Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior

Predicting the evacuation decisions of individuals before the disaster strikes is crucial for planning first response strategies. In addition to the studies on post-disaster analysis of evacuation behavior, there are various works that attempt to predict the evacuation decisions beforehand. Most of these predictive methods, however, require real time location data for calibration, which are becoming much harder to obtain due to the rising privacy concerns. Meanwhile, web search queries of anonymous users have been collected by web companies. Although such data raise less privacy concerns, they have been under-utilized for various applications. In this study, we investigate whether web search data observed prior to the disaster can be used to predict the evacuation decisions. More specifically, we utilize a "session-based query encoder" that learns the representations of each user's web search behavior prior to evacuation. Our proposed approach is empirically tested using web search data collected from users affected by a major flood in Japan. Results are validated using location data collected from mobile phones of the same set of users as ground truth. We show that evacuation decisions can be accurately predicted (84%) using only the users' pre-disaster web search data as input. This study proposes an alternative method for evacuation prediction that does not require highly sensitive location data, which can assist local governments to prepare effective first response strategies.Comment: Accepted in ACM KDD 201

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

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Predictive smart relaying schemes for decentralized wireless systems

Recent developments in decentralized wireless networks make the technology potentially deployable in an extremely broad scenarios and applications. These include mobile Internet of Things (IoT) networks, smart cities, future innovative communication systems with multiple aerial layer flying network platforms and other advanced mobile communication networks. The approach also could be the solution for traditional operated mobile network backup plans, balancing traffic flow, emergency communication systems and so on. This thesis reveals and addresses several issues and challenges in conventional wireless communication systems, particular for the cases where there is a lack of resources and the disconnection of radio links. There are two message routing plans in the data packet store, carry and forwarding form are proposed, known as KaFiR and PaFiR. These employ the Bayesian filtering approach to track and predict the motion of surrounding portable devices and determine the next layer among candidate nodes. The relaying strategies endow smart devices with the intelligent capability to optimize the message routing path and improve the overall network performance with respect to resilience, tolerance and scalability. The simulation and test results present that the KaFiR routing protocol performs well when network subscribers are less mobile and the relaying protocol can be deployed on a wide range of portable terminals as the algorithm is rather simple to operate. The PaFiR routing strategy takes advantages of the Particle Filter algorithm, which can cope with complex network scenarios and applications, particularly when unmanned aerial vehicles are involved as the assisted intermediate layers. When compared with other existing DTN routing protocols and some of the latest relaying plans, both relaying protocols deliver an excellent overall performance for the key wireless communication network evolution metrics, which shows the promising future for this brand new research direction. Further extension work directions based on the tracking and prediction methods are suggested and reviewed. Future work on some new applications and services are also addressed