An Inquiry Regarding the Development of an Effectual Architecture Framework Supporting Next Generation 9-1-1

The emergency 9-1-1 service is a vital part of our nation â„¢s emergency response and disaster preparedness systems. At last count there were 6100 Public Safety Answering Points across the United States, 97 of those reside in the State of Colorado, and the citizens of the United States cannot email, text, or instant message these types of non-traditional communication to those Public Safety Answering Points due to technological limitations. The trends in personal communication technologies are accelerating the obsolescence of the current 9-1-1 systems. The Public Safety Answering Point of today is designed to accept and process voice media only; and proved successful in delivering emergency services in times of personal, regional, and national need. The current circuit-switched infrastructure of the 9-1-1 Public Safety Answering Point network cannot receive digital data (e.g., text messages, email, photographs, and video) from the communication devices commonly used by the public today. A national movement known as Next Generation 9-1-1 is underway that will support non-traditional communication digital data processing in the Public Safety Answering Point. This case study will attempt to determine if practical service oriented architecture methodology can be used in the development of an effectual architecture framework supporting the Next Generation 9-1-1framework and the nontraditional communication technology within the Public Safety Answering Points of Colorado

Communication and tracking ontology development for civilians earthquake disaster assistance

One of the most important components of recovery and speedy response during and immediately after an earthquake disaster is a communication and tracking which possibly capable of discovering affected peoples and connects them with their families, friends, and communities with first responders and/or to support computational systems. With the capabilities of current mobile technologies, we believed that it can be a smart earthquake disaster tools aid to help people in this situation. Ontologies are becoming crucial parts to facilitate an effective communication and coordination across different parties and domains in providing assistance during earthquake disasters, especially where affected locations are remote, affected population is large and centralized coordination is poor. Several existing competing methodologies give guidelines as how ontology may be built, there are no single right ways of building an ontology and no standard of Disaster Relief Ontology exist, although separated related ontologies may be combined to create an initial version. This article discusses the ongoing development of an ontology for a Communication and Tracking System (CTS), based on existing related ontologies, that is aimed to be used by mobile phone applications to support earthquake disaster relief at the real-time

The Recognition of Fires Originating from Photovoltaic (PV) Solar Systems

There has been an observable increase in the fitting of photovoltaic (PV) solar panels on the roofs of buildings in the UK over the last decade. The origin of some fires in domestic and commercial properties has been attributed to PV systems. This thesis examines the ability of fire examiners to recognise and record details of fires believed to have originated from PV systems, as well as investigating the effect of internal heating in direct current (DC) isolators to the point at which they fail. National fire data was examined along with the methods for collecting and collating these data. This clarified that national fire data cannot identify the specifics of electrical fires. Validity of these data was then tested by identifying the confidence and competence in the recognition of the origin of fire, (especially when associated with PV systems), of some fire staff responsible for collecting fire data. This suggests that some fire scenes examiners are not confident in their own ability to recognise fires originating from PV systems. Evidence for fires occurring in PV systems in Kent between 2009 and 2014 was then examined, including a cold case forensic review of the evidence. This provided an indication that a potential common point of failure, which may lead to fire originating from a PV system, was to be found within the DC section of the PV circuits and probably within the DC isolator switch itself. Experimentation revealed that internal heating of a terminal connection can lead to changes of the phase of the insulating material, causing failure of structural integrity and therefore allowing an arc to be established. Observable post fire indicators associated with this mechanism of failure have been identified as well as hydrocarbons evolved from pyrolysis of isolator insulating material. Finally, areas for further experimental research and training of fire staff are suggested as well as the modification of recording mechanisms and building regulations

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Communication and Tracking Ontology Development for Civilians Earthquake Disaster Assistance

ABSTRACT One of the most important components of recovery and speedy response during and immediately after an earthquake disaster is a communication and tracking which possibly capable of discovering affected peoples and connects them with their families, friends, and communities with first responders and/or to support computational systems. With the capabilities of current mobile technologies, we believed that it can be a smart earthquake disaster tools aid to help people in this situation. Ontologies are becoming crucial parts to facilitate an effective communication and coordination across different parties and domains in providing assistance during earthquake disasters, especially where affected locations are remote, affected population is large and centralized coordination is poor. Several existing competing methodologies give guidelines as how ontology may be built, there are no single right ways of building an ontology and no standard of Disaster Relief Ontology exist, although separated related ontologies may be combined to create an initial version. This article discusses the ongoing development of an ontology for a Communication and Tracking System (CTS), based on existing related ontologies, that is aimed to be used by mobile phone applications to support earthquake disaster relief at the real-time

Exploring the impact of COVID-19 on aviation industry: A text mining approach

LARC publication</p

Mission Dependency Index of Air Force Built Infrastructure: Knowledge Discovery with Machine Learning

Mission Dependency Index (MDI) is a metric developed to capture the relative criticality of infrastructure assets with respect to organizational missions. The USAF adapted the MDI metric from the United States Navy’s MDI methodology. Unlike the Navy’s MDI data collection process, the USAF adaptation of the MDI metric employs generic facility category codes (CATCODEs) to assign MDI values. This practice introduces uncertainty into the MDI assignment process with respect to specific missions and specific infrastructure assets. The uncertainty associated with USAF MDI values necessitated the MDI adjudication process. The MDI adjudication process provides a mechanism for installation civil engineer personnel to lobby for accurate MDI values for specific infrastructure assets. The MDI adjudication process requires manual identification of MDI discrepancies, documentation, and extensive coordination between organizations. Given the existing uncertainty with USAF MDI values and the effort required for the MDI adjudication process, this research pursues machine learning and the knowledge discovery in databases (KDD) process to identify and understand relationships between real property data and mission critical infrastructure. Furthermore, a decision support tool is developed for the MDI adjudication process. Specifically, supervised learning techniques are employed to develop a classifier that can identify potential MDI discrepancies. This automation effort serves to minimize the manual MDI review process by identifying a subset of facilities for potential adjudication