Resumo
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. © 2024 by the authors.
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BibTeX (Download)
@article{Miranda2024,
title = {Revolutionising the Quality of Life: The Role of Real-Time Sensing in Smart Cities},
author = {R. Miranda and C. Alves and R. Sousa and A. Chaves and L. Montenegro and H. Peixoto and D. Durães and R. Machado and A. Abelha and P. Novais and J. Machado},
doi = {10.3390/electronics13030550},
issn = {20799292},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {Electronics (Switzerland)},
volume = {13},
number = {3},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
abstract = {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. © 2024 by the authors.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}