Smart City Gnosys

Smart city article details

Title	Evaluating Urban Environments For The Integration Of Cutting-Edge Technologies Enhances Smart Cities' Evolution
ID_Doc	24702
Authors	Andreou A.; Mavromoustakis C.X.; Batalla J.M.; Markakis E.; Mastorakis G.; Chatzimisios P.
Year	2023
Published	IEEE International Conference on Communications, 2023-May
DOI	http://dx.doi.org/10.1109/ICC45041.2023.10278752
Abstract	The endeavours to interpret the acquired data are combined with the efforts to strengthen the smart city's multidimensional framework. As the name implies, smart cities are built atop more intelligent data. However, it is a significant challenge because Big Data needs to be evaluated to provide interpretation for a posterior evolution of the current technology. Therefore, using the right building blocks is vital, aligned with clear and convincing guidelines on best practices. To achieve a scale of evaluation, we need standards. The intertwining development drivers need to define how we see and measure the world around us and how this Big Data in the era of IoT informs the decision-making processes. Hence, we are introducing an evaluation model for Big Data obtained from the assessment of Quality of Service (QoS) and Quality of Experience (QoE) delivery in an urban environment. Using the Best-Worst Method (BWM) combined with the orientation of Intuitionistic fuzzy sets. We obtained intuitive preference information based on various criteria. Thus, by prioritizing these end-user predilections and transmitting them into adaptable technological improvements, we achieved a significant step toward sustainable Smart Cities. © 2023 IEEE.
Author Keywords	Best-Worst method; Big Data; intuitionistic fuzzy sets; QoE; QoS; Smart City

Similar Articles

Id	Similarity	Authors	Title	Published
39870	0.895	Andreou A.; Mavromoustakis C.X.; Markakis E.K.; Song H.	On The Integration Of User Preferences By Using A Hybrid Methodology For Multi-Criteria Decision Making	IEEE Access, 11 (2023)
60738	0.884	Zdravković N.; Simjanović D.; Šibalija T.; Vesić N.	Utilizing Fuzzy Ahp With Spherical Numbers To Indicate Ioe Factors For Successful Smart City Development	Lecture Notes in Electrical Engineering, 1226 LNEE (2024)
39935	0.875	Bibri S.E.	On The Sustainability Of Smart And Smarter Cities In The Era Of Big Data: An Interdisciplinary And Transdisciplinary Literature Review	Journal of Big Data, 6, 1 (2019)
35039	0.871	Karimi, Y; Kashani, MH; Akbari, M; Mahdipour, E	Leveraging Big Data In Smart Cities: A Systematic Review	CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 33, 21 (2021)
12015	0.871	Singh Rathore S.P.; Vishnubhai Dalabhai C.; Babubhai Patel C.K.; Sharma R.; Mathur A.; Yadav A.	Big Data Analytics For Smart Cities	Proceedings - IEEE 2024 1st International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024 (2024)
39934	0.869	Bibri S.E.	On The Sustainability And Unsustainability Of Smart And Smarter Urbanism And Related Big Data Technology, Analytics, And Application	Advances in Science, Technology and Innovation (2019)
49624	0.867	Wu, SM; Chen, TC; Wu, YJ; Lytras, M	Smart Cities In Taiwan: A Perspective On Big Data Applications	SUSTAINABILITY, 10, 1 (2018)
50314	0.865	Soni P.	Smart City Innovations And Iot As A Frontier Of Ai At The Edge Of Intelligence	Edge of Intelligence: Exploring the Frontiers of AI at the Edge (2025)
4297	0.865	Kasubi J.W.; D.h M.; Demewez G.D.	A Review On The Internet Of Things And Big Data Analytics Based On Smart Cities	Proceedings - International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021 (2021)
55978	0.863	Bibri S.E.	The Iot And Big Data Analytics For Smart Sustainable Cities: Enabling Technologies And Practical Applications	Advances in Science, Technology and Innovation (2020)