Scalable context-dependent analysis of emergency egress models

Pervasive environments offer an increasing number of services to a large number of people moving within these environments, including timely information about where to go and when, and contextual information about the surrounding environment. This information may be conveyed to people through public displays or direct to a person's mobile phone. People using these services interact with the system but they are also meeting other people and performing other activities as relevant opportunities arise. The design of such systems and the analysis of collective dynamic behaviour of people within them is a challenging problem. We present results on a novel usage of a scalable analysis technique in this context. We show the validity of an approach based on stochastic process-algebraic models by focussing on a representative example, i.e. emergency egress. The chosen case study has the advantage that detailed data is available from studies employing alternative analysis methods, making cross-methodology comparison possible. We also illustrate how realistic, context-dependent human behaviour, often observed in emergency egress, can naturally be embedded in the models, and how the effect of such behaviour on evacuation can be analysed in an efficient and scalable way. The proposed approach encompasses both the agent modelling viewpoint, as system behaviour emerges from specific (discrete) agent interaction, and the population viewpoint, when classes of homogeneous individuals are considered for a (continuous)approximation of overall system behaviour

Research Directions in Information Systems for Humanitarian Logistics

This article systematically reviews the literature on using IT (Information Technology) in humanitarian logistics focusing on disaster relief operations. We first discuss problems in humanitarian relief logistics. We then identify the stage and disaster type for each article as well as the article’s research methodology and research contribution. Finally, we identify potential future research directions

Fireground location understanding by semantic linking of visual objects and building information models

This paper presents an outline for improved localization and situational awareness in fire emergency situations based on semantic technology and computer vision techniques. The novelty of our methodology lies in the semantic linking of video object recognition results from visual and thermal cameras with Building Information Models (BIM). The current limitations and possibilities of certain building information streams in the context of fire safety or fire incident management are addressed in this paper. Furthermore, our data management tools match higher-level semantic metadata descriptors of BIM and deep-learning based visual object recognition and classification networks. Based on these matches, estimations can be generated of camera, objects and event positions in the BIM model, transforming it from a static source of information into a rich, dynamic data provider. Previous work has already investigated the possibilities to link BIM and low-cost point sensors for fireground understanding, but these approaches did not take into account the benefits of video analysis and recent developments in semantics and feature learning research. Finally, the strengths of the proposed approach compared to the state-of-the-art is its (semi -)automatic workflow, generic and modular setup and multi-modal strategy, which allows to automatically create situational awareness, to improve localization and to facilitate the overall fire understanding

From flooding to finance: NHS ambulance‐assisted evacuations of care home residents in Norfolk and Suffolk, UK

Focusing on the counties of Norfolk and Suffolk (UK), this investigation examines the effect of coastal and fluvial flooding on the use of ambulance service vehicles in the assisted evacuation of care home residents and quantifies the cost of this service to the NHS under flood conditions. This was completed using GIS Network Analyst functions to identify the impacts of flood probability (high: 1 in 30, medium: 1 in 30 to 1 in 100, and low: 1 in 100 to 1 in 1000) and target ambulance response-times (7, 18, 120, and 180 min) on ambulance service area, road network accessibility, the number of vulnerable care homes and their accessibility, the appropriateness of pre-identified evacuation routes, and the drive-time based evacuation cost to the National Health Service (NHS). The results indicate that approximately 68 care homes and 2,320 residents in Norfolk and Suffolk are at risk of inundation, and care home accessibility, in addition to ambulance service area, decreases with shorter ambulance response-times and lower flood probabilities. Additionally, the use of pre-identified evacuation routes, by the ambulance service, promotes efficient navigation between ambulance stations, care homes, and rest centres, but can unfavourably cause network clustering if unmanaged. In association with these routes, an estimated cost of evacuation based on ambulance drivetime was calculated at £34,000–£42,000 depending on flood probability. The importance of this research is highlighted by the current lack of identified flood evacuation and accessibility maps for emergency responder use, and the associated lack of evacuation cost estimations to be used by the government and NHS to budget for aid assistance during these natural disasters. Therefore, the application of this approach at a national level in the flood emergency planning process would be beneficial to promote strategic efficiency and financial preparedness of ambulance services for the purpose of ambulance-assisted flood evacuations

Behavior of Ad Hoc routing protocols, analyzed for emergency and rescue scenarios, on a real urban area

A mobile Ad Hoc network (MANET) is a collection of wireless mobile nodes that can dynamically configure a network without a fixed infrastructure or central administration. This makes it ideal for emergency and rescue scenarios, where sharing information is essential and should occur as soon as possible. This article discusses which of the routing strategies for mobile MANETs: proactive, reactive or hierarchical, has a better performance in such scenarios. By selecting a real urban area for the emergency and rescue scenario, we calculated the density of nodes and the mobility model needed for the validation study of AODV, DSDV and CBRP in the routing model. The NS2 simulator has been used for our study. We also show that the hierarchical routing strategies are better suited for this type of scenarios