Abstract
There has been an increasing prevalence of ad-hoc networks for various purposes and applications. These include Low Power Wide Area Networks (LPWAN) and Wireless Body Area Networks (WBAN) which have emerging applications in health monitoring as well as user location tracking in emergency settings. Further applications can include real-time actuation of IoT equipment, and activation of emergency alarms through the inference of a user's situation using sensors and personal devices through a LPWAN. This has potential benefits for military networks and applications regarding the health of soldiers and field personnel during a mission. Due to the wireless nature of ad-hoc network devices, it is crucial to conserve battery power for sensors and equipment which transmit data to a central server. An inference system can be applied to devices to reduce data size for transfer and subsequently reduce battery consumption, however this could result in compromising accuracy. This paper presents a framework for secure automated messaging and data fusion as a solution to address the challenges of requiring data size reduction whilst maintaining a satisfactory accuracy rate. A Multilayer Inference System (MIS) was used to conserve the battery power of devices such as wearables and sensor devices. The results for this system showed a data reduction of 97.9% whilst maintaining satisfactory accuracy against existing single layer inference methods. Authentication accuracy can be further enhanced with additional biometrics and health data information.
Highlights
Significant research in the area of mobile health has been conducted including its applications and informatics
This paper proposes a framework of military mobile health (mHealth) networks using a Multilayer Inference System (MIS) along with various military applications using mHealth in conjunction with Low Power Wide Area Networks (LPWAN)
MIS OF IOT AND PERSONAL HEALTH DEVICES The mHealth network provides a data inference system to reduce the frequency of data transfer and conserve battery power of sensor devices, which is critical in mHealth security
Summary
Significant research in the area of mobile health (mHealth) has been conducted including its applications and informatics. Internet of Things (IoT) and Low Power Wide Area Networks (LPWAN) networks are emerging to replace previous sensor networks and technologies. These two networks together provide a suitable solution for military applications as they can satisfy the unique requirements for military mobile networks which needs to be adaptable to changing and often unpredictable environmental conditions and needs. Computational and battery constraints remain a challenge for military mobile network sensors and devices as many use portable batteries which have power constraints To mitigate these problems, this paper proposes a Multilayer Inference System (MIS) to build a framework for military mobile networks. The following sections describe an overview of the motivation, problem statement and the chosen approach with methodologies used to develop the solution
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