading the system. Researchers recommend architectures equipped with intelligent data filters, edge device regulation, and network infrastructure upgrades to maximize bandwidth.
Processors and Transmitters
Powerful processors are essential for processing large data volumes quickly in IoMT. Transmitters must also be capable of transmitting large data volumes wirelessly through radio communication systems, ensuring speed and range.
Data Storage Solutions
The defense industry is exploring various solutions for storing large data volumes. Private companies like Amazon offer storage solutions to government users, including the US Department of Defense. However, combat operations’ data storage capabilities must comply with strict technical specifications and likely require specialized solutions separate from commercial off-the-shelf (COTS) options.
Cloud Services Competition
In the civilian market, IoT represents the next battleground for cloud services. Companies like Amazon, Google, Microsoft, Alibaba, and IBM are competing to provide the cloud infrastructure needed to connect and manage the world’s IoT devices. These vendors offer various IoT-specific cloud services to enable fast and efficient data storage and processing, primarily on Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) solutions. They are increasingly verticalizing these services to attract industry-specific workloads.
Effective processing and information management are critical for MIoT. By integrating advanced cloud and edge computing technologies, prioritizing cognitive load management, and leveraging powerful processors and data storage solutions, the military can enhance the efficiency and reliability of its IoT applications. This approach ensures that the vast amounts of data generated are effectively managed and utilized, improving operational outcomes and battlefield decision-making.
AI and Analytics: AI and advanced analytics are essential for managing the massive data generated by IoT devices. AI-driven analytics provide actionable insights from the vast amounts of data collected, enhancing decision-making processes. Predictive maintenance, logistics, and battlefield intelligence benefit from AI’s ability to analyze large datasets and uncover hidden threats or insights. However, ensuring that soldiers receive relevant and accurate information is crucial to avoid cognitive overload and incorrect actions.
Security: Security is a paramount concern in IoT and MIoT deployments. Ensuring the integrity, confidentiality, and authenticity of data across distributed sensors, devices, and networks is critical. End-to-end security solutions from leaders in unified threat management, such as Check Point Software and Palo Alto Networks, are essential for protecting IoT ecosystems.
Advanced security measures, including blockchain technology, protect sensitive military data from cyber threats.
Edge Computing: By processing data closer to the source, edge computing reduces latency and ensures timely responses in critical military operations.
Challenges and Opportunities
Challenges
- Security Concerns: Ensuring the security of IoT and MIoT networks is paramount, given the sensitive nature of the data involved.
- Interoperability: Integrating diverse devices and systems into a cohesive network remains a significant challenge.
- Data Management: The sheer volume of data generated by IoT devices requires robust data management and storage solutions.
Opportunities
- Innovation: The convergence of technologies in IoT and MIoT opens up new avenues for innovation in both civilian and military applications.
- Efficiency: Improved operational efficiencies in logistics, maintenance, and decision-making processes.
- Enhanced Capabilities: IoT and MIoT enhance the capabilities of individuals and organizations, from smart homes to advanced military operations.
Conclusion
The convergence of multiple technologies has propelled the evolution of IoT and MIoT, transforming how we interact with the world and enhancing military capabilities. These advancements are transforming the way we live, work, and protect our nations. As technology continues to advance, the potential of IoT and MIoT will expand, driving innovation and creating new opportunities across various sectors. Ensuring robust communication, processing, analytics, and security will be key to fully realizing the benefits of these interconnected systems. As IoT and MIoT continue to evolve, they promise to deliver unprecedented levels of connectivity, efficiency, and security, paving the way for a smarter and more secure future.
GIS based visualization
Military IoT deployed for situation awareness requires visualization that displays the environment and conditions of smart things. There is need new 3D display technologies for visualization of smart things that provides more information about their situation.
Network management
The network management of military devices and systems with diverse capabilities are challenging. Software solutions spanning security and device management that allow IoT devices to seamlessly discover each other, dynamically communicate and interact with nearby devices is required
AI and analytics
The amount of data that is expected to generate by billions of IoT devices have to handle by the Big Data. Advances in data analytics have allowed for the efficient analysis of the rapidly increasing amounts of data created by IoT devices. AI is a key element for the optimal use of IoMT, as it allows for more efficient analysis of the vast amounts of data that flow at a high rate from an increasingly large number of edge devices.
New advanced analytical tools and algorithms are required that can be used to examine large amounts of battlefield data to uncover subtle or hidden threats and threat activities, correlations, and other insights.
Defence/security-related intelligence mainly comes in the form of open-source intelligence (OSINT), logistics, support and maintenance, and battlefield intelligence. With around 80% of the information available on the internet, other media sources, and social networks, analysis has relied on expert systems.
Big data analytics can scan through a larger volume of data and at the same time reduce the associated noise using AI technologies, such as machine learning. Logistics, support and maintenance hugely benefit from big data analytics.
Predictive or condition-based maintenance can reduce costs and increase the availability of platforms. Depending on the customer and their security concerns, as well as the available industrial capabilities IoMT, in conjunction with big data analytics and performance-based logistics (PBL), is a highly-promising combination for the defence industry.
Finally, battlefield intelligence IoMT is expected to maintain a human-centric or man-in-the-loop approach. Due to its nature, which involves firing against targets, especially when it comes to operations in civilian areas, human identification and clearance for firing will always be necessary. There are many ethical dilemmas that arise from this necessity, which are expected to act as barriers to the rapid expansion of IoMT in the field of armed unmanned systems. For this specific market segment, it is important for a user to invest in the quality and quantity of its sensors, so as to be able to recognise and identify targets.
AI still experiences issues related to causality. For example, machines still cannot always tell the difference between a man holding a baseball bat and a weapon, and, if it does come up with an answer, it cannot always explain why. That is an extremely important aspect especially for the security domain, where unmanned systems with AI technology, especially when operating in swarms, could eventually carry out their missions near civilians and civilian assets.
In terms of the moral dilemmas posed, people are very reluctant to have in their vicinity an unmanned system that could decide for itself what or who consists a threat, even if the accuracy rate of the algorithm is the highest possible. Many defence contractors already offer their solutions for OSINT analysis and systems’ health monitoring, which are also available to the civilian market as well. Examples of such companies are Northrop Grumman, Lockheed Martin, Boeing, ESRI, and Palantir Technologies.
References and Resources also include:
https://www.thomasnet.com/articles/instruments-controls/types-of-internet-of-things-iot-sensors/
