Smart Cities and M³: Rapid Research, Meaningful Metrics and Co-Design

The research described in this paper is undertaken under the banner of the smart city, a concept that captures the way urban spaces are re-made by the incursion of new technology. Much of smart is centred on converting everyday activities into data, and using this data to generate knowledge mediated by technology. Ordinary citizens, those that may have their lives impacted by the technology, usually are not properly involved in the ‘smartification’ process. Their perceptions, concerns and expectations should inform the conception and development of smart technologies at the same extent. How to engage general public with smart cities research is the central challenge for the Making Metrics Meaningful (MMM) project. Applying a rapid participatory method, ‘Imagine’ over a five-month period (March – July) the research sought to gain insights from the general public into novel forms of information system innovation. This brief paper describes the nature of the accelerated research undertaken and explores some of the themes which emerged in the analysis. Generic themes, beyond the remit of an explicit transport focus, are developed and pointers towards further research directions are discussed. Participatory methods, including engaging with self- selected transport users actively through both picture creation and programmatically specific musical ‘signatures’ as well as group discussion, were found to be effective in eliciting users’ own concerns, needs and ideas for novel information systems

Enrichment of OpenStreetMap data completeness with sidewalk geometries using data mining techniques

Tailored routing and navigation services utilized by wheelchair users require certain information about sidewalk geometries and their attributes to execute efficiently. Except some minor regions/cities, such detailed information is not present in current versions of crowdsourced mapping databases including OpenStreetMap. CAP4Access European project aimed to use (and enrich) OpenStreetMap for making it fit to the purpose of wheelchair routing. In this respect, this study presents a modified methodology based on data mining techniques for constructing sidewalk geometries using multiple GPS traces collected by wheelchair users during an urban travel experiment. The derived sidewalk geometries can be used to enrich OpenStreetMap to support wheelchair routing. The proposed method was applied to a case study in Heidelberg, Germany. The constructed sidewalk geometries were compared to an official reference dataset ("ground truth dataset"). The case study shows that the constructed sidewalk network overlays with 96% of the official reference dataset. Furthermore, in terms of positional accuracy, a low Root Mean Square Error (RMSE) value (0.93 m) is achieved. The article presents our discussion on the results as well as the conclusion and future research directions

A Service-Oriented Approach to Crowdsensing for Accessible Smart Mobility Scenarios

This work presents an architecture to help designing and deploying smart mobility applications. The proposed solution builds on the experience already matured by the authors in different fields: crowdsourcing and sensing done by users to gather data related to urban barriers and facilities, computation of personalized paths for users with special needs, and integration of open data provided by bus companies to identify the actual accessibility features and estimate the real arrival time of vehicles at stops. In terms of functionality, the first “monolithic” prototype fulfilled the goal of composing the aforementioned pieces of information to support citizens with reduced mobility (users with disabilities and/or elderly people) in their urban movements. In this paper, we describe a service-oriented architecture that exploits the microservices orchestration paradigm to enable the creation of new services and to make the management of the various data sources easier and more effective. The proposed platform exposes standardized interfaces to access data, implements common services to manage metadata associated with them, such as trustworthiness and provenance, and provides an orchestration language to create complex services, naturally mapping their internal workflow to code. The manuscript demonstrates the effectiveness of the approach by means of some case studies

A Systematic Review of Urban Navigation Systems for Visually Impaired People

Blind and Visually impaired people (BVIP) face a range of practical difficulties when undertaking outdoor journeys as pedestrians. Over the past decade, a variety of assistive devices have been researched and developed to help BVIP navigate more safely and independently. In~addition, research in overlapping domains are addressing the problem of automatic environment interpretation using computer vision and machine learning, particularly deep learning, approaches. Our aim in this article is to present a comprehensive review of research directly in, or relevant to, assistive outdoor navigation for BVIP. We breakdown the navigation area into a series of navigation phases and tasks. We then use this structure for our systematic review of research, analysing articles, methods, datasets and current limitations by task. We also provide an overview of commercial and non-commercial navigation applications targeted at BVIP. Our review contributes to the body of knowledge by providing a comprehensive, structured analysis of work in the domain, including the state of the art, and guidance on future directions. It will support both researchers and other stakeholders in the domain to establish an informed view of research progress

On combining crowdsourcing, sensing and open data for an accessible smart city

This work presents a novel geospatial mapping service, based on OpenStreetMap, which has been designed and developed in order to provide personalized path to users with special needs. This system gathers data related to barriers and facilities of the urban environment via crowdsourcing and sensing done by users. It also considers open data provided by bus operating companies to identify the actual accessibility feature and the real time of arrival at the stops of the buses. The resulting service supports citizens with reduced mobility (users with disabilities and/or elderly people) suggesting urban paths accessible to them and providing information related to travelling time, which are tailored to their abilities to move and to the bus arrival time. The manuscript demonstrates the effectiveness of the approach by means of a case study focusing on the differences between the solutions provided by our system and the ones computed by main stream geospatial mapping services

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

Mining Heterogeneous Urban Data at Multiple Granularity Layers

The recent development of urban areas and of the new advanced services supported by digital technologies has generated big challenges for people and city administrators, like air pollution, high energy consumption, traffic congestion, management of public events. Moreover, understanding the perception of citizens about the provided services and other relevant topics can help devising targeted actions in the management. With the large diffusion of sensing technologies and user devices, the capability to generate data of public interest within the urban area has rapidly grown. For instance, different sensors networks deployed in the urban area allow collecting a variety of data useful to characterize several aspects of the urban environment. The huge amount of data produced by different types of devices and applications brings a rich knowledge about the urban context. Mining big urban data can provide decision makers with knowledge useful to tackle the aforementioned challenges for a smart and sustainable administration of urban spaces. However, the high volume and heterogeneity of data increase the complexity of the analysis. Moreover, different sources provide data with different spatial and temporal references. The extraction of significant information from such diverse kinds of data depends also on how they are integrated, hence alternative data representations and efficient processing technologies are required. The PhD research activity presented in this thesis was aimed at tackling these issues. Indeed, the thesis deals with the analysis of big heterogeneous data in smart city scenarios, by means of new data mining techniques and algorithms, to study the nature of urban related processes. The problem is addressed focusing on both infrastructural and algorithmic layers. In the first layer, the thesis proposes the enhancement of the current leading techniques for the storage and elaboration of Big Data. The integration with novel computing platforms is also considered to support parallelization of tasks, tackling the issue of automatic scaling of resources. At algorithmic layer, the research activity aimed at innovating current data mining algorithms, by adapting them to novel Big Data architectures and to Cloud computing environments. Such algorithms have been applied to various classes of urban data, in order to discover hidden but important information to support the optimization of the related processes. This research activity focused on the development of a distributed framework to automatically aggregate heterogeneous data at multiple temporal and spatial granularities and to apply different data mining techniques. Parallel computations are performed according to the MapReduce paradigm and exploiting in-memory computing to reach near-linear computational scalability. By exploring manifold data resolutions in a relatively short time, several additional patterns of data can be discovered, allowing to further enrich the description of urban processes. Such framework is suitably applied to different use cases, where many types of data are used to provide insightful descriptive and predictive analyses. In particular, the PhD activity addressed two main issues in the context of urban data mining: the evaluation of buildings energy efficiency from different energy-related data and the characterization of people's perception and interest about different topics from user-generated content on social networks. For each use case within the considered applications, a specific architectural solution was designed to obtain meaningful and actionable results and to optimize the computational performance and scalability of algorithms, which were extensively validated through experimental tests

Succeeding with Smart People Initiatives: Difficulties and Preconditions for Smart City Initiatives that Target Citizens

Smart City is a paradigm for the development of urban spaces through the implementation of state-of-the-art ICT. There are two main approaches when developing Smart Cities: top-down and bottom-up. Based on the bottom-up approach, the concepts of Smart People and Smart Communities have emerged as dimensions of the Smart City, advocating for the engagement of citizens in Smart People initiatives. The aim of this research is both to find the types of Smart People initiatives and to identify their difficulties and preconditions for success. However, such initiatives that aim to (1) leverage the citizens intellectually and (2) use citizens as a source of input for ideas and innovation, are understudied. Therefore, this research proposes a concentrated framework of Smart People initiatives from an extensive literature review. On one hand, this framework contributes with a common ground and vocabulary that facilitates the dialogue within and between practitioners and academia. On the other hand, the identification of difficulties and preconditions guides the academia and practitioners in how to successfully account for citizens in the Smart City. From the literature review and the conduct of case studies of five European cities, participation came out as the key difficulty across both types of Smart People initiatives and cases, closely followed by awareness, motivation and complexity

Développement d'une application mobile adaptée à la navigation des personnes à mobilité réduite

Actuellement, l'usage d'un système d'aide à la navigation est devenu de plus en plus indispensable dans la vie quotidienne. Cependant, les systèmes existants ne sont pas adaptés à la navigation des personnes à mobilité réduite (PMR) utilisatrices d'un fauteuil roulant. De nombreux projets ont été créés, comme Wegoto en France ou Route4U en Hongrie. Au Canada, le projet multidisciplinaire MobiliSIG a été lancé en 2013. Ce projet vise à concevoir et développer des technologies géospatiales de navigation selon les principes de la conception cognitive pour assister les PMR dans leurs déplacements quotidiens et leur accès à l'environnement. L'objectif global du présent projet est la conception d'un système mobile de planification de trajet et de guidage pendant la navigation, multimodal et adapté aux différents profils de personnes à mobilité réduite utilisatrices de fauteuil roulant. Pour commencer, nous avons passé en revue la littérature relative aux concepts liés à notre problématique. Ensuite, nous avons proposé une approche d'aide à la navigation qui combine des éléments de guidage pas à pas avec des informations sur des repères ainsi que de différents éléments pertinents (points d'intérêts, obstacles/facilitateurs, ...) pour la description d'un trajet personnalisé et adapté au profil des PMR. Finalement, en nous appuyant sur les principes de la conception modulaire et sur le concept des applications mobiles riches (AMR), nous avons conçu et développé une solution mobile composée de trois modules : un module profil pour gérer le profil et les préférences de l'utilisateur, un module de planification qui gère la planification adaptée des itinéraires et un module de navigation pour fournir un guidage multimodal (visuel, vocal et haptique) pendant la navigation en tenant compte de profil de l'utilisateur.Currently, the use of a navigation aid system has become more and more essential in daily life. However, the existing systems are not adapted to the navigation of people with reduced mobility (PRM) using a wheelchair. Many projects have been created, such as Wegoto in France or Route4U in Hungary. In Canada, the multidisciplinary project MobiliSIG was launched in 2013. This project aims to design and develop geospatial navigation technologies according to the principles of cognitive design to assist PRMs in their daily travel and access to the environment. The overall objective of this project is the design of a mobile route planning and guidance system during navigation, multimodal and adapted to the different profiles of wheelchair users with reduced mobility. To begin, we reviewed the literature related to the concepts of our problem. Then, we proposed a navigation aid approach that combines step-by-step guidance elements with information on landmarks and different relevant elements (points of interest, obstacles/facilitators, ...) for the description of a personalized path adapted to the profile of PRM. Finally, based on the principles of modular design and the concept of rich mobile applications (RMAs), we designed and developed a mobile solution composed of three modules: a profile module to manage the user's profile and preferences; a planning module to manage the adapted route planning; and a navigation module to provide multimodal guidance (visual, voice and haptic) during navigation taking into account the user's profile