Contextual Human Trajectory Forecasting within Indoor Environments and Its Applications

A human trajectory is the likely path a human subject would take to get to a destination. Human trajectory forecasting algorithms try to estimate or predict this path. Such algorithms have wide applications in robotics, computer vision and video surveillance. Understanding the human behavior can provide useful information towards the design of these algorithms. Human trajectory forecasting algorithm is an interesting problem because the outcome is influenced by many factors, of which we believe that the destination, geometry of the environment, and the humans in it play a significant role. In addressing this problem, we propose a model to estimate the occupancy behavior of humans based on the geometry and behavioral norms. We also develop a trajectory forecasting algorithm that understands this occupancy and leverages it for trajectory forecasting in previously unseen geometries. The algorithm can be useful in a variety of applications. In this work, we show its utility in three applications, namely person re-identification, camera placement optimization, and human tracking. Experiments were performed with real world data and compared to state-of-the-art methods to assess the quality of the forecasting algorithm and the enhancement in the quality of the applications. Results obtained suggests a significant enhancement in the accuracy of trajectory forecasting and the computer vision applications.Computer Science, Department o

Evaluating the Effectiveness of Tree Locations and Arrangements for Improving Urban Thermal Environment

abstract: Trees serve as a natural umbrella to mitigate insolation absorbed by features of the urban environment, especially building structures and pavements. For a desert community, trees are a particularly valuable asset because they contribute to energy conservation efforts, improve home values, allow for cost savings, and promote enhanced health and well-being. The main obstacle in creating a sustainable urban community in a desert city with trees is the scarceness and cost of irrigation water. Thus, strategically located and arranged desert trees with the fewest tree numbers possible potentially translate into significant energy, water and long-term cost savings as well as conservation, economic, and health benefits. The objective of this dissertation is to achieve this research goal with integrated methods from both theoretical and empirical perspectives. This dissertation includes three main parts. The first part proposes a spatial optimization method to optimize the tree locations with the objective to maximize shade coverage on building facades and open structures and minimize shade coverage on building rooftops in a 3-dimensional environment. Second, an outdoor urban physical scale model with field measurement is presented to understand the cooling and locational benefits of tree shade. The third part implements a microclimate numerical simulation model to analyze how the specific tree locations and arrangements influence outdoor microclimates and improve human thermal comfort. These three parts of the dissertation attempt to fill the research gap of how to strategically locate trees at the building to neighborhood scale, and quantifying the impact of such arrangements. Results highlight the significance of arranging residential shade trees across different geographical scales. In both the building and neighborhood scales, research results recommend that trees should be arranged in the central part of the building south front yard. More cooling benefits are provided to the building structures and outdoor microclimates with a cluster tree arrangement without canopy overlap; however, if residents are interested in creating a better outdoor thermal environment, open space between trees is needed to enhance the wind environment for better human thermal comfort. Considering the rapid urbanization process, limited water resources supply, and the severe heat stress in the urban areas, judicious design and planning of trees is of increasing importance for improving the life quality and sustaining the urban environment.Dissertation/ThesisDoctoral Dissertation Geography 201

Déploiement optimal de réseaux de capteurs dans des environnements intérieurs en support à la navigation des personnes à mobilité réduite

La participation sociale des personnes ayant une incapacité (PAI) est l'un des enjeux majeurs de notre société. La participation sociale des PAI est influencée par les résultats des interactions entre les facteurs personnels et les facteurs environnementaux (physiques et sociaux). L'une des activités quotidiennes les plus importantes en milieu urbain est la mobilité, ce qui est fondamental pour la participation sociale des PAI. L'environnement urbain est composé des infrastructures et des services principalement conçus pour les personnes sans incapacités et ne prend pas en compte les besoins spécifiques des PAI. Dans ce contexte, la conception et le développement des environnements intelligents peuvent contribuer à une meilleure mobilité et participation sociale des PAI grâce à l'avancement récent de technologie de l'information et de télécommunication ainsi que de réseaux de capteurs. Cependant, le déploiement de réseaux de capteurs en tant que technologie d'assistance pour améliorer la mobilité des personnes n'est conçu que sur la base des modèles trop simplistes de l'environnement physique. Bien que des approches de déploiement de réseaux de capteurs aient été développées ces dernières années, la plupart d'entre elles ont considéré le modèle simple des capteurs (cercle ou sphérique dans le meilleur des cas) et l'environnement 2D, (sans obstacle), indépendamment des besoins des PAI lors de leur mobilité. À cet égard, l'objectif global de cette thèse est le déploiement optimal de réseau de capteurs dans un environnement intérieur pour améliorer l'efficacité de la mobilité des personnes à mobilité réduite (PMR). Plus spécifiquement, nous sommes intéressés à la mobilité des personnes utilisatrices de fauteuil roulant manuel. Pour atteindre cet objectif global, trois objectifs spécifiques sont identifiés. Premièrement, nous proposons un cadre conceptuel pour l'évaluation de la lisibilité de l'environnement intérieur pour les PMR, afin de déterminer la méthode appropriée pour évaluer les interactions entre les facteurs personnels et les facteurs environnementaux (par exemple, pentes, rampes, marches, etc.). Deuxièmement, nous développons un algorithme d'optimisation locale basé sur la structure Voronoi 3D pour le déploiement de capteurs dans l'environnement intérieur 3D pour s'attaquer à la complexité de la structure de l'environnement intérieur (par exemple, différentes hauteurs de plafonds) afin de maximiser la couverture du réseau. Troisièmement, pour aider la mobilité des PMR, nous développons un algorithme d'optimisation ciblé pour le déploiement de capteurs multi-types dans l'environnement intérieur en tenant compte du cadre d'évaluation de la lisibilité pour les PMR. La question la plus importante de cette recherche est la suivante : quels sont les emplacements optimaux pour un ensemble des capteurs pour le positionnement et le guidage des PMR dans l'environnement intérieur complexe 3D. Pour répondre à cette question, les informations sur les caractéristiques des capteurs, les éléments environnementaux et la lisibilité des PMR ont été intégrés dans les algorithmes d'optimisation locale pour le déploiement de réseaux de capteurs multi-types, afin d'améliorer la couverture du réseau et d'aider efficacement les PMR lors de leur mobilité. Dans ce processus, le diagramme de Voronoi 3D, en tant que structure géométrique, est utilisé pour optimiser l'emplacement des capteurs en fonction des caractéristiques des capteurs, des éléments environnementaux et de la lisibilité des PMR. L'optimisation locale proposée a été mise en œuvre et testée avec plusieurs scénarios au Centre des congrès de Québec. La comparaison des résultats obtenus avec ceux des autres algorithmes démontre une plus grande efficacité de l'approche proposée dans cette recherche.Social participation of people with disabilities (PWD) is one of the challenging problems in our society. Social participation of PWD is influenced by results from the interactions between personal characteristics and the physical and social environments. One of the most significant daily activities in the urban environment is mobility which impacts on the social participation of PWD. The urban environment includes infrastructure and services are mostly designed for people without any disability and does not consider the specific needs of PWD. In this context, the design and development of intelligent environments can contribute to better mobility and social participation of PWD by leveraging the recent advancement in information and telecommunications technologies as well as sensor networks. Sensor networks, as an assistive technology for improving the mobility of people are generally designed based on the simplistic models of physical environment. Although sensor networks deployment approaches have been developed in recent years, the majority of them have considered the simple model of sensors (circle or spherical in the best case) and the environment (2D, without obstacles) regardless of the PWD needs during their mobility. In this regard, the global objective of this thesis is the determination of the position and type of sensors to enhance the efficiency of the people with motor disabilities (PWMD) mobility. We are more specifically interested in the mobility of people using manual wheelchair. To achieve this global objective, three specific objectives are demarcated. First, a framework is developed for legibility assessment of the indoor environment for PWMD to determine the appropriate method to evaluate the interactions between personal factors with environmental factors (e.g. slops, ramps, steps, etc.). Then, a local optimization algorithm based on 3D Voronoi structure for sensor deployment in the 3D indoor environment is developed to tackle the complexity of structure of indoor environment (e.g., various ceilings' height) to maximize the network coverage. Next, a purpose-oriented optimization algorithm for multi-type sensor deployment in the indoor environment to help the PWMD mobility is developed with consideration of the legibility assessment framework for PWMD. In this thesis, the most important question of this research is where the optimal places of sensors are for efficient guidance of the PWMD in their mobility in 3D complex indoor environments. To answer this question, the information of sensors characteristics, environmental elements and legibility of PWMD have been integrated into the local optimization algorithms for multi-type sensor networks deployment to enhance the network coverage as well as efficiently help the PWMD during their mobility. In this process, Voronoi diagram as a geometrical structure is used to change the sensors' location based on the sensor characteristics, environmental elements and legibility of PWMD. The proposed local optimization is implemented and tested for several scenarios in Quebec City Convention Centre. The obtained results show that these integration in our approach enhance its effectiveness compared to the existing methods

Poster Abstract: Connected Wireless Camera Network Deployment with Visibility Coverage

ABSTRACT First responder applications often require safety surveillance using wireless camera network