English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Deployment of Internet of Things (IoT) devices and Data Fusion techniqueshave gained popularity in public and government domains. This usually requirescapturing and consolidating data from multiple sources. As datasets do notnecessarily originate from identical sensors, fused data typically results in acomplex data problem. Because military is investigating how heterogeneous IoTdevices can aid processes and tasks, we investigate a multi-sensor approach.Moreover, we propose a signal to image encoding approach to transforminformation (signal) to integrate (fuse) data from IoT wearable devices to animage which is invertible and easier to visualize supporting decision making.Furthermore, we investigate the challenge of enabling an intelligentidentification and detection operation and demonstrate the feasibility of theproposed Deep Learning and Anomaly Detection models that can support futureapplication that utilizes hand gesture data from wearable devices.

IoT Solutions with Multi-Sensor Fusion and Signal-Image Encoding for Secure Data Transfer and Decision Making