A Smart IoT-Aware System For Crisis Scenario Management

In most dangerous events, involving many people in large buildings, rescue workers need to intervene in a timely and targeted manner in order to help most number of people and secure the environments without wasting resources. This work presents an Internet of Things(IoT)-based framework, aiming at monitoring environmental parameters in order to alert rescuers when they exceed some alarm thresholds. A hardware infrastructure driven by a software layer adds flexibility and adaptability to the Complex Event Processing engine and to a rule engine-based reflective middleware that manages and analyzes raw data in conjunction with a knowledge base modeling the application domain

Fog Computing Architecture for Indoor Disaster Management

Most people spend their time indoors. Indoors have a higher complexity than outdoors. Moreover, today's building structures are increasingly sophisticated and complex, which can create problems when a disaster occurs in the room. Fire is one of the disasters that often occurs in a building. For that, we need disaster management that can minimize the risk of casualties. Disaster management with cloud computing has been extensively investigated in other studies. Traditional ways of centralizing data in the cloud are almost scalable as they cannot cater to many latency-critical IoT applications, and this results in too high network traffic when the number of objects and services increased. It will be especially problematic when in a disaster that requires a quick response. The Fog infrastructure is the beginning of the answer to such problems. This research started with an analysis of literature and hot topics related to fog computing and indoor disasters, which later became the basis for creating a fog computing-based architecture for indoor disasters. In this research, fog computing is used as the backbone in disaster management architecture in buildings. MQTT is used as a messaging protocol with the advantages of simplicity and speed. This research proposes a disaster architecture for indoor disasters, mainly fire disasters

On Evolution of God-Seeking Mind: An Inquiry Into Why Natural Selection Would Favor Imagination and Distortion of Sensory Experience

The earliest known products of human imagination appear to express a primordial concern and struggle with thoughts of dying and of death and mortality. I argue that the structures and processes of imagination evolved in that struggle, in response to debilitating anxieties and fearful states that would accompany an incipient awareness of mortality. Imagination evolved to find that which would make the nascent apprehension of death more bearable, to engage in a search for alternative perceptions of death: a search that was beyond the capability of the external senses. I argue that imagination evolved as flight and fight adaptations in response to debilitating fears that paralleled an emerging foreknowledge of death. Imagination, and symbolic language to express its perceptions, would eventually lead to religious behavior and the development of cultural supports. Although highly speculative, my argument draws on recent brain studies, and on anthropology, psychology, and linguistics

Spartan Daily, April 8, 1994

Volume 102, Issue 44https://scholarworks.sjsu.edu/spartandaily/8544/thumbnail.jp

Probabilistic Methods and Technologies of Risk Prediction and Rationale of Preventive Measures by Using “Smart Systems”: Applications to Coal Branch for Increasing Industrial Safety of Enterprises

Abilities of “smart systems” for processing information, adaptation to conditions of uncertainty, and performance of scientifically proven preventive actions in real time are analyzed. Basic probabilistic models and technologies for the analysis of complex systems, using “smart systems,” ways of generation of probabilistic models for prognostic researches of the new systems projected, modernized, or transformed, are proposed. The proposed methods are described to predict risks to lose integrity for complex structures on the given prognostic time and rationale of preventive measures considering admissible risk, estimate “smart system” operation quality, and predict in real time the mean residual time before the next parameter abnormalities. The methods and technologies are implemented on the level of the remote monitoring systems. The application is illustrated on the examples of the joint-stock company “Siberian Coal Energy Company.

A Sensor Ontology For The Domain Of Firefighting Robots

Fires create thousands of dollars in damage and thousands of deaths each year. Firefighters risk their lives everyday and are often killed in action. Firefighting robots may be able to reduce the loss of lives and damage due to fires. Robots are often used for redundant tasks that require the consistency and efficiency of a machine. They are especially optimal for tasks that require strength that exceeds that of a typical human being or for environments that are hazardous to people. Robots\u27 metallic exteriors are far more durable and easier to replace than flesh and blood, thus they are ideal for fighting fire that may be unreachable or too dangerous for humaning beings. Firefighting robots are most often shaped like tanks and are equipped with fire extinguishers, sensors, and cameras. The robots are typically operated via remote control and lack autonomy. Because of the volatile nature of fires, it is difficult for software engineers to create algorithms to make firefighting robots more autonomous. Ontologies are commonly used for sharing domain information and structuring and analyzing data. This study proposes using an ontology that is designed specifically for a firefighting robot programmed to rescue a human in danger in order to make a decision making algorithm. The methodology uses ontological tools to build the ontology. A decision-making algorithm is created using the information that is stored in the ontology. The study is evaluated on the accuracy rate of making the correct decision. It is also evaluated on if the decision-making algorithm performs significantly better than decisions chosen at random

The Concept of Human Security as a Basis for the Application of Big Data Concept in Establishment of Early Warning System for Crisis Management in the Republic of Croatia

We live in a globalised world characterized by constant crises in numerous social and geographical areas. Political instability, climate change, overpopulation, uncontrolled migration, poor governance, crime, as well as many other factors create the circumstances from which crises can develop. Each crisis given its causes and possible consequences requires different approaches and response systems. This research focuses on considering modern technological solutions that have the purpose of alerting and protecting individuals from risks and threats that can lead to their suffering, caused by natural, technical-technological and anthropogenic crisis events. It also aims to link the theory of human security and the big data concept and present their application through the development of the early warning system for crisis management in the Republic of Croatia. This research has significant value because it analyses and describes the establishment of a particular system in the world

Machine-to-machine emergency system for urban safety

Nowadays most people live in urban areas. As populations grow, demand on the city ecosystem increases, directly affecting the entities responsible for the city control. Challenges like this make leaders adopt ways to engage with the surroundings of their city, making them more prepared and aware. The decisions they make not only directly affect the city in short term, but are also a means to improve the decision making process. This work aimed to develop a system which can act as an emergency and security supervisor in a city, generating alerts to empower entities responsible for disaster management. The system is capable of monitoring data from sensors and provide useful knowledge from it. This work presents an architecture for the collection of data in the Internet of Things (IoT). It delivers the analysis of the used tools and the choices made regarding the implemented system. Also, it provides the necessary inputs for developers to participate in the project, since it describes all the techniques, languages, strategies and programming paradigms used. Finally, it describes the prototype that receives data and processes it to generate alerts with the purpose of warning emergency response teams and the future implementation of a prediction module that can act as a useful tool to better manage the emergency personnel. The completion of the internship allowed the learning of new concepts and techniques, as well as the development of those that were already familiar. With regard to the company, the developed system will integrate the company’s Citibrain platform and will act as a central point, in which, every application (e.g. water management, waste management) can be subscribed to receive alerts

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