O PAPEL DA UNIVERSIDADE NA CONSTRUÇÃO DE CIDADES INTELIGENTES E HUMANAS

Universities play a fundamental role in the Human Smart Cities context. Thus, the development of a smart campus is recently a growing trend aiming at improving infrastructure and living conditions on universities campuses. Clearly, it is possible to correlate universities with cities in a compositional view, which shows the viability to test and build solutions inside campuses that later can be applied on the development of smart cities. The present paper describes the project Smart Campus UFPA, a study in progress for building a smart campus in the Federal University of Pará and, also, the mobile application called Smart UFPA, which has its initial focus on mobility. The project itself has as its objective to encourage the academic community to discuss and develop alternative solutions to the problems found in the university campus that may be scaled up to the city.As universidades desempenham um papel fundamental para o desenvolvimento das cidades inteligentes e humanas. Iniciativas de smart campus tornaram-se uma tendência crescente com o objetivo de melhorar a infraestrutura e vivência dentro dos campi universitários, bem como para promover soluções que impulsionem a inovação urbana. Nesse sentido, o presente artigo descreve o projeto Smart Campus UFPA, um estudo em progresso para a construção de um smart campus na Universidade Federal do Pará. Também, apresenta o primeiro resultado dessa iniciativa, o aplicativo móvel para Android, denominado Smart UFPA, o qual tem seu foco inicial na área de mobilidade. O projeto tem como objetivo engajar a comunidade para discutir e desenvolver soluções alternativas para os problemas encontrados no campus universitário, que possam ser, posteriormente, ampliadas para ajudar a melhorar o contexto urbano da cidade

An Evolutionary Density and Grid-Based Clustering Algorithm

Abstract. This paper presents EDACluster, an Estimation of Distribution Algorithm (EDA) applied to the clustering task. EDA is an Evolutionary Algorithm used here to optimize the search for adequate clusters when very little is known about the target dataset. The proposed algorithm uses a mixed approach – density and grid-based – to identify sets of dense cells in the dataset. The output is a list of items and their associated clusters. Items in low-density areas are considered noise and are not assigned to any cluster. This work uses four public domain datasets to perform the tests that compare EDACluster with DBSCAN, a conventional density-based clustering algorithm. 1

Tape-Shaped, Multiscale, and Continuous-Readable Fiducial Marker for Indoor Navigation and Localization Systems

The present study proposes a fiducial marker for location systems that uses computer vision. The marker employs a set of tape-shaped markers that facilitate their positioning in the environment, allowing continuous reading to cover the entire perimeter of the environment and making it possible to minimize interruptions in the location service. Because the marker is present throughout the perimeter of the environment, it presents hierarchical coding patterns that allow it to be robust against multiple detection scales. We implemented an application to help the user generate the markers with a floor plan image. We conducted two types of tests, one in a 3D simulation environment and one in a real-life environment with a smartphone. The tests made it possible to measure the performance of the tape-shaped marker with readings at multiple distances compared to ArUco, QRCode, and STag with detections at distances of 10 to 0.5 m. The localization tests in the 3D environment analyzed the time of marker detection during the journey from one room to another in positioning conditions (A) with the markers positioned at the baseboard of the wall, (B) with the markers positioned at camera height, and (C) with the marker positioned on the floor. The localization tests in real conditions allowed us to measure the time of detections in favorable conditions of detections, demonstrating that the tape-shaped-marker-detection algorithm is not yet robust against blurring but is robust against lighting variations, difficult angle displays, and partial occlusions. In both test environments, the marker allowed for detection at multiple scales, confirming its functionality