Journal of Information Systems Engineering and Management

A Comprehensive Study on User-Centric Smart Life Solutions: Integrating Mobile Integrated Technology and Big Data Analytics for Digitalized Smart City Environments
Chengsi Li 1, Younghwan Pan 2 *
More Detail
1 Ph.D candidate, Department of Smart Experience Design, Kookmin University, Seoul, Republic of Korea
2 Doctor, Professor, Department of Smart Experience Design, Kookmin University, Seoul, Republic of Korea
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2024 - Volume 9 Issue 1, Article No: 24684
https://doi.org/10.55267/iadt.07.14077

Published Online: 25 Jan 2024

Views: 624 | Downloads: 513

How to cite this article
APA 6th edition
In-text citation: (Li & Pan, 2024)
Reference: Li, C., & Pan, Y. (2024). A Comprehensive Study on User-Centric Smart Life Solutions: Integrating Mobile Integrated Technology and Big Data Analytics for Digitalized Smart City Environments. Journal of Information Systems Engineering and Management, 9(1), 24684. https://doi.org/10.55267/iadt.07.14077
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Li C, Pan Y. A Comprehensive Study on User-Centric Smart Life Solutions: Integrating Mobile Integrated Technology and Big Data Analytics for Digitalized Smart City Environments. J INFORM SYSTEMS ENG. 2024;9(1):24684. https://doi.org/10.55267/iadt.07.14077
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Li C, Pan Y. A Comprehensive Study on User-Centric Smart Life Solutions: Integrating Mobile Integrated Technology and Big Data Analytics for Digitalized Smart City Environments. J INFORM SYSTEMS ENG. 2024;9(1), 24684. https://doi.org/10.55267/iadt.07.14077
Chicago
In-text citation: (Li and Pan, 2024)
Reference: Li, Chengsi, and Younghwan Pan. "A Comprehensive Study on User-Centric Smart Life Solutions: Integrating Mobile Integrated Technology and Big Data Analytics for Digitalized Smart City Environments". Journal of Information Systems Engineering and Management 2024 9 no. 1 (2024): 24684. https://doi.org/10.55267/iadt.07.14077
Harvard
In-text citation: (Li and Pan, 2024)
Reference: Li, C., and Pan, Y. (2024). A Comprehensive Study on User-Centric Smart Life Solutions: Integrating Mobile Integrated Technology and Big Data Analytics for Digitalized Smart City Environments. Journal of Information Systems Engineering and Management, 9(1), 24684. https://doi.org/10.55267/iadt.07.14077
MLA
In-text citation: (Li and Pan, 2024)
Reference: Li, Chengsi et al. "A Comprehensive Study on User-Centric Smart Life Solutions: Integrating Mobile Integrated Technology and Big Data Analytics for Digitalized Smart City Environments". Journal of Information Systems Engineering and Management, vol. 9, no. 1, 2024, 24684. https://doi.org/10.55267/iadt.07.14077
ABSTRACT
Digitalized smart cities employ user-centric smart living solutions to study how big data analytics and mobile integrated technology (MIT) affect user satisfaction, technology adoption, and quality of life. To show how smart city residents may benefit from this technology. The quantitative technique used surveys, feedback, and sentiment analysis. These methodologies revealed MIT and big data analytics' influence. Research: smart city services should be user-centered. Research suggests big data analytics enhance urban living. With big data, smart cities manage resources, transportation, sustainability, and more. Furthermore, big data analytics-enabled data-driven decision-making continuously raises user satisfaction and rates of technology adoption. In tackling urban issues such as healthcare accessibility and traffic congestion, MIT solutions prove to be effective tools that also foster economic growth in smart cities. The financial gains underscore MIT's capacity to promote prosperity in digitally advanced smart city settings. Moreover, the study advances user-centered design theories, technology adoption, and urban planning. It supports accepted theories and emphasizes the importance of user participation in design, technology acceptance, and the financial benefits of smart city technology. The study's results provide empirical support for the claim that combining big data analytics with MIT greatly enhances user enjoyment, adoption of new technologies, and the general quality of life in digitalized smart cities. Urban planners, legislators, and technology developers can benefit greatly from the theoretical and practical implications presented, encouraging the creation of user-centric smart life solutions in the rapidly changing field of smart cities.
KEYWORDS
REFERENCES
  • Agnihotri, P., Luthra, M., & Peters, S. (2019). Urbanpulse: Adaptable middleware to offer city and user centric smart city solution. In Proceedings of the 20th International Middleware Conference Demos and Posters (pp. 29-30). New York, NY, United States: Association for Computing Machinery.
  • Alhalabi, W., Lytras, M., & Aljohani, N. (2021). Crowdsourcing research for social insights into smart cities applications and services. Sustainability (Switzerland), 13(14), 7531.
  • Allen, B., Tamindael, L. E., Bickerton, S. H., & Cho, W. (2020). Does citizen coproduction lead to better urban services in smart cities projects? An empirical study on e-participation in a mobile big data platform. Government Information Quarterly, 37(1), 101412.
  • Andrade, R. O., Yoo, S. G., Tello-Oquendo, L., & Ortiz-Garcés, I. (2020). A comprehensive study of the IoT cybersecurity in smart cities. IEEE Access, 8, 228922-228941.
  • Angelidou, M., Politis, C., Panori, A., Barkratsas, T., & Fellnhofer, K. (2022). Emerging smart city, transport and energy trends in urban settings: Results of a pan-European foresight exercise with 120 experts. Technological Forecasting and Social Change, 183, 121915.
  • Daoudagh, S., Marchetti, E., Savarino, V., Bernabe, J. B., García-Rodríguez, J., Moreno, R. T., ... Skarmeta, A. F. (2021). Data protection by design in the context of smart cities: A consent and access control proposal. Sensors, 21(21), 1-21.
  • Drahansky, M., Paridah, M., Moradbak, A., Mohamed, A., Owolabi, F. A., & Asniza, M. (2016). We are IntechOpen, the world’s leading publisher of Open Access books Built by scientists, for scientists TOP 1%. Intech, 1(tourism), 13.
  • Esmaeilpoorarabi, N., & Yigitcanlar, T. (2023). User-Centric Innovation District Planning: Lessons from Brisbane’s Leading Innovation Districts. Buildings, 13(4), 1-21.
  • Ferreira, M. S., Antão, J., Pereira, R., Bianchi, I. S., Tovma, N., & Shurenov, N. (2023). Improving real estate CRM user experience and satisfaction: A user-centered design approach. Journal of Open Innovation: Technology, Market, and Complexity, 9(2), 100076.
  • Gomez, C., Chessa, S., Fleury, A., Roussos, G., & Preuveneers, D. (2019). Internet of Things for enabling smart environments: A technology-centric perspective. Journal of Ambient Intelligence and Smart Environments, 11(1), 23-43.
  • Habbal, A., Goudar, S. I., & Hassan, S. (2019). A Context-aware Radio Access Technology selection mechanism in 5G mobile network for smart city applications. Journal of Network and Computer Applications, 135, 97-107.
  • Kaluarachchi, Y. (2022). Implementing Data-Driven Smart City Applications for Future Cities. Smart Cities, 5(2), 455-474.
  • Kamruzzaman, M. M., Alanazi, S., Alruwaili, M., Alshammari, N., Elaiwat, S., Abu-Zanona, M., ... Ahmed Alanazi, B. (2023). AI- and IoT-Assisted Sustainable Education Systems during Pandemics, such as COVID-19, for Smart Cities. Sustainability (Switzerland), 15(10), 1-17.
  • Kasznar, A. P. P., Hammad, A. W., Najjar, M., Linhares Qualharini, E., Figueiredo, K., Soares, C. A. P., & Haddad, A. N. (2021). Multiple dimensions of smart cities’ infrastructure: A review. Buildings, 11(2), 73.
  • Kirimtat, A., Krejcar, O., Kertesz, A., & Tasgetiren, M. F. (2020). Future Trends and Current State of Smart City Concepts: A Survey. IEEE Access, 8, 86448-86467.
  • Koban, C., Falaleyeva, M., Spravtseva, M., Moiseev, R., & Khan, S. (2022). Modeling User-Centric Threats in Smart City: A Hybrid Threat Modeling Method. In 2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA) (pp. 1-7). IEEE.
  • Kong, X., Liu, X., Jedari, B., Li, M., Wan, L., & Xia, F. (2019). Mobile Crowdsourcing in Smart Cities: Technologies, Applications, and Future Challenges. IEEE Internet of Things Journal, 6(5), 8095-8113.
  • Kornyshova, E., Deneckere, R., Sadouki, K., Gressier-Soudan, E., & Brinkkemper, S. (2022). Smart Life: review of the contemporary smart applications. In International Conference on Research Challenges in Information Science (pp. 302-318). Cham, Switzerland: Springer International Publishing.
  • Kuru, K., & Ansell, D. (2020). TCitySmartF: A comprehensive systematic framework for transforming cities into smart cities. IEEE Access, 8, 18615-18644.
  • Larrinaga, F., Pérez, A., Aldalur, I., Hernández, J. L., Izkara, J. L., & de Viteri, P. S. (2021). A holistic and interoperable approach towards the implementation of services for the digital transformation of smart cities: The case of Vitoria-Gasteiz (Spain). Sensors, 21(23), 1-23.
  • Lavalle, A., Teruel, M. A., Maté, A., & Trujillo, J. (2020). Improving sustainability of smart cities through visualization techniques for big data from IoT devices. Sustainability, 12(14), 5595.
  • Lim, C., Cho, G. H., & Kim, J. (2021). Understanding the linkages of smart-city technologies and applications: Key lessons from a text mining approach and a call for future research. Technological Forecasting and Social Change, 170, 120893.
  • Liu, B., Penaka, S. R., Lu, W., Feng, K., Rebbling, A., & Olofsson, T. (2023). Data-driven quantitative analysis of an integrated open digital ecosystems platform for user-centric energy retrofits: A case study in northern Sweden. Technology in Society, 75, 102347.
  • Lopez-Carreiro, I., Monzon, A., & Lopez, E. (2023). MaaS Implications in the Smart City: A Multi-Stakeholder Approach. Sustainability (Switzerland), 15(14), 10832.
  • Manimuthu, A., Dharshini, V., Zografopoulos, I., Priyan, M. K., & Konstantinou, C. (2021). Contactless Technologies for Smart Cities: Big Data, IoT, and Cloud Infrastructures. SN Computer Science, 2(4), 1-24.
  • Mithun, A. M., & Yafooz, W. M. (2018). Extended user centered design (UCD) process in the aspect of human computer interaction. In 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) (pp. 1-6). IEEE.
  • Mokhtari, G., Anvari-Moghaddam, A., & Zhang, Q. (2019). A New Layered Architecture for Future Big Data-Driven Smart Homes. IEEE Access, 7, 19002-19012.
  • Müller, O., Fay, M., & Vom Brocke, J. (2018). The Effect of Big Data and Analytics on Firm Performance: An Econometric Analysis Considering Industry Characteristics. Journal of Management Information Systems, 35(2), 488-509.
  • Nawaz, A., Chen, J., Su, X., & Zahid Hassan, H. M. (2022). Material based penalty-cost quantification model for construction projects influencing waste management. Frontiers in Environmental Science, 10, 807359.
  • Nawaz, A., & Guribie, F. L. (2022). Impacts of institutional isomorphism on the adoption of social procurement in the Chinese construction industry. Construction Innovation, ahead-of-print. https://doi.org/10.1108/CI-02-2022-0035
  • Nikitas, A., Michalakopoulou, K., Njoya, E. T., & Karampatzakis, D. (2020). Artificial intelligence, transport and the smart city: Definitions and dimensions of a new mobility era. Sustainability (Switzerland), 12(7), 1-19.
  • O’Dwyer, E., Pan, I., Acha, S., & Shah, N. (2019). Smart energy systems for sustainable smart cities: Current developments, trends and future directions. Applied Energy, 237, 581-597.
  • Puthal, D., Yang, L. T., Dustdar, S., Wen, Z., Jun, S., Moorsel, A. V., & Ranjan, R. (2020). A user-centric security solution for Internet of Things and edge convergence. ACM Transactions on Cyber-Physical Systems, 4(3), 1-19.
  • Ribeiro, P., Dias, G., & Pereira, P. (2021). Transport systems and mobility for smart cities. Applied System Innovation, 4(3), 61.
  • Rocha, N. P., Bastardo, R., Pavão, J., Santinha, G., Rodrigues, M., Rodrigues, C., ... Dias, A. (2021). Smart cities’ applications to facilitate the mobility of older adults: A systematic review of the literature. Applied Sciences (Switzerland), 11(14), 6395.
  • Samarakkody, A., Amaratunga, D., & Haigh, R. (2023). Technological Innovations for Enhancing Disaster Resilience in Smart Cities: A Comprehensive Urban Scholar’s Analysis. Sustainability (Switzerland), 15(15), 12036.
  • Sarker, I. H. (2022). Smart City Data Science: Towards data-driven smart cities with open research issues. Internet of Things, 19, 100528.
  • Suvarna, M., Büth, L., Hejny, J., Mennenga, M., Li, J., Ng, Y. T., ... Wang, X. (2020). Smart manufacturing for smart cities—overview, insights, and future directions. Advanced Intelligent Systems, 2(10), 2000043.
  • Talamo, C., Pinto, M. R., Viola, S., & Atta, N. (2019). Smart cities and enabling technologies: influences on urban Facility Management services. In IOP Conference Series: Earth and Environmental Science, 296, 1, 012047. IOP Publishing.
  • Whaiduzzaman, M., Barros, A., Chanda, M., Barman, S., Sultana, T., Rahman, M. S., ... Fidge, C. (2022). A review of emerging technologies for IoT-based smart cities. Sensors, 22(23), 9271.
  • Xu, Y., Ahokangas, P., Turunen, M., Mäntymäki, M., & Heikkilä, J. (2019). Platform-based business models: Insights from an emerging ai-enabled smart building ecosystem. Electronics (Switzerland), 8(10), 1-19.
  • Yang, S., Wang, X., Adeel, U., Zhao, C., Hu, J., Yang, X., & McCann, J. (2022). The Design of User-Centric Mobile Crowdsensing with Cooperative D2D Communications. IEEE Wireless Communications, 29(1), 134-142.
LICENSE
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.