Collaborative visualization and virtual reality in construction projects

In the Colombian construction industry it is recognized as a general practice that di!erent designers deliver 2D drawings to the project construction team -- Some 3D modeling applications are used but only with commercial intentions, thus wasting visualization tools that facilitate the understanding of the project, that allow the coordination of plans between di!erent specialists, and that can prevent errors with high impact on costs in the construction phase of the project -- As a continuation of the project "immersive virtual reality for construction" developed by EAFIT University, the present work intends to demonstrate how a collaborative virtual environment can be helpful in order to improve visualization of construction projects and achieve the interaction of di!erent specialties, evaluating the impact of collaborative work in the design process of the same -- The end result of this research is an application created using freely available tools and a use case scenario on how this application can be used to perform review meetings by di!erent specialist in real time -- Initial test on the system has been made with civil engineering students showing that this virtual reality tool ease the burden of performing reviews where traditionally plans and sharing the same geographical space were neede

Deep Reinforcement Learning for Autonomous Search and Rescue

Unmanned Aerial Vehicles (UAVs) are becoming more prevalent every day. In addition, advances in battery life and electronic sensors have enabled the development of diverse UAV applications outside their original military domain. For example, Search and Rescue (SAR) operations can benefit greatly from modern UAVs since even the simplest commercial models are equipped with high-resolution cameras and the ability to stream video to a computer or portable device. As a result, autonomous unmanned systems (ground, aquatic, and aerial) have recently been employed for such typical SAR tasks as terrain mapping, task observation, and early supply delivery. However, these systems were developed before advances such as Google Deepmind’s breakthrough with the Deep Q-Network (DQN) technology. Therefore, most of them rely heavily on greedy or potential-based heuristics, without the ability to learn. In this research, we present two possible approximations (Partially Observable Markov Decision Processes) for enhancing the performance of autonomous UAVs in SAR by incorporating newly-developed Reinforcement Learning methods. The project utilizes open-source tools such as Microsoft’s state-of-the-art UAV simulator AirSim, and Keras, a machine learning framework that can make use of Google’s popular tensor library called TensorFlow. The main approach investigated in this research is the Deep Q-Network

Propuesta de mejoramiento del proceso software para una empresa de soluciones integrales de ingeniería de mantenimiento

Propuesta de Mejoramiento del Proceso Software para una empresa de soluciones integrales de ingeniería de mantenimiento, se trata de un proyecto elaborado con el propósito de obtener el título de Ingeniero de Sistemas para cada uno de sus realizadores, a través de la elaboración de un proyecto dirigido a propiciar la implementación del modelo CMMI en el desarrollo de los procesos de software de una pyme radicada en la ciudad de Medellín, que visionariamente ha permitido el acceso a su información corporativa con el objeto de obtener una propuesta de mejoramiento que habrá de verse reflejada, a largo plazo, en reconocimiento y competitividad dentro del mercado de servicios que ocupa su objeto social, y en el corto y mediano plazo, en la optimización de sus recursos a todo nivel y en la calidad de sus procesos.126 p.Contenido parcial: Descripción del modelo CMMI -- Identificación del contexto y de las oportunidades en la organización -- Estructura del área y del proceso de desarrollo de software -- Fase 1. Diseño de áreas de proceso -- Fase 2. Institucionalización de procesos diseñados