Orcid Publications

José Machado

José Machado

Jose Machado is Full Professor of the Department of Informatics, School of Engineering, University of Minho. He is at the…

ORCID iD 0000-0003-4121-6169
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2025

La computación espacial como motor de innovación en marketing y comercio

Spatial computing emerges as a technological convergence that significantly transforms both marketing and commerce. This study examines this phenomenon through a systematic theoretical review complemented by the analysis of five representative cases, covering diverse sectors such as retail, cosmetics, e-commerce, construction, and agri-food. Through technologies like augmented reality, mixed reality, and advanced geolocation systems, organizations develop immersive, personalized, and contextualized experiences in real environments. The results identify consistent emerging trends: real-time contextual personalization, visualization as a trust-generating mechanism, and the extension of storytelling into physical spaces. Simultaneously, technical, ethical, and evaluative challenges are evident, requiring rethinking of traditional paradigms. The study concludes that spatial computing not only provides competitive advantages but fundamentally redefines the relationship between consumer and brand. This research offers practical implications for innovation management and proposes future research directions aimed at evaluating the experiential and symbolic impact of these technologies in various commercial contexts.

Redmarka. Revista de Marketing Aplicado
José Luís Reis, Carlos Alves, Samuel Anjos, José Machado
2024

Revolutionising the Quality of Life: The Role of Real-Time Sensing in Smart Cities

To further evolve urban quality of life, this paper explores the potential of crowdsensing and crowdsourcing in the context of smart cities. To aid urban planners and residents in understanding the nuances of day-to-day urban dynamics, we actively pursue the improvement of data visualisation tools that can adapt to changing conditions. An architecture was created and implemented that ensures secure and easy connectivity between various sources, such as a network of Internet of Things (IoT) devices, to merge with crowdsensing data and use them efficiently. In addition, we expanded the scope of our study to include the development of mobile and online applications, emphasizing the integration of autonomous and geo-surveillance. The main findings highlight the importance of sensor data in urban knowledge. Their incorporation via Tepresentational State Transfer (REST) Application Programming Interface (APIs) improves data access and informed decision-making, and dynamic data visualisation provides better insights. The geofencing of the application encourages community participation in urban planning and resource allocation, supporting sustainable urban innovation.

Rui Miranda, Carlos Alves, Regina Sousa, António Chaves, Larissa Montenegro, Hugo Peixoto, Dalila Durães, Ricardo Machado, António Abelha, Paulo Novais, José Machado

Behaviour of Machine Learning algorithms in the classification of energy consumption in school buildings

Abstract The significance of energy efficiency in the development of smart cities cannot be overstated. It is essential to have a clear understanding of the current energy consumption (EC) patterns in both public and private buildings. One way to achieve this is by employing machine learning classification algorithms, which offer a broader perspective on the factors influencing EC. These algorithms can be applied to real data from databases, making them valuable tools for smart city applications. In this paper, our focus is specifically on the EC of public schools in a Portuguese city, as this plays a crucial role in designing a Smart City. By utilizing a comprehensive dataset on school EC, we thoroughly evaluate multiple ML algorithms. The objective is to identify the most effective algorithm for classifying average EC patterns. The outcomes of this study hold significant value for school administrators and facility managers. By leveraging the predictions generated from the selected algorithm, they can optimize energy usage and, consequently, reduce costs. The use of a comprehensive dataset ensures the reliability and accuracy of our evaluations of various ML algorithms for EC classification.

Logic Journal of the IGPLSJRQ20.264JCRQ20.800SCIE
Larissa Montenegro, Carlos Alves, Ricardo Machado, Paulo Novais, António Chaves, Dalila Durães, José Machado

Future Perspectives in Healthcare: An Analysis of Augmented Reality and Spatial Computing in Hospital Environments

This article investigates the applicability of Augmented Reality (AR) and Spatial Computing in hospital environments, exploring how these technologies can enhance interaction between patients and healthcare professionals as well as the efficiency of medical procedures. Through a systematic literature review using the PRISMA methodology, relevant articles highlighting the potential of these technologies in the hospital setting were selected and analysed. The results suggest a growing adoption of AR and Spatial Computing, driven by the advancement of 5G technology, with the potential to improve diagnostic accuracy, the effectiveness of surgical procedures, and the educational experience of healthcare professionals. The study concludes that the integration of these emerging technologies promises to transform hospital environments, emphasising the need to overcome technical, ethical, and privacy challenges to maximise their positive impact on health.

Procedia Computer Science
Carlos Alves, José Luís Reis, José Paulo Marques Dos Santos, Luís Mendes Gomes, José Machado
2023

An Overview of Omnichannel Interaction in Health Care Services

The adoption of omnichannel interaction services in health care can bring significant benefits to both health care institutions and their patients. The ongoing health pandemic caused by coronavirus disease has further emphasized the need for health care providers to implement an omnichannel strategy to provide seamless personalized experiences to their patients through multiple access channels. This study aimed to examine the current state of research on omnichannel interaction services in health care with a focus on the benefits, challenges, and issues that health care institutions may encounter when adopting this strategy. A systematic literature review was conducted to synthesize the current state of research and provide a comprehensive overview of the field. The results of the review were used to perform a strengths, weaknesses, opportunities, and threats analysis of omnichannel services in health care and identify 5 key criteria that health care institutions should consider when implementing an omnichannel strategy. This study contributes to the field by offering an updated and comprehensive understanding of omnichannel interaction services in health care and provides valuable insights for health care providers considering this strategy. The ultimate goal of an omnichannel strategy in health care is to improve patient engagement, increase access to care, and reduce costs while improving communication and collaboration among health care providers. The successful implementation of this strategy requires a well-defined plan, robust technology, infrastructure, data analytics, capabilities, trained professionals, and a basic understanding of the communication channels among patients. The adoption of an omnichannel strategy in health care can lead to new business growth and increased patient engagement, but health care institutions must be properly aligned and patients must be prepared for its implementation.

Mayo Clinic Proceedings Digital HealthSJRQ20.525
Ailton Moreira, Carlos Alves, José Machado, Manuel Filipe Santos

Keywords

2021

Software tools for conducting real-time information processing and visualization in industry: An up-to-date review

The processing of information in real-time (through the processing of complex events) has become an essential task for the optimal functioning of manufacturing plants. Only in this way can artificial intelligence, data extraction, and even business intelligence techniques be applied, and the data produced daily be used in a beneficent way, enhancing automation processes and improving service delivery. Therefore, professionals and researchers need a wide range of tools to extract, transform, and load data in real-time efficiently. Additionally, the same tool supports or at least facilitates the visualization of this data intuitively and interactively. The review presented in this document aims to provide an up-to-date review of the various tools available to perform these tasks. Of the selected tools, a brief description of how they work, as well as the advantages and disadvantages of their use, will be presented. Furthermore, a critical analysis of overall operation and performance will be presented. Finally, a hybrid architecture that aims to synergize all tools and technologies is presented and discussed.

Applied Sciences SwitzerlandSJRQ20.521
Regina Sousa, Rui Miranda, Ailton Moreira, Carlos Alves, Nicolas Lori, José Machado
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