Establishing a mesh communication backbone for disaster management: proof of concept

"This article addresses the establishment of a mesh communication backbone to facilitate a near real-time and seamless communications channel for disaster data management at its proof of concept stage. A complete function of the data communications is aimed at the input in near real-time of texts, photos, live HD videos of the incident to originate the disaster data management of a military unit responsible for prevention and solving disaster problems and in need of a communication backbone that links data from a Response Unit to an Incident Command Station. The functions of data flow were tested in lab and at fields. Texts encompassing registered name, latitude, longitude, sent time were sent from concurrent 6 responders. Photos and full HD live videos were successfully sent to a laptop Incident Command Station. However, a disaster database management system was needed to store data sent by the Response Unit. Quantitative statistics were suggested for a more substantial proof of concept and subject to further studies."

Reactivity to crisis situations in the transport sector

The article deals with the response to crisis situations in road transport. Crisis situations are recorded in every critical infrastructure sector. Road transport is no exception. The material transported annually records the growth. The planning of the transport does not take into account the risk of the planned route or the categorization of the transport unit. When categorizing the transport unit the limited choice of suitable routes. The article is focused on real-time responsiveness to crisis situations. The purpose is to minimize next risks that could result in more and more serious events when one crisis situation arises.

Soft Target assessment software

The soft targets and crowded places are closely related to the risk of attack to the group of people. These places are very specific because the moving in the soft targets is not organized. That’s mean these places have open and public access. The attack in the soft targets (attack on the soft targets) can have a significant impact on the population and life of the people. The main aim of the proposed software is to analyze the features of the object. According to the analyses, we can define the corrective action, which can have a significant impact on the security situation in the object.

Agent-based simulation of a fire department’s response to emergency incidents: an updated model

A modelling and simulation (M&S) approach was earlier developed, following statistical analysis of the emergency incident database of the Vaughan Fire & Rescue Service covering eight years of consecutive incident records from January 2009 to December 2016. The M&S framework, which could potentially be replicated for fire departments across Canada, involved two different simulation models running on separate platforms: (i) an Incident Generation Engine, which simulates the ‘arrival’ of emergency incidents, and (ii) a Response Simulation Model. The current report covers only an update of the Response Simulation Model, an agent-based model developed using AnyLogic. Two issues associated with the earlier Response Simulation Model have specifically been addressed and resolved by the updated model. We report on findings from our simulation experiments based on the updated model.

An ontology for threat modeling and simulation of Small Unmanned Aerial Vehicles

Low, Slow and Small Unmanned Aerial Vehicles (LSS UAVs) are one of the fastest-growing threats for national defense, security and privacy. A NATO task group performed a study to identify the elements necessary to define LSS models applicable for the development of necessary countermeasure to potential threats in the future. The goal of this project is to utilize this data collected by the NMSG-154 study to generate a Web Ontology Language (OWL) ontology for LSS threat modeling. The LSS ontology will form the basis for a metamodel for a domain-specific language (DSL) based on the parameters identified. This DSL will eventually be used to generate specific simulation scenarios to model potential threats caused by small drones.

Modeling realistic 3D trees using materials from field survey for terrain analysis of tactical training center

This paper elaborates processes of modeling 3D trees for the simulation of the Army’s Tactical Training Center. The ultimate objective is to develop the 3D model database for inclusion to a game engine library. The adopted methodology includes collecting a forestry inventory for later 3D tree modeling in a Unity’s 3D Tree Modeler. Leaves and trunks were closely modeled using the data collected from the real site in the package SpeedTree modeler. Three tree types were sampled to demonstrate how close and realistic the adopted processes were to produce result 3D models for inclusion to the simulation of the tactical center. Visual comparison was made to show the final models. 3D scenes generated from the inclusion of the models were illustrated in comparison to the photo taken from the site. Further studies to adopt surface modeling data from UAV terrain mapping for tree canopies were recommended to verify photorealism of the processed 3D models.

Deep learning of virtual-based aerial images: increasing the fidelity of serious games for live training

The aim of rapidly reconstructing high-fidelity, Synthetic Natural Environments (SNEs) may benefit from a deep learning algorithm: this paper explores how deep learning on virtual, or synthetic, terrain assets of aerial imagery can support the process of quickly and effectively recreating lifelike SNEs for military training, including serious games. Namely, a deep learning algorithm was trained on small hills, or berms, from a SNE, derived from real-world geospatial data. In turn, the deep learning algorithm’s level of classification was tested. Then, assets learned (i.e., classified) from the deep learning were transferred to a game engine for reconstruction. Ultimately, results suggest that deep learning will support automated population of highfidelity SNEs. Additionally, we identify constraints and possible solutions when utilising the commercial game engine of Unity for dynamic terrain generation.