Ferreira Joao Carlos

• Elvas, Luìs B.; Nunes, Miguel; Ferreira, Joao C.; Francisco, Bruno & Afonso, Jose A. (2023). Georeferenced analysis of urban nightlife and noise based on mobile phone data. Applied Sciences. ISSN 2076-3417. 14(1). doi: 10.3390/app14010362. Vis sammendrag

  Urban environments are characterized by a complex soundscape that varies across different periods and geographical zones. This paper presents a novel approach for analyzing nocturnal urban noise patterns and identifying distinct zones using mobile phone data. Traditional noise-monitoring methods often require specialized equipment and are limited in scope. Our methodology involves gathering audio recordings from city sensors and localization data from mobile phones placed in urban areas over extended periods with a focus on nighttime, when noise profiles shift significantly. By leveraging machine learning techniques, the developed system processes the audio data to extract noise features indicative of different sound sources and intensities. These features are correlated with geographic location data to create comprehensive city noise maps during nighttime hours. Furthermore, this work employs clustering algorithms to identify distinct noise zones within the urban landscape, characterized by their unique noise signatures, reflecting the mix of anthropogenic and environmental noise sources. Our results demonstrate the effectiveness of using mobile phone data for nocturnal noise analysis and zone identification. The derived noise maps and zones identification provide insights into noise pollution patterns and offer valuable information for policymakers, urban planners, and public health officials to make informed decisions about noise mitigation efforts and urban development.

• Ferreira, Joao C.; Francisco, Bruno; Elvas, Luìs B.; Nunes, Miguel & Afonso, Jose A. (2023). Predicting People’s Concentration and Movements in a Smart City. Electronics. ISSN 2079-9292. 13(1). doi: 10.3390/electronics13010096. Vis sammendrag

  first_pagesettingsOrder Article Reprints Open AccessArticle Predicting People’s Concentration and Movements in a Smart City by Joao C. Ferreira 1,2,3ORCID,Bruno Francisco 1,Luis Elvas 1,2,3,Miguel Nunes 1 andJose A. Afonso 4,*ORCID 1 Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR, 1649-026 Lisboa, Portugal 2 Inov Inesc Inovação—Instituto de Novas Tecnologias, 1000-029 Lisbon, Portugal 3 Department of Logistics, Molde University College, 6410 Molde, Norway 4 CMEMS-UMinho/LABBELS—Associate Laboratory, University of Minho, 4800-058 Guimarães, Portugal * Author to whom correspondence should be addressed. Electronics 2024, 13(1), 96; https://doi.org/10.3390/electronics13010096 Submission received: 25 October 2023 / Revised: 18 December 2023 / Accepted: 21 December 2023 / Published: 25 December 2023 (This article belongs to the Special Issue AI Technologies and Smart City) Downloadkeyboard_arrow_down Browse Figures Versions Notes Abstract With the rapid growth of urbanization and the proliferation of mobile phone usage, smart city initiatives have gained momentum in leveraging data-driven insights to enhance urban planning and resource allocation. This paper proposes a novel approach for predicting people’s concentration and movements within a smart city environment using mobile phone data provided by telecommunication operators. By harnessing the vast amount of anonymized and aggregated mobile phone data, we present a predictive framework that offers valuable insights into urban dynamics. The methodology involves collecting and processing location-based data obtained from telecommunication operators. Using machine learning techniques, including clustering and spatiotemporal analysis, we developed models to identify patterns in people’s movements and concentration across various city regions. Our proposed approach considers factors such as time of day, day of the week, and special events to capture the intricate dynamics of urban activities. The predictive models presented in this paper demonstrate the ability to predict areas of high concentration of people, such as commercial districts during peak hours, as well as the people flow during the time. These insights have significant implications for urban planning, traffic management, and resource allocation. Our approach respects user privacy by working with aggregated and anonymized data, ensuring compliance with privacy regulations and ethical considerations. The proposed models were evaluated using real-world mobile phone data collected from a smart city environment in Lisbon, Portugal. The experimental results demonstrate the accuracy and effectiveness of our approach in predicting people’s movements and concentration. This paper contributes to the growing field of smart city research by providing a data-driven solution for enhancing urban planning and resource allocation strategies. As cities continue to evolve, leveraging mobile phone data from telecommunication operators can lead to more efficient and sustainable urban environments.

• Tokkozhina, Ulpan; Martins, Ana Lucia & Ferreira, Joao C. (2023). Blockchain-powered fish industry : trust perceptions of final consumers on traceable information availability. I Martins, Ana Lucia; Ferreira, Joao C.; Kocian, Alexander; Tokkozhina, Ulpan; Helgheim, Berit & Bråthen, Svein (Red.), Intelligent Transport Systems : 7th EAI International Conference, INTSYS 2023, Molde, Norway, September 6-7, 2023, Proceedings. Springer. ISSN 978-3-031-49379-9. s. 151–162. doi: https:/doi.org/10.1007/978-3-031-49379-9_8. Vis sammendrag

  Blockchain is being actively discussed for business applications to digitalise supply chains. The still nascent level of blockchain adoption creates a difficulty to see the potential value that it may add to products and final consumers. Through a quantitative method, this study explores the impact of the traceability feature of products on the trust in the seller supermarket chain from the perspective of final consumers. Data from 417 questionnaires applied to buyers of fish was used to analyse such relation. Findings reveal the interest of final consumers towards traceable products and a positive relationship between the traceable information availability and the trust towards product.

• Tokkozhina, Ulpan; Martins, Ana Lucia & Ferreira, Joao C. (2023). Blockchain-based solution for charitable supply chains : network proposal architecture for Portuguese tax consignment program. I Martins, Ana Lucia; Ferreira, Joao C.; Kocian, Alexander; Tokkozhina, Ulpan; Helgheim, Berit & Bråthen, Svein (Red.), Intelligent Transport Systems : 7th EAI International Conference, INTSYS 2023, Molde, Norway, September 6-7, 2023, Proceedings. Springer. ISSN 978-3-031-49379-9. s. 92–104. doi: https:/doi.org/10.1007/978-3-031-49379-9_5. Vis sammendrag

  This paper presents a blockchain-based solution for enhancing transparency, accountability, and efficiency in charitable supply chains, with a focus on the Portuguese Tax Consignment Program, but adaptively to other tax systems. Charitable organizations often face challenges in managing and tracking donations, leading to potential inefficiencies and distrust among stakeholders. Leveraging blockchain technology, this research proposes a network proposal architecture that enables secure and immutable recording of donation transactions, ensures proper allocation of funds, and fosters transparency in the charitable supply chain ecosystem.

• Elvas, Luìs B.; Nunes, Miguel; Francisco, Bruno; Gonçalves, Frederica; Martins, Ana Lucia & Ferreira, Joao C. (2023). Points of interest in smart cities and visitor behavior. I Martins, Ana Lucia; Ferreira, Joao C.; Kocian, Alexander; Tokkozhina, Ulpan; Helgheim, Berit & Bråthen, Svein (Red.), Intelligent Transport Systems : 7th EAI International Conference, INTSYS 2023, Molde, Norway, September 6-7, 2023, Proceedings. Springer. ISSN 978-3-031-49379-9. s. 69–91. doi: 10.1007/978-3-031-49379-9_4. Vis sammendrag

  Home Intelligent Transport Systems Conference paper Points of Interest in Smart Cities and Visitor Behavior Luís B. Elvas, Miguel Nunes, Bruno Francisco, Frederica Gonçalves, Ana Lucia Martins & Joao Carlos Ferreira Conference paper First Online: 12 December 2023 15 Accesses Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 540) Abstract Smart cities leverage technology and data to enhance the quality of urban life, including the management of points of interest (POIs) and visitor experiences. This paper explores the relationship between POIs and visitor behavior in smart cities, examining the impact of technology-driven solutions on understanding, analyzing, and optimizing visitor experiences. It highlights the importance of data-driven approaches in identifying and managing POIs, enhancing visitor satisfaction, and driving economic growth. The paper reviews existing literature, discusses key concepts, and presents case studies to illustrate the role of POIs in smart cities and their influence on visitor behavior. Our major contribution is a data driven approach to extract useful information from real data to municipality decisions and understand the problem. It concludes with recommendations for future research and practical implications for city planners, policymakers, and tourism authorities.

• Pereira, José; Antunes, Nuno; Rosa, Joana; Ferreira, Joao C.; Mogo, Sandra & Pereira, Manuel (2023). Intelligent Clinical Decision Support System for Managing COPD Patients. Journal of Personalized Medicine. 13(9), s. 1–34. doi: 10.3390/jpm13091359. Vis sammendrag

  Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. Health remote monitoring systems (HRMSs) play a crucial role in managing COPD patients by identifying anomalies in their biometric signs and alerting healthcare professionals. By analyzing the relationships between biometric signs and environmental factors, it is possible to develop artificial intelligence models that are capable of inferring patients’ future health deterioration risks. In this research work, we review recent works in this area and develop an intelligent clinical decision support system (CIDSS) that is capable of providing early information concerning patient health evolution and risk analysis in order to support the treatment of COPD patients. The present work’s CIDSS is composed of two main modules: the vital signs prediction module and the early warning score calculation module, which generate the patient health information and deterioration risks, respectively. Additionally, the CIDSS generates alerts whenever a biometric sign measurement falls outside the allowed range for a patient or in case a basal value changes significantly. Finally, the system was implemented and assessed in a real case and validated in clinical terms through an evaluation survey answered by healthcare professionals involved in the project. In conclusion, the CIDSS proves to be a useful and valuable tool for medical and healthcare professionals, enabling proactive intervention and facilitating adjustments to the medical treatment of patients. Keywords: chronic obstructive pulmonary disease (COPD), decision support system (DSS), intelligent clinical decision support system (CIDSS), health remote monitoring system (HRMS), triage validation module (TVM)

• Tokkozhina, Ulpan; Mataloto, Bruno Miguel; Martins, Ana Lucia & Ferreira, Joao C. (2023). Decentralizing online food delivery services : a blockchain and IoT model for smart cities. Mobile Networks and Applications. ISSN 1383-469X. doi: 10.1007/s11036-023-02119-5. Vis sammendrag

  With the worldwide pandemic outbreak, the style of restaurant food consumption underwent a major shift towards online delivery services. This poses an urgent need in trust between main stakeholders of the process: requiring restaurants to correspond to the quality declared, providing high quality and safe to consume meals, and obliging delivery entities to deliver food carefully, scrupulously following the delivery conditions. In this research, we explore a novelty approach that combines IoT, Blockchain technology, and city LoRa network to create a new trusted, decentralized approach for food distribution process in the context of a Smart City. This approach allows controlling the food delivery process using sensors data to control live location, temperature, vibrations, and shakings during the transportation process. We also suggest a fresh perspective on a rating system of delivery entities, where reputation points will be provided both from the side of the restaurant and the final consumer. This will create more trust towards the delivery entity since information will be tamper-proof and immutable due to the nature of Blockchain. This novel system proposal allows rethinking the online food delivery process in the context of Smart City, using the city’s LoRa LPWAN radio frequency technology and Blockchain decentralized solution.

• Tokkozhina, Ulpan; Martins, Ana Lucia & Ferreira, Joao C. (2023). Multi-tier supply chain behavior with blockchain technology : evidence from a frozen fish supply chain. Operations Management Research. ISSN 1936-9735. 16(3), s. 1562–1576. doi: 10.1007/s12063-023-00377-w. Vis sammendrag

  Relationships in multi-tier supply chains (MTSCs) are complex and require constant information sharing. For MTSCs involved in perishable product distribution, blockchain technology (BCT) is one of the most promising technologies that can ensure products’ traceability and safety. This study examines a Portuguese MTSC for frozen fish products piloting BCT adoption for its supply chain (SC) practices. The goal is therefore to explore the consequences of information availability inherent for BCT adoption pilots in the SC context. This study follows a mixed-method approach, with qualitative and quantitative data collection techniques. Three semi-structured interviews with players from a single frozen fish SC, including supplier, transporter, and retailer were conducted. MAXQDA Analytics Pro 2022 software was used for further coding and data analysis. An online survey among retail chain consumers was conducted resulting in 112 responses. Regression analysis and Pearson correlation test were further performed via IBM SPSS Statistics software. Data collection for both parts took place between December 2021 and July 2022. This study explores four layers in the SC– including supplier, transporter, retailer and final consumer. Findings revealed a current lack of extensive and detailed information from upper tiers regarding products’ characteristics. Despite being hyped as a “trust-enabling” technology, BCT was found not to eliminate the need for trustful relationships between players prior to adoption, as information input requires human intervention. Even in those cases when the traceability option is not of major interest to final consumers, findings revealed a higher probability of purchasing fish products that have traceable information available.

• Pires, Ana Rita; Ferreira, Joao C. & Klakegg, Øystein (2023). The future in fishfarms : an ocean of technologies to explore. I Abraham, Ajith; Bajaj, Anu; Gandhi, Niketa; Madureira, Ana Maria & Kahraman, Cengiz (Red.), Innovations in Bio-Inspired Computing and Applications : Proceedings of the 13th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2022) Held During December 15-17, 2022. Springer. ISSN 978-3-031-27498-5. s. 318–326. doi: 10.1007/978-3-031-27499-2_30. Vis sammendrag

  We present the potential application of Machine Learning (ML) to fish farm in a similar approach used in agriculture to control crop growing and predict diseases. The agriculture concept of Precision Agriculture is now applied to fish farm by applying control-engineering principles to fish production; Precision Fish Farming (PFF) aims to improve the farmer's ability to monitor, control, and document biological processes. PFF can help the industry because it takes into consideration the boundary conditions and potentials that are unique to farming operations in the aquatic environment. The proposed solution improves commercial aquaculture and makes it possible to transition to knowledge-based production regime as opposed to experience-based. We apply a data mining approach to identify and evaluate the impact on the growth and mortality of fish in hatcheries. The use of ML techniques, combined with regulation, can increase the productivity and welfare of aquaculture living organisms. Keywords: machine learning, precision fish farming, data analytics, IoT, water quality

• Ferreira, Joao C.; Martins, Ana Lucia; Tokkozhina, Ulpan & Helgheim, Berit (2022). Fish control process and traceability for value creation using blockchain technology. I Abraham, Ajith; Madureira, Ana Maria; Kaklauskas, Arturas; Gandhi, Niketa; Bajaj, Anu; Muda, Azah Kamilah; Kriksciuniene, Dalia & Ferreira, Joao C. (Red.), Innovations in Bio-Inspired Computing and Applications : Proceedings of the 12th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2021) Held During December 16–18, 2021. Springer. ISSN 978-3-030-96298-2. s. 761–773. doi: 10.1007/978-3-030-96299-9_72. Vis sammendrag

  Currently, the globe and, more specifically, corporate processes are evolving towards digitization and the elimination of time-consuming procedures. As origin knowledge and safety assurance of products became more important in establishing end-consumer confidence, traceability solutions are acute. A Blockchain (BC) is one of the most exciting disruptive technologies emerging today. The purpose of this study is to analyze the possibility of using BC to allow end-to-end supply chain (SC) management traceability and to provide a proposition of a BC application for fish tracking and control in SC contexts. The proposition demonstrates that BC provides the use of a single information system by several players across SC, resulting in more secure and efficient data sharing. A future understanding of the significance of BC technology usage as a traceability supplier and a detailed testing of a proposed architecture is identified as a diretion for future study. We, therefore, study current applications in supply chain management, with a big emphasis on the fish control process. Keywords: blockchain, traceability, supply chain, IoT, fish

• Tokkozhina, Ulpan; Martins, Ana Lúcia & Ferreira, Joao C. (2022). Use of blockchain technology to manage the supply chains : comparison of perspectives between technology providers and early industry adopters. Journal of Theoretical and Applied Electronic Commerce Research. ISSN 0718-1876. 17(4), s. 1616–1632. doi: 10.3390/jtaer17040082. Vis sammendrag

  Following the interest in blockchain technology (BCT) business solutions and the nascent stage of technology in supply chain (SC) practices, this research compares views from business practitioners who are experienced in real cases of BCT adoption with the views of technology consultants proficient in the complexities of BCT to analyze the benefits and challenges BCT holds for SCs. Based on the comparison of the two sides, the joint views that both adopters and technology consultants share is the ability that BCT holds to speed up processes across SCs through decentralized data access, thus decreasing human errors and reducing paperwork. However, technology consultants perceive the need to increase BCT awareness levels of businesses, to prevent BCT implementation just for reasons such as ‘recordkeeping’ and to reduce misconceptions in areas such as cryptocurrency applications. The findings also revealed that technology consultants insist on the careful evaluation and definition of records to be kept on BCT platforms prior to the adoption process, in order to avoid unnecessary data input. Currently, according to early industry adopters’ cases, most business attempts of BCT adoption use private networks, so technology consultants promote business entities on developing plans towards open-access public networks. Keywords: supply chain management, blockchain, early industry adopters, technology consultants, semi-structured interviews

• Tokkozhina, Ulpan; Martins, Ana Lucia & Ferreira, Joao C. (2022). Uncovering dimensions of the impact of blockchain technology in supply chain management. Operations Management Research. ISSN 1936-9735. 16(1), s. 99–125. doi: 10.1007/s12063-022-00273-9. Vis sammendrag

  Supply chains around the globe are faced with difficulties and disruptions due to the worldwide pandemic situation and digital solutions are needed. There is significant research interest in the implementation of blockchain technology (BCT) for supply chain management (SCM). A challenge that remains is analyzing the interactions of BCT in different areas of SCM. This study aims to identify the influential dimensions of the impact of BCT adoption in SCM and to discuss the synergetic and counter-synergetic effects between these dimensions. Advantages, disadvantages, and constraints of adopting BCT in the SCM context are explored through a systematic literature review, which provides the foundation for identifying the dimensions of impact. The interactions between these dimensions are conceptually discussed. This study introduces three dimensions of the impact of implementing BCT in SCM: ‘operations and processes’, ‘supply chain relationships’, and ‘innovation and data access’. These dimensions are interrelated and have overlapping areas within them, which leads to synergetic and counter-synergetic effects. The overlaps and synergies of the three dimensions of impact are illustrated, and the virtuous and vicious cycles of BCT adoption in SCM cases are highlighted. This study assists scholars and practitioners by clarifying the synergetic relationships within the dimensions of the impact of BCT in SCM and by providing considerations to prevent undesirable effects and expand desired ones.

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• Martins, Ana Lucia; Ferreira, Joao C.; Kocian, Alexander; Tokkozhina, Ulpan; Helgheim, Berit & Bråthen, Svein (2023). Intelligent Transport Systems : 7th EAI International Conference, INTSYS 2023, Molde, Norway, September 6-7, 2023, Proceedings. Springer. ISBN 978-3-031-49379-9. 259 s. Vis sammendrag

  This book constitutes the refereed proceedings of the 7th International Conference on Intelligent Transport Systems, INTSYS 2023, held in Molde, Norway, during September 6-7, 2023. With the globalization of trade and transportation and the consequent multi-modal solutions used, additional challenges are faced by organizations and countries. Intelligent Transport Systems make transport safer, more efficient, and more sustainable by applying information and communication technologies to all transportation modes. The 14 full papers included in this book were carefully reviewed and selected from 39 submissions and are organized in three thematic sessions on transportation; smart cities and blockchain; networks.

• Abraham, Ajith; Madureira, Ana Maria; Kaklauskas, Arturas; Gandhi, Niketa; Bajaj, Anu & Muda, Azah Kamilah [Vis alle 8 forfattere av denne artikkelen] (2022). Innovations in Bio-Inspired Computing and Applications : Proceedings of the 12th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2021) Held During December 16–18, 2021. Springer. ISBN 978-3-030-96298-2. 192 s.

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