IoT has already disrupted many industries with its Connected Devices framework or autonomous presence in the closed loop network of devices. Many Countries are trying to take advantage of IoT in Military and Defence Applications to tackle various warfare and battlefield challenges. The Internet of Military Things (IoMT) is a class of IoT for modern combat operations and Intelligent warfare. By creating a miniature ecosystem of smart technology capable of distilling sensory information and autonomously governing multiple tasks at once, the IoMT is conceptually designed to offload much of the physical and mental burden that war fighters encounter in a field combat. IoMT mainly targets and tries to solve below challenges of the modern warfare.
IoT Applications in Defence
Surveying the battlefield using unmanned aerial drones with attached cameras and sensors to map the landscape and positions of the enemies and send the data to command centre. This data can assist the officers in taking strategic decisions. These drones can also be used for autonomous patrolling near the borders and to alert the army personnel in case of a breach or a potential threat. This nullifies any personnel loss as they are unmanned and pose no additional risk as they can be operated remotely.
In the above image, a drone can be seen collecting data on the landscape to identify vantage points, water bodies and water level and mapping the terrain structure into a 3D model.
Monitoring a Fighter’s health while on the battlefield is very tricky. A wide range of sensors like Hear rate sensor, Ph sensors, Pressure sensors on Kevlar suite to assess the damage can be attached to the soldiers vest which can track, sense and send alerts about their changing medical condition to the command centre where each fighter can be centrally monitored and in adverse situations can be pulled off from the field or be administered medical supplements based on need.
Additionally, the doctors and medical personnel will have a prior knowledge on the severity of the injury of the fighters before they are brought back to the medical base for treatment. Based on the information, necessary equipment could be arranged in advance so that no time is wasted during the treatment of injured soldiers.
The US Army is investing heavily in preparing soldiers using VR / AR Simulation. Computerized models are generated based on real battle field data from earlier and then a Training Simulation environment is rendered and the Fighters are equipped with VR / AR devices who are then dropped to the simulated environment and their accuracy, emotional control, movement speed and other parameters are captured and used for the assessment. Soldiers can also improve the aim and accuracy by practising in this environment with no physical damage and prepare for the actual battle. Mistakes can be made in the Training and the same mistake can cause a life during a battle.
There is flight simulator for Pilots who can test and get the near physical experience of flying the plane prior using a Flight Simulator. Pilots need to perform various manoeuvres to dodge an enemy trail or escape a tracking missile. Physical training for such scenarios can be costly to arrange and sometimes can result in fatal injuries. Simulation is the perfect choice for training pilots in such scenarios.
The military vehicles are equipped with sensors to track their position, damage level, fuel efficiency, engine status, total engine hours left and pretty more such parameters. Now managing 100 such vehicles can be difficult if there is no efficient fleet management. The effective transportation of goods, ammunitions, armaments and troops is very essential to a successful operation. Integrating AI with military transportation can lower transportation costs and reduce human operational efforts. It also enables military fleets to easily detect anomalies and quickly predict component failures. Smart tracking these vehicle fleets can track the Driver’s awareness and make him accountable for every step of the vehicle. According to DoD, Real-Time Fleet Management would reduce fuel costs by 25 percent.
Not just Vehicles, but weapons and unmanned terrain vehicles can also be tracked using sensors. Weapons can have a Cartridge sensor to let the fighter know when to reload and remote unmanned terrain vehicles can be tracked and monitored during spying and surveillance the enemy grounds.
AI techniques are being developed to enhance the accuracy of target recognition in complex combat environments. These techniques allow defence forces to gain an in-depth understanding of potential operation areas by analysing reports, documents, news feeds, and other forms of unstructured information. Additionally, AI in target recognition systems improves the ability of these systems to identify the position of their targets. Capabilities of AI-enabled target recognition systems include probability-based forecasts of enemy behaviour, aggregation of weather and environmental conditions, anticipation and flagging of potential supply line bottlenecks or vulnerabilities, assessments of mission approaches, and suggested mitigation strategies. Machine learning is also used to learn, track, and discover targets from the data obtained
In the US, DARPA’s Target Recognition and Adaption in Contested Environments (TRACE) program uses machine learning techniques to identify targets and automatically locate with the help of Synthetic-Aperture Radar (SAR) images. Target recognition also helps in search and rescue missions or military personnel or if there are any hostages involved during terrorist attacks. US Army is already using drones for autonomous patrolling near the borders or send drones when the RADAR / Sensing devices detect any movement. This can save precious lives of military personnel in case of a surprise attack by the enemy. First-hand investigation with live feed can be done by these unmanned drones and then necessary action can be taken based on threat level.
A drone combined with Machine Learning uses Object / Target recognition to identify the vehicles, humans and track their positions from an altitude. This data is captured and processed in real-time giving the edge to the army personnel before they proceed to the attacking zone.
From supply-chain logistics to public transit, IoT solutions are being used to improve business in many ways. By connecting shipping vehicles with sensors to monitor temperature, it can help ensure goods, especially food, arrive in a safe condition. Sensors and smart software can be used to collect data that can help the driver operate the vehicle in a manner that helps save fuel. In the future, connected infrastructure will also work with connected vehicles to help reduce traffic and prevent accidents.
Machine Learning and AI is extremely useful to efficiently process large volumes of data captured from hoards of devices and sensors from the battlefield in order to obtain valuable and critical information. This information helps is taking time critical decisions by the officers and plot strategic actions to combat the enemy. AI can assist in culling and aggregating information from different datasets, as well as acquire and sum supersets of information from various sources. This advanced analysis enables military personnel to then recognize patterns and derive correlations.
IoT can complement the already efficient Army with its connected framework and all sensing capabilities. Couple this with Machine Learning, we can get critical insights of the battlefield in near real-time putting the officers at an advantage to use the information to change the course of actions on the field and to carry out a successful operation. IoT can help the military in any kind of operation like battlefield combat, spying and surveillance an enemy base or a terrorist hideout, Search and Rescue, Reconnaissance and to gather information.