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

Development of transportation and supply chain problems with the combination of agent-based simulation and network optimization

Demand drives a different range of supply chain and logistics location decisions, and agent-based modeling (ABM) introduces innovative solutions to address supply chain and logistics problems. This dissertation focuses on an agent-based and network optimization approach to resolve those problems and features three research projects that cover prevalent supply chain management and logistics problems. The first case study evaluates demographic densities in Norway, Finland, and Sweden, and covers how distribution center (DC) locations can be established using a minimizing trip distance approach. Furthermore, traveling time maps are developed for each scenario. In addition, the Nordic area consisting of those three countries is analyzed and five DC location optimization results are presented. The second case study introduces transportation cost modelling in the process of collecting tree logs from several districts and transporting them to the nearest collection point. This research project presents agent-based modelling (ABM) that incorporates comprehensively the key elements of the pick-up and delivery supply chain model and designs the components as autonomous agents communicating with each other. The modelling merges various components such as GIS routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. The entire pick-up and delivery operation are modeled by ABM and modeling outcomes are provided by time series charts such as the number of trucks in use, facilities inventory and travel distance. In addition, various scenarios of simulation based on potential facility locations and truck numbers are evaluated and the optimal facility location and fleet size are identified. In the third case study, an agent-based modeling strategy is used to address the problem of vehicle scheduling and fleet optimization. The solution method is employed to data from a real-world organization, and a set of key performance indicators are created to assess the resolution's effectiveness. The ABM method, contrary to other modeling approaches, is a fully customized method that can incorporate extensively various processes and elements. ABM applying the autonomous agent concept can integrate various components that exist in the complex supply chain and create a similar system to assess the supply chain efficiency.Tuotteiden kysyntä ohjaa erilaisia toimitusketju- ja logistiikkasijaintipäätöksiä, ja agenttipohjainen mallinnusmenetelmä (ABM) tuo innovatiivisia ratkaisuja toimitusketjun ja logistiikan ongelmien ratkaisemiseen. Tämä väitöskirja keskittyy agenttipohjaiseen mallinnusmenetelmään ja verkon optimointiin tällaisten ongelmien ratkaisemiseksi, ja sisältää kolme tapaustutkimusta, jotka voidaan luokitella kuuluvan yleisiin toimitusketjun hallinta- ja logistiikkaongelmiin. Ensimmäinen tapaustutkimus esittelee kuinka käyttämällä väestötiheyksiä Norjassa, Suomessa ja Ruotsissa voidaan määrittää strategioita jakelukeskusten (DC) sijaintiin käyttämällä matkan etäisyyden minimoimista. Kullekin skenaariolle kehitetään matka-aikakartat. Lisäksi analysoidaan näistä kolmesta maasta koostuvaa pohjoismaista aluetta ja esitetään viisi mahdollista sijaintia optimointituloksena. Toinen tapaustutkimus esittelee kuljetuskustannusmallintamisen prosessissa, jossa puutavaraa kerätään useilta alueilta ja kuljetetaan lähimpään keräyspisteeseen. Tämä tutkimusprojekti esittelee agenttipohjaista mallinnusta (ABM), joka yhdistää kattavasti noudon ja toimituksen toimitusketjumallin keskeiset elementit ja suunnittelee komponentit keskenään kommunikoiviksi autonomisiksi agenteiksi. Mallinnuksessa yhdistetään erilaisia komponentteja, kuten GIS-reititys, mahdolliset tilojen sijainnit, satunnaiset puunhakupaikat, kaluston mitoitus, matkan pituus sekä monimuotokuljetukset. ABM:n avulla mallinnetaan noutojen ja toimituksien koko ketju ja tuloksena saadaan aikasarjoja kuvaamaan käytössä olevat kuorma-autot, sekä varastomäärät ja ajetut matkat. Lisäksi arvioidaan erilaisia simuloinnin skenaarioita mahdollisten laitosten sijainnista ja kuorma-autojen lukumäärästä sekä tunnistetaan optimaalinen toimipisteen sijainti ja tarvittava autojen määrä. Kolmannessa tapaustutkimuksessa agenttipohjaista mallinnusstrategiaa käytetään ratkaisemaan ajoneuvojen aikataulujen ja kaluston optimoinnin ongelma. Ratkaisumenetelmää käytetään dataan, joka on peräisin todellisesta organisaatiosta, ja ratkaisun tehokkuuden arvioimiseksi luodaan lukuisia keskeisiä suorituskykyindikaattoreita. ABM-menetelmä, toisin kuin monet muut mallintamismenetelmät, on täysin räätälöitävissä oleva menetelmä, joka voi sisältää laajasti erilaisia prosesseja ja elementtejä. Autonomisia agentteja soveltava ABM voi integroida erilaisia komponentteja, jotka ovat olemassa monimutkaisessa toimitusketjussa ja luoda vastaavan järjestelmän toimitusketjun tehokkuuden arvioimiseksi yksityiskohtaisesti.fi=vertaisarvioitu|en=peerReviewed

Developing Early Risk Detection and Preparedness System with Risk Analysis and Contingency Plan

PresentationWhen the natural or human-made disasters, such as hurricanes, floods, tornadoes, wildfires and gas leaks, threaten a populated area, mass casualties and property losses may be followed. To avoid, minimize or eliminate the risks for public safety, a well-organized early risk detection and preparedness system is needed in order to save lives and minimize losses. To make this early detection system efficient yet effective, a mobile app, risk preparedness aid, was developed. This aid system can communicate with sensors, location information, and disaster management server. The aid was designed using the concepts of location based service and risk management and it includes gas leak detection, warning and emergency evacuation procedure with routing. Based on the identified risks and preparing procedure, various contingency plans were developed. The contingency plans should be very clear so that it is easy for public and employee to follow. Because each system has unique infrastructure its contingency plan must be unique. This paper also shows an evacuation process in the form of a flowchart for ease of use in the event of an emergency

Évaluation et la représentation spatiotemporelle de l'accessibilité des réseaux piétonniers pour le déplacement des personnes à mobilité réduite

La mobilité des personnes à mobilité réduite (PMR) joue un rôle important dans leur inclusion sociale. Les PMR ont besoin de se déplacer de manière autonome pour effectuer leurs routines quotidiennes comme aller à l'école, au travail, au centre de remise en forme ou faire du magasinage. Cependant, celles-ci ne sont pas entièrement exécutées en raison de la conception non-adaptée des villes pour ces personnes. En effet, la mobilité est une habitude de vie humaine qui est le résultat d'interactions entre les facteurs humains (par exemple, les capacités) et les facteurs environnementaux. Au cours des dernières années, la mise au point de technologies d’aide technique s'est développée progressivement pour permettre aux PMR d’améliorer leur qualité de vie. En particulier, ces technologies offrent une variété de caractéristiques qui permettent à ces personnes de surmonter divers obstacles qui réduisent leur mobilité et contribuent à leur exclusion sociale. Cependant, malgré la disponibilité des technologies d’aide à la navigation et à la mobilité, leur potentiel est mal exploité pour les PMR. En effet, ces technologies ne considèrent pas les interactions « humain-environnement » adéquatement pour ces utilisateurs. L'objectif général de cette thèse est d'utiliser les potentiels des méthodes et des technologies de science de l'information géographique (SIG) afin d’aider à surmonter les problèmes de mobilité des PMR en créant un cadre d'évaluation de l'accessibilité et en développant une approche personnalisée de routage qui prend en compte les profils de ces personnes. Pour atteindre ce but, quatre objectifs spécifiques sont considérés: 1) développer une ontologie de mobilité pour les PMR qui considère les facteurs personnels et environnementaux, 2) proposer une méthode de l’évaluation de l'accessibilité du réseau piétonnier pour la mobilité des PMR en considérant spécifiquement les interactions entre les facteurs humains (la confiance) et les facteurs environnementaux, 3) étudier le rôle des facteurs sociaux dans l'accessibilité des zones urbaines et, finalement, 4) affiner les algorithmes existants pour calculer les itinéraires accessibles personnalisés pour les PMR en considérant leurs profils. En effet, tout d'abord pour développer une ontologie pour la mobilité des PMR, la dimension sociale de l'environnement ainsi que la dimension physique sont intégrées et une nouvelle approche basée sur une perspective « nature-développement » est présentée. Ensuite, une approche fondée sur la confiance des PMR est développée pour l'évaluation de l'accessibilité du réseau piétonnier, compte tenu de l'interaction entre les facteurs personnels et les facteurs environnementaux. De plus, dans une perspective de considération des facteurs sociaux, le rôle des actions politiques sur l'accessibilité du réseau piétonnier est étudié et l'influence de trois politiques potentielles est analysée. Enfin, une nouvelle approche pour calculer des itinéraires personnalisés pour les PMR en tenant compte de leurs perceptions, de leurs préférences et de leurs confidences est proposée. Les approches proposées sont développées et évaluées dans le quartier Saint-Roch à Québec, et ce, en utilisant une application d'assistance mobile et multimodale développée dans le cadre du projet MobiliSIG.Mobility of people with motor disabilities (PWMD) plays a significant role in their social inclusion. PWMD need to move around autonomously to perform their daily routines such as going to school, work, shopping, and going to fitness centers. However, mostly these needs are not accomplished because of either limitations concerning their capabilities or inadequate city design. Indeed, mobility is a human life habit, which is the result of interactions between people and their surrounded environments. In recent years, assistive technologies have been increasingly developed to enable PWMD to live independently and participate fully in all aspects of life. In particular, these technologies provide a variety of features that allow these individuals to overcome diverse obstacles that reduce their mobility and contribute to their social exclusion. However, despite increasing availability of assistive technologies for navigation and mobility, their potential is poorly exploited for PWMD. Indeed, these technologies do not fully consider the human-environment interactions. The overall goal of this dissertation is to benefit from the potentials of methods and technologies of the Geographic Information Sciences (GIS) in order to overcome the mobility issues of PWMD by creating an accessibility-assessing framework and ultimately by developing a personalized routing approach, which better considers the humanenvironment interaction. To achieve this goal, four specific objectives were followed: 1) develop a mobility ontology for PWMD that considers personal factors as well as environmental factors, 2) propose a method to evaluate the accessibility of the pedestrian network for the mobility of PWMD considering the interactions between human factors (confidence) and the environmental factors, 3) study of the role of social factors in the accessibility of urban areas, and finally, 4) refine the existing algorithms to calculate accessible routes for PWMD considering their profile. First, to develop an adapted ontology for mobility of the PWMD, the social dimension of the environment with the physical dimension were integrated and a new approach based on a “Nature-Development” perspective was presented. This perspective led to the development of useful ontologies, especially for defining the relationships between the social and physical parts of the environment. Next, a confidence-based approach was developed for evaluation of the accessibility of pedestrian network considering the interaction between personal factors and environmental factors for the mobility of PWMD. In addition, the role of policy actions on the accessibility of the pedestrian network was investigated and the influence of three potential policies was analyzed. Finally, a novel approach to compute personalized routes for PWMD considering their perception, preferences, and confidences was proposed. The approaches proposed were implemented in the Saint-Roch area of Quebec City and visualized within the multimodal mobile assistive technology (MobiliSIG) applicatio

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 Protection

Facility Location Planning Under Disruption

Facility Location Problems (FLPs) such as the Uncapacitated Facility Location (UFL) and the Capacitated Facility Location (CFL) along with the k-Shortest Path Problem (k-SPP) are important research problems in managing supply chain networks (SCNs) and related operations. In UFL, there is no limit on the facility serving capacity while in CFL such limit is imposed. FLPs aim to find the best facility locations to meet the customer demands within the available capacity with minimized facility establishment and transportation costs. The objective of the (k-SPP) is to find the k minimal length and partial overlapping paths between two nodes in a transport network graph. In the literature, many approaches are proposed to solve these problems. However, most of these approaches assume totally reliable facilities and do not consider the failure probability of the facilities, which can lead to notably higher cost. In this thesis, we investigate the reliable uncapacitated facility location (RUFL)and the reliable capacitated facility location (RCFL) problems, and the k-SPP where potential facilities are exposed to disruption then propose corresponding solution approaches to efficiently handle these problems. An evolutionary learning technique is elaborated to solve RUFL. Then, a non-linear integer programming model is introduced for the RCFL along with a solution approach involving the linearization of the model and its use as part of an iterative procedure leveraging CPLEX for facility establishment and customer assignment along with a knapsack implementation aiming at deriving the best facility fortification. In RUFL and RCFL, we assume heterogeneous disruption with respect to the facilities, each customer is assigned to primary and backup facilities and a fixed fortification budget allows to make a subset of the facilities totally reliable. Finally, we propose a hybrid approach based on graph partitioning and modified Dijkstra algorithm to find k partial overlapping shortest paths between two nodes on a transport network that is exposed to heterogeneous connected node failures. The approaches are illustrated via individual case studies along with corresponding key insights. The performance of each approach is assessed using benchmark results. For the k-SPP, the effect of preferred establishment locations is analyzed with respect to disruption scenarios, failure probability, computation time, transport costs, network size and partitioning parameters

Geographic Information Systems and Science

Geographic information science (GISc) has established itself as a collaborative information-processing scheme that is increasing in popularity. Yet, this interdisciplinary and/or transdisciplinary system is still somewhat misunderstood. This book talks about some of the GISc domains encompassing students, researchers, and common users. Chapters focus on important aspects of GISc, keeping in mind the processing capability of GIS along with the mathematics and formulae involved in getting each solution. The book has one introductory and eight main chapters divided into five sections. The first section is more general and focuses on what GISc is and its relation to GIS and Geography, the second is about location analytics and modeling, the third on remote sensing data analysis, the fourth on big data and augmented reality, and, finally, the fifth looks over volunteered geographic information.info:eu-repo/semantics/publishedVersio

A Spatial Agent-based Model for Volcanic Evacuation of Mt. Merapi

Natural disasters, especially volcanic eruptions, are hazardous events that frequently happen in Indonesia. As a country within the “Ring of Fire”, Indonesia has hundreds of volcanoes and Mount Merapi is the most active. Historical studies of this volcano have revealed that there is potential for a major eruption in the future. Therefore, long-term disaster management is needed. To support the disaster management, physical and socially-based research has been carried out, but there is still a gap in the development of evacuation models. This modelling is necessary to evaluate the possibility of unexpected problems in the evacuation process since the hazard occurrences and the population behaviour are uncertain. The aim of this research was to develop an agent-based model (ABM) of volcanic evacuation to improve the effectiveness of evacuation management in Merapi. Besides the potential use of the results locally in Merapi, the development process of this evacuation model contributes by advancing the knowledge of ABM development for large-scale evacuation simulation in other contexts. Its novelty lies in (1) integrating a hazard model derived from historical records of the spatial impact of eruptions, (2) formulating and validating an individual evacuation decision model in ABM based on various interrelated factors revealed from literature reviews and surveys that enable the modelling of reluctant people, (3) formulating the integration of multi-criteria evaluation (MCE) in ABM to model a spatio-temporal dynamic model of risk (STDMR) that enables representation of the changing of risk as a consequence of changing hazard level, hazard extent and movement of people, and (4) formulating an evacuation staging method based on MCE using geographic and demographic criteria. The volcanic evacuation model represents the relationships between physical and human agents, consisting of the volcano, stakeholders, the population at risk and the environment. The experimentation of several evacuation scenarios in Merapi using the developed ABM of evacuation shows that simultaneous strategy is superior in reducing the risk, but the staged scenario is the most effective in minimising the potential of road traffic problems during evacuation events in Merapi. Staged evacuation can be a good option when there is enough time to evacuate. However, if the evacuation time is limited, the simultaneous strategy is better to be implemented. Appropriate traffic management should be prepared to avoid traffic problems when the second option is chosen

Improving the Reliability of Optimised Link State Routing Protocol in Smart Grid’s Neighbour Area Network

A reliable and resilient communication infrastructure that can cope with variable application traffic types and delay objectives is one of the prerequisites that differentiates a Smart Grid from the conventional electrical grid. However, the legacy communication infrastructure in the existing electrical grid is insufficient, if not incapable of satisfying the diverse communication requirements of the Smart Grid. The IEEE 802.11 ad hoc Wireless Mesh Network (WMN) is re-emerging as one of the communication networks that can significantly extend the reach of Smart Grid to backend devices through the Advanced Metering Infrastructure (AMI). However, the unique characteristics of AMI application traffic in the Smart Grid poses some interesting challenges to conventional communication networks including the ad hoc WMN. Hence, there is a need to modify the conventional ad hoc WMN, to address the uncertainties that may exist in its applicability in a Smart Grid environment. This research carries out an in-depth study of the communication of Smart Grid application traffic types over ad hoc WMN deployed in the Neighbour Area Network (NAN). It begins by conducting a critical review of the application characteristics and traffic requirements of several Smart Grid applications and highlighting some key challenges. Based on the reviews, and assuming that the application traffic types use the internet protocol (IP) as a transport protocol, a number of Smart Grid application traffic profiles were developed. Through experimental and simulation studies, a performance evaluation of an ad hoc WMN using the Optimised Link State Routing (OLSR) routing protocol was carried out. This highlighted some capacity and reliability issues that routing AMI application traffic may face within a conventional ad hoc WMN in a Smart Grid NAN. Given the fact that conventional routing solutions do not consider the traffic requirements when making routing decisions, another key observation is the inability of link metrics in routing protocols to select good quality links across multiple hops to a destination and also provide Quality of Service (QoS) support for target application traffic. As with most routing protocols, OLSR protocol uses a single routing metric acquired at the network layer, which may not be able to accommodate different QoS requirements for application traffic in Smart Grid. To address these problems, a novel multiple link metrics approach to improve the reliability performance of routing in ad hoc WMN when deployed for Smart Grid is presented. It is based on the OLSR protocol and explores the possibility of applying QoS routing for application traffic types in NAN based ad hoc WMN. Though routing in multiple metrics has been identified as a complex problem, Multi-Criteria Decision Making (MCDM) techniques such as the Analytical Hierarchy Process (AHP) and pruning have been used to perform such routing on wired and wireless multimedia applications. The proposed multiple metrics OLSR with AHP is used to offer the best available route, based on a number of considered metric parameters. To accommodate the variable application traffic requirements, a study that allows application traffic to use the most appropriate routing metric is presented. The multiple metrics development is then evaluated in Network Simulator 2.34; the simulation results demonstrate that it outperforms existing routing methods that are based on single metrics in OLSR. It also shows that it can be used to improve the reliability of application traffic types, thereby overcoming some weaknesses of existing single metric routing across multiple hops in NAN. The IEEE 802.11g was used to compare and analyse the performance of OLSR and the IEEE 802.11b was used to implement the multiple metrics framework which demonstrate a better performance than the single metric. However, the multiple metrics can also be applied for routing on different IEEE wireless standards, as well as other communication technologies such as Power Line Communication (PLC) when deployed in Smart Grid NAN

Optimizing Integrated Municipal Solid Waste Management System under Multiple Uncertainties

To define a holistic and systematic approach to municipal waste management, an integrated municipal solid waste management (IMSWM) system is proposed. This system includes functional elements of waste generation, source handling, and processing, waste collection, waste processing at facilities, transfer, and disposal. Multi-objective optimization algorithms are used to develop an optimum IMSWM that can satisfy all main pillars of sustainable development, aiming to minimize the total cost of the system (economic), and minimize the total greenhouse gas emissions (environmental), while maximizing the total social suitability of the system (social). For the social objective, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to identify the main parameters that affect the social suitability of the system. This research focuses on developing an optimized holistic model that considers all four main components of a modern IMSWM namely transfer, recycling, treatment, and disposal. The model is formulated as a mixed-integer linear programming (MILP) problem and solved using the epsilon constraint handling method. A metaheuristic method is developed using non dominated sorting genetic algorithm (NSGA) to deal with larger problems. A solution repair function is developed to handle several equality constraints included in the proposed IMSWM model. Sensitivity analyses are conducted to identify the effect of changes in parameters on the objective functions. Based on the results, the proposed metaheuristic algorithm based on NSGA-II performed better than other algorithms. The interval-parameter programming (IPP) methods are used to consider various uncertainties that exist in the system. The model is applied to the case study of the Australian capital territory (ACT). The data is gathered from several resources including Australian national waste reports, and ACT government transport Canberra and city services (TCCS). Based on the waste characteristic and city map several feasible scenarios are recommended. Several non-dominated solutions are identified for the model that the decision-maker can choose the most desirable solution based on the preferences. Based on the importance of any objective function at any time the decision-maker can choose a solution to suit the needs