1,721,071 research outputs found
GeoAI: a review of artificial intelligence approaches for the interpretation of complex geomatics data
No full textResearchers have explored the benefits and applications of modern artificial intelligence (AI) algorithms in different scenarios. For the processing of geomatics data, AI offers overwhelming opportunities. Fundamental questions include how AI can be specifically applied to or must be specifically created for geomatics data. This change is also having a significant impact on geospatial data. The integration of AI approaches in geomatics has developed into the concept of geospatial artificial intelligence (GeoAI), which is a new paradigm for geographic knowledge discovery and beyond. However, little systematic work currently exists on how researchers have applied AI for geospatial domains. Hence, this contribution outlines AI-based techniques for analysing and interpreting complex geomatics data. Our analysis has covered several gaps, for instance defining relationships between AI-based approaches and geomatics data. First, technologies and tools used for data acquisition are outlined, with a particular focus on red-green-blue (RGB) images, thermal images, 3D point clouds, trajectories, and hyperspectral-multispectral images. Then, how AI approaches have been exploited for the interpretation of geomatic data is explained. Finally, a broad set of examples of applications is given, together with the specific method applied. Limitations point towards unexplored areas for future investigations, serving as useful guidelines for future research directions
A Geodatabase for Multisource Data Management Applied to Cultural Heritage: The Case Study of Villa Buonaccorsi's Historical Garden
Full text linkIn recent years, the digitization of historical data related to the architectural heritage and the development of ICT-based methodologies applied to cultural goods have become increasingly relevant. In this context, the use of GIS (Geographical Information System) is growing significantly, with the aim of collecting, analysing and managing heterogeneous data in a spatial context. Given such premise, the site identified for this case-study is a historical Italian Garden into the Villa Buonaccorsi in Potenza Picena (MC, Italy). The project aims at creating a methodology, that organizing natural and artificial elements in the GIS, to support management and planning of this landscape architecture, considering also the changes during the time. A suitable GIS can promote and ensure a correct use of the heritage knowledge, preserving the historical identity, overlaying the data. The data management system, specifically developed for this case, is based on an open source GIS, where surveyed data coming from different sources and the relation to the attributes have been descripted in a conceptual model. The inventory of this geodatabase, in a dedicated GIS, has allowed to perform some queries, making in output a dialogue box with all the information, in form of report, useful to the manager of a historical garden. The structure of the GIS can significantly to help who works with similar cases and it can be useful for analysis, management, storage and integration of information related to Italian gardens
eTourism: ICT and its role for tourism management
No full textPurpose: This paper aims to present innovative information and communication technology (ICT) infrastructure specifically designed and optimized for the tourism sector. The case presented, “La Valle del Pensare lungo il corso del Potenza”, has been conceived with the aim of providing a digital infrastructure to ten municipalities in the Marche Region (Italy), nestled among the valley of the Potenza River. This research project is aimed at developing an important communication system that facilitates the tourist routes of mining attractions and specific thematic routes across the territory, promoting historical centers, cultural heritage, green areas and interesting places. Design/methodology/approach: “La Valle del Pensare” information system has the main feature of being scalable and multi-purpose, as the contents can be managed and conveyed through the website, app mobile, totem touch screen and standard tourist signage. It is integrated and modular and allows to manage multiple information, ensuring an interoperable and multi-channel approach. It is designed for small municipalities in the province of Macerata to connect the territory’s resources and activities through a network. Findings: This work represents an important communication system, i.e. innovative ICT infrastructure that facilitates the tourist routes of mining attractions and specific thematic routes across the territory. Thanks to the collection of user-generated data, the platform allows monitoring of usage statistics and performances. In this way, the municipalities can infer useful information about user’s preferences and needs. The paper also discusses how “La Valle del Pensare” gives identity to the territory, which is not identified as a simple summation of the Common, but as a recognizable system that intends to implement the level of competitiveness through the creation of a real territorial logo able to identify vocations and specificity of the Valley of the Potenza. Originality/value: The value of the project lies in the ICT system, able to convey information at different scales, providing the users with updated contents; at the same time, administrations can constantly monitor its performances, being able to infer useful information about tourists’ needs, habits and preferences. The main contributions are the creation of a single cloud-based architecture for the management of multiple multi- media contents, to be exploited in various platforms; the design of a unique content management system used by several small municipalities of a same territory; the monitoring user’s preferences and needs by collecting users’ generated data; and the analysis of meaningful statistics about the tourists, tested and verified in real scenario with real users
SeSAME: Re-identification-based ambient intelligence system for museum environment
Full text linkNowadays, understanding and analysing visitors activities and behaviours is becoming imperative for personalising and improving the user experience in a museum environment. Users' behaviour can provide important statistics, insights and objective information about their interactions, such as attraction, attention and action. These data represent a precious value for the museum curators, and they are one of the parameters that need to be assessed. These information are collected through manual approaches based on questionnaires or visual observations. This procedure is time consuming and can be affected by the subjective interpretation of the evaluator. From such premises, SeSAME (Senseable Self Adapting Museum Environment) a novel system for collecting and analysing the behaviours of visitors inside a museum environment is presented in this paper. SeSAME is based on a multi-modal deep neural network architecture able to extract anthropometric and appearance features from RGB-D videos acquired in crowded environments. Our approach has been tested on four different temporal modelling methods to aggregate a sequence of image-level features into clip-level features. This paper uses as a benchmark TVPR2, a public dataset of acquired videos with an RGB-D camera in a top-view configuration, in the presence of persistent and temporarily heavy occlusion. Moreover, a dataset specifically collected for this work has been acquired in a real museum environment, which is Palazzo Buonaccorsi, an important historical building in Macerata, in Marche Region in the center of Italy. During the experimental phase, the evaluation metrics show the effectiveness and the suitability of the proposed method
Measuring and Assessing Augmented Reality Potential for Educational Purposes: SmartMarca Project
No full textAugmented and Virtual reality proved to be valuable solutions to convey contents in a more appealing and interactive way. Their use is nearly embracing several domains like medicine, geospatial applications, industry, tourism and so on. But among the others, the one that might benefit the most by their use is the Cultural Heritage. In fact, given the improvement of mobile and smart devices in terms of both usability and computational power, contents can be easily conveyed with a realism level never reached in the past. However, despite the tremendous number of researches related with the presentation of new fascinating applications of ancient goods and artifacts augmentation, few papers are focusing on the real effect that these tools have on learning. In fact, whether a disposable use of such tools seems to have a great benefit in terms of visual impact for the users, the same cannot be said about the long-term effect they have on the users, especially for education purposes. Within the framework of SmartMarca project, that will be briefly explained in these pages, this paper focuses on assessing the potential of AR applications specifically designed for Cultural Heritage. More specifically, tests have been conducted on an Augmented Reality experience upon different paintings. For evaluating the benefits of such technology in terms of learning, we have performed our experiment on classrooms of teenagers. By testing different learning approaches, we were able to evaluate and assess the effectiveness of using these technologies for the education process. The paper will even argue on the necessity of developing new tools to enable users to become producers of contents of AR/VR experiences, since up to now there no exists a platform specifically designed for an agile creation, even for not skilled programmers
Human trajectory prediction and generation using LSTM models and GANs
No full textHuman trajectory prediction is an important topic in several application domains, ranging from self-driving cars to environment design and planning, from socially-aware robots to intelligent tracking systems. This complex subject comes with different challenges, such as human-space interaction, human-human interaction, multimodality, and generalizability. Currently, these challenges, especially generalizability, have not been completely explored by state-of-the-art works. This work attempts to fill this gap by proposing and defining new methods and metrics to help understand trajectories. In particular, new deep learning models based on Long Short-Term Memory and Generative Adversarial Network architectures are used in both unimodal and multimodal contexts. These approaches are evaluated with new error metrics, which normalize some biases in standard metrics. Tests have been assessed using newly collected datasets characterized by a higher diversity and lower linearity than those used in state-of-the-art works. The results prove that the proposed models and datasets are comparable to and yield better generalizability than state-of-the-art works. Moreover, we also prove that our datasets better represent multimodal scenarios (allowing for multiple possible behaviors) and that human trajectories are moderately influenced by their spatial region and slightly influenced by their date and time
Dissemination in archaeology: a GIS-based StoryMap for Chan Chan
Full text linkPurpose: The purpose of this paper is to demonstrate the importance of exploiting a geographic information system (GIS)-based data management, designed and implemented for an important monumental site. In particular, data collected during the years have been used to create a storytelling experience to disseminate the tangible and intangible heritage of Chan Chan (Peru), the wider site in mud bricks of Latin America. Design/methodology/approach: The paper discusses the steps that have been performed to use the data stored in a GIS, arguing over the importance of sharing the knowledge through web-based tools, and in particular by the implementation of a storytelling. In this context, the data were structured in interoperable forms in order to preserve the universal value of the archaeological site. The exploitation in an all-in-one solution of the archival research, field surveys and planning represents a step forward for let known ancient testimonies to the whole mankind. Findings: The GIS-based inventories represent the backbone for an affordable management of heritage resources. The novelty of the proposed approach lies on the creation of an integrated, accessible and updatable data system sharable on web. Originality/value: The GIS of Chan Chan is an example of documentation of a wide archaeological area (14 km2) with complex and heterogeneous data. The developed web tool makes use of these data which can be queried even by non-expert users. The pipeline of this paper can act as useful guidelines to practitioners and researchers who want to disseminate cultural information
A Method for Determining the Shape Similarity of Complex Three-Dimensional Structures to Aid Decay Restoration and Digitization Error Correction
Full text linkThis paper introduces a new method for determining the shape similarity of complex three-dimensional (3D) mesh structures based on extracting a vector of important vertices, ordered according to a matrix of their most important geometrical and topological features. The correlation of ordered matrix vectors is combined with perceptual definition of salient regions in order to aid detection, distinguishing, measurement and restoration of real degradation and digitization errors. The case study is the digital 3D structure of the Camino Degli Angeli, in the Urbino’s Ducal Palace, acquired by the structure from motion (SfM) technique. In order to obtain an accurate, featured representation of the matching shape, the strong mesh processing computations are performed over the mesh surface while preserving real shape and geometric structure. In addition to perceptually based feature ranking, the new theoretical approach for ranking the evaluation criteria by employing neural networks (NNs) has been proposed to reduce the probability of deleting shape points, subject to optimization. Numerical analysis and simulations in combination with the developed virtual reality (VR) application serve as an assurance to restoration specialists providing visual and feature-based comparison of damaged parts with correct similar examples. The procedure also distinguishes mesh irregularities resulting from the photogrammetry process
Can AI Replace Conventional Markerless Tracking? A Comparative Performance Study for Mobile Augmented Reality Based on Artificial Intelligence
No full textCyber Physical Systems for Industry 4.0: Towards Real Time Virtual Reality in Smart Manufacturing
No full textCyber Physical System (CPS) together with Internet of Things, Big Data, Cloud Computing and Industrial Wireless Networks are the core technologies allowing the introduction of the fourth industrial revolution, Industry 4.0. Along with the advances in new generation information technologies, smart manufacturing is becoming the focus of global manufacturing transformation. Considering the competitive nature of industry, it requires manufacturers to implement new methodologies. Realistic virtual models mirroring the real world are becoming essential to bridge the gap between design and manufacturing. In this paper model conceptualization, representation, and implementation of the digital twin is presented, on the real use case of manufacturing industry and in the cyber physical environment. A novel CPS architecture for real time visualization of complex industrial process is proposed. It essentially considers the Simulation technological pillar of Industry 4.0. The results from a real industrial environment show good performances in terms of real time behaviour, virtual reality and WebGL CPS visualization features, usability and readability
- …
