2022
Miranda, R.; Ramos, V.; Ribeiro, E.; Rodrigues, C.; Silva, A.; Durães, D.; Analide, C.; Abelha, A.; Machado, J.
Crowdsensing on Smart Cities: A Systematic Review Proceedings Article
Em: A.C., Rodriguez Ribon J. C. Ferro M. Bicharra Garcia (Ed.): pp. 103-106, Springer Science and Business Media Deutschland GmbH, 2022, ISSN: 03029743, (cited By 2; Conference of 17th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2022 ; Conference Date: 23 November 2022 Through 25 November 2022; Conference Code:289599).
Resumo | Links | BibTeX | Etiquetas: Crowdsensing; Quality of life; Sensing devices; Smart notification; Systematic Review, Internet of things, Smart city
@inproceedings{Miranda2022103,
title = {Crowdsensing on Smart Cities: A Systematic Review},
author = {R. Miranda and V. Ramos and E. Ribeiro and C. Rodrigues and A. Silva and D. Durães and C. Analide and A. Abelha and J. Machado},
editor = {Rodriguez Ribon J. C. Ferro M. Bicharra Garcia A.C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148698891&doi=10.1007%2f978-3-031-22419-5_9&partnerID=40&md5=400c3090fe6a5ffac109f06f5f487953},
doi = {10.1007/978-3-031-22419-5_9},
issn = {03029743},
year = {2022},
date = {2022-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {13788 LNAI},
pages = {103-106},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {With the rise of the internet and the Internet of Things (IoT), the concept of a Smart City began to materialise. Crowdsensing is the process of using portable sensing devices to gather information about people’s surroundings. Furthermore, the research on these domains has pivoted from solely technology concepts to now including how they improve the quality of life of citizens and their utility. This paper presents a systematic review aiming to identify the role and purpose of crowdsensing and the improvement of citizens’ lives in a smart city through this technique. Using the SCOPUS citation and abstract database, six papers were picked out as relevant for discussion in the review. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
note = {cited By 2; Conference of 17th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2022 ; Conference Date: 23 November 2022 Through 25 November 2022; Conference Code:289599},
keywords = {Crowdsensing; Quality of life; Sensing devices; Smart notification; Systematic Review, Internet of things, Smart city},
pubstate = {published},
tppubtype = {inproceedings}
}
With the rise of the internet and the Internet of Things (IoT), the concept of a Smart City began to materialise. Crowdsensing is the process of using portable sensing devices to gather information about people’s surroundings. Furthermore, the research on these domains has pivoted from solely technology concepts to now including how they improve the quality of life of citizens and their utility. This paper presents a systematic review aiming to identify the role and purpose of crowdsensing and the improvement of citizens’ lives in a smart city through this technique. Using the SCOPUS citation and abstract database, six papers were picked out as relevant for discussion in the review. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Witeck, G. R.; Rocha, A. M. A. C.; Silva, G. O.; Silva, A.; Durães, D.; Machado, J.
A Bibliometric Review and Analysis of Traffic Lights Optimization Proceedings Article
Em: O., Misra S. Murgante B. Gervasi (Ed.): pp. 43-54, Springer Science and Business Media Deutschland GmbH, 2022, ISSN: 03029743, (cited By 0; Conference of 22nd International Conference on Computational Science and Its Applications , ICCSA 2022 ; Conference Date: 4 July 2022 Through 7 July 2022; Conference Code:281299).
Resumo | Links | BibTeX | Etiquetas: Bibliometric; Cycle time; Number of vehicles; Optimisations; Research questions; Traffic light; Travel-time; Urban areas; Urban mobility; Urban travels, Particle swarm optimization (PSO); Travel time, Smart city
@inproceedings{Witeck202243,
title = {A Bibliometric Review and Analysis of Traffic Lights Optimization},
author = {G. R. Witeck and A. M. A. C. Rocha and G. O. Silva and A. Silva and D. Durães and J. Machado},
editor = {Misra S. Murgante B. Gervasi O.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135878912&doi=10.1007%2f978-3-031-10562-3_4&partnerID=40&md5=cb31d8b72c37fbf91545fbf66609cc1e},
doi = {10.1007/978-3-031-10562-3_4},
issn = {03029743},
year = {2022},
date = {2022-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {13378 LNCS},
pages = {43-54},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {The significant increase in the number of vehicles in urban areas emerges the challenge of urban mobility. Researchers in this area suggest that most daily delays in urban travel times are caused by intersections, which could be reduced if the traffic lights at these intersections were more efficient. The use of simulation for real intersections can be effective in optimizing the cycle times and improving the traffic light timing to coordinate vehicles passing through intersections. From these themes emerge the research questions: How are the existing approaches (optimization techniques and simulation) to managing traffic lights smartly? What kind of data (offline and online) are used for traffic lights optimization? How beneficial is it to propose an optimization approach to the traffic system? This paper aims to answer these questions, carried out through a bibliometric literature review. In total, 93 articles were analyzed. The main findings revealed that the United States and China are the countries with the most studies published in the last ten years. Moreover, Particle Swarm Optimization is a frequently used approach, and there is a tendency for studies to perform optimization of real cases by real-time data, showing that the praxis of smart cities has resorted to smart traffic lights. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
note = {cited By 0; Conference of 22nd International Conference on Computational Science and Its Applications , ICCSA 2022 ; Conference Date: 4 July 2022 Through 7 July 2022; Conference Code:281299},
keywords = {Bibliometric; Cycle time; Number of vehicles; Optimisations; Research questions; Traffic light; Travel-time; Urban areas; Urban mobility; Urban travels, Particle swarm optimization (PSO); Travel time, Smart city},
pubstate = {published},
tppubtype = {inproceedings}
}
The significant increase in the number of vehicles in urban areas emerges the challenge of urban mobility. Researchers in this area suggest that most daily delays in urban travel times are caused by intersections, which could be reduced if the traffic lights at these intersections were more efficient. The use of simulation for real intersections can be effective in optimizing the cycle times and improving the traffic light timing to coordinate vehicles passing through intersections. From these themes emerge the research questions: How are the existing approaches (optimization techniques and simulation) to managing traffic lights smartly? What kind of data (offline and online) are used for traffic lights optimization? How beneficial is it to propose an optimization approach to the traffic system? This paper aims to answer these questions, carried out through a bibliometric literature review. In total, 93 articles were analyzed. The main findings revealed that the United States and China are the countries with the most studies published in the last ten years. Moreover, Particle Swarm Optimization is a frequently used approach, and there is a tendency for studies to perform optimization of real cases by real-time data, showing that the praxis of smart cities has resorted to smart traffic lights. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.