ARX2021 was an Australian Defence Force sponsored event, where the Head of Land Capability (HLC) issued a Challenge Statement to industry to provide Robotic and Autonomous Systems (RAS) Technology applications in the future operating environment.
The Army RAS Strategy identifies five fields that Army will benefit from in its core deployed task.
CrownMGT is offering solutions for ARX21 in the fields of:
CrownMGT’s solution offerings are based on emerging technology of Multi-Access Edge Computing (MEC) which has its foundations on the Internet of Things (IoT). In the broader context, a “thing” is any device capable of providing a sensed piece of data – analogue or digital.
In the case of the ADFs Land environment, a wearable sensor on the soldier, or an integrated sensor on a vehicle platform can provide real time raw information directly to the local host (such as position, direction, speed, and altitude) – but with emerging edge compute devices we are now able to do so much more.
Small, low power compute devices can collect data from several other wearable IoT devices and perform real time data analysis and machine learning computation at the edge, aiding in improved situational awareness, response times, decision-making, and reducing backhaul tactical communications requirements.
CrownMGT are proposing a pervasive, distributed, decentralised sensor environment with edge computing providing real time analysis and prediction to enable Autonomous Logistics.
Our solution is based on integrated Soldier and Vehicle sensors, combined with sufficient edge compute, to perform Machine Learning (ML) predictions based on real-time data.
The IoBT has the potential to completely revolutionise modern warfare by using data to improve combat effectiveness as well as reduce damages and losses by automated actions while reducing the burden on human warfighters. However, the real power lies in the interconnection of devices and sharing of sensory information that will enable humans to make useful sense of the massive, complex, confusing, and potentially deceptive ocean of information.
IoBT networks are significantly different from traditional IoT networks due to battlefield specific challenges such as the absence of communication infrastructure, heterogeneity of devices, and susceptibility to cyber-physical attacks.
The Soldier Combat Ensemble has integrated sensorised compartments to monitor standard resupply items such as ammunition, rations, and water. It can also monitor the rates of consumption coupled with other health sensors to predict abnormal states of stress, anxiety, and dehydration.
One set of predictive data can be used to enable demand driven logistics, and the other can inform higher commanders on the welfare, and ultimately, the combat effectiveness of the soldiers under their command.
Vehicle Health and Usage Monitoring System (HUMS) data is in all current ADF vehicles and is specified in the Australian Land Data Model (AS LDM). Currently this data is used only for real time on-platform operations. There is too much data to move through the tactical data network, but there is an opportunity for real time analysis and ML prediction to be performed on the platform. An increase in the use of POL, or increased wear in consumable items can be used to predict maintenance requirements, training issues, or imminent equipment failure.
As trends are established, a proactive approach to maintenance, logistics, and supply chain management issues would be enabled in contrast to the current reactive state. Given analytics in these areas, supply chains could be further streamlined to meet requirements.
For IoBT technology to be viable in dynamic battlefield environments, large-scale data ingest, and analysis will need to be conducted in near-real time.
Commercial IoT can rely on ubiquitous connectivity and the ability to rely on large, centralised Cloud data centres. Even in the presence of cellular or wireless networks, once the device connects to a base station or access point, the connectivity is ubiquitous, making it straightforward for any IoT device to reach a Cloud-based resource. Most commercial IoT devices rely on uploading their data to a Cloud resource for post processing.
However, in a battlefield environment that relies on tactical wireless networks, any approach that requires a centralised Cloud-based infrastructure is unlikely to work. Tactical networks are often disrupted, ad hoc, and bandwidth limited, with no spare capacity for transmission of raw sensed data.
Even if a device has a high bandwidth link to a local resource, it is not likely that all devices will be able to have good connectivity to the same Cloud-based platform. Therefore, one of the challenges that needs to be addressed is developing a decentralised infrastructure to support IoBT.
Also, Artificial Intelligence and Machine Learning algorithms require data – lots of data! Data to train and data to test. For a ML algorithm to work with a high confidence it needs to be trained sufficiently and tested with new data under supervision.
Below are real time approximations of sensor data collected on a Soldier, a Vehicle Platform and a combined Combat Team. Note this does NOT include voice or video data.
The most modern tactical communications system would not cope with this much data in real time - Edge Computing is the only solution.
For further information on CrownMGT’s ARX21 solution offerings, please email us at info@crownmgt.com.au
M. J. Farooq and Q. Zhu, "On the Secure and Reconfigurable Multi-Layer Network Design for Critical Information Dissemination in the Internet of Battlefield Things (IoBT)," in IEEE Transactions on Wireless Communications, vol. 17, no. 4, pp. 2618-2632, April 2018, doi: 10.1109/TWC.2018.2799860.
M. Tortonesi, A. Morelli, M. Govoni, J. Michaelis, N. Suri, C. Stefanelli, and S. Russell, “Leveraging internet of things within the military network environment-challenges and solutions,” in IEEE 3rd World Forum on Internet of Things (WF-IoT 2016), RESTON, VA, USA, Dec.2016, pp. 111–116.
N. Suri, M. Tortonesi, J. Michaelis, P. Budulas, G. Benincasa, S. Russell,C. Stefanelli, and R. Winkler, “Analyzing the applicability of internet of things to the battlefield environment,” in Intl. Conf. Mil. Commun. And Inf. Sys. (ICMCIS 2016), Brussels, Belgium, May 2016