Modelling blue-light ambulance mobility in the London metropolitan area

Actions taken immediately following a life-threatening incident are critical for the survival of the patient. In particular, the timely arrival of ambulance crew often makes the difference between life and death. As a consequence, ambulance services are under persistent pressure to achieve rapid emergency response. Meeting stringent performance requirements poses special challenges in metropolitan areas where the higher population density results in high rates of life-threatening incident occurrence, compounded by lower response speeds due to traffic congestion. A key ingredient of data-driven approaches to address these challenges is the effective modelling of ambulance movement thus enabling the accurate prediction of the expected arrival time of a crew at the site of an incident. Ambulance mobility patterns however are distinct and in particular differ from civilian traffic: crews travelling with ashing blue lights and sirens are by law exempt from certain traffic regulations; and moreover, ambulance journeys are triggered by emergency incidents that are generated following distinct spatial and temporal patterns. We use a large historical dataset of incidents and ambulance location traces to model route selection and arrival times. Working on a road routing network modified to reflect the differences between emergency and regular vehicle traffic, we develop a methodology for matching ambulances Global Positioning System (GPS) coordinates to road segments, allowing the reconstruction of ambulance routes with precise speed data. We demonstrate how a road speed model that exploits this information achieves best predictive performance by implicitly capturing route-specific patterns in changing traffic conditions. We then present a hybrid model that achieves a high route similarity score while minimising journey duration error. This hybrid model outperforms alternative mobility models. To the best of our knowledge, this study represents the first attempt to apply data-driven methodologies to route selection and estimation of arrival times of ambulances travelling with blue lights and sirens

Electronic Payment Systems Observatory (ePSO). Newsletter Issues 9-15

Abstract not availableJRC.J-Institute for Prospective Technological Studies (Seville

IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing

A systematic development of a secure architecture for the European Rail Traffic Management System

The European Rail Traffic Management System (ERTMS) is a new signalling scheme that is being implemented worldwide with the aim of improving interoperability and cross-border operation. It is also an example of an Industrial Control System, a safety-critical system which, in recent years, has been subject to a number of attacks and threats. In these systems, safety is the primary concern of the system designers, whilst security is sometimes an afterthought. It is therefore prudent to assure the security for current and future threats, which could affect the safe operation of the railway. In this thesis, we present a systematic security analysis of parts of the ERTMS standard, firstly reviewing the security offered by the protocols used in ERTMS using the ProVerif tool. We will then assess the custom MAC algorithm used by the platform and identify issues that exist in each of the ERTMS protocol layers, and aim to propose solutions to those issues. We also identify a challenge presented by the introduction of ERTMS to National Infrastructure Managers surrounding key management, where we also propose a novel key management scheme, TRAKS, which reduces its complexity. We then define a holistic process for asset owners to carry out their own security assessments for their architectures and consider the unique challenges that are presented by Industrial Control Systems and how these can be mitigated to ensure security of these systems. Drawing conclusions from these analyses, we introduce the notion of a `secure architecture' and review the current compliance of ERTMS against this definition, identifying the changes required in order for it to have a secure architecture, both now and also in the future

Storm Spotting and Amateur Radio: a Field Guide for Volunteer Storm Spotters

Volunteers have played a critical part in relaying weather information since the middle 19th century. The effort of these volunteers has helped safeguard life and property when severe weather threatens. For almost 100 years Amateur Radio operators have played a critical part in severe weather preparedness and response. Amateur Radio operators not only bring a willingness to serve, but communications skills that provide an added benefit to any storm spotter program. The National Weather Service recognized this when developing the SKYWARN program during the 1960’s. Amateur Radio and the National Weather Service have developed over the last 40 years a solid relationship that has been beneficial to communities across the country that face the threat of severe weather. This project, the first of its kind, seeks to gather information together that will help better prepare Amateur Radio operators that serve as volunteer storm spotters