Pengembangan Sensor-Cloud pada Smart City untuk Menghadirkan Ketersediaan Data Waktu Nyata
DOI:
https://doi.org/10.19166/isd.v7i2.557Keywords:
Smart-City, Sensor-Cloud, Real Time, Integrated System, Sensor-FusionAbstract
A Smart-City development and operation highly depends on more than one group of real-time data sources. Such data integration might be achieved via Sensor- Fusion management. The main resources to this is a reliable virtual sensors cluster that adaptive to environment change such as data feeding disruption. A stability sensor network operation should be put forward as the system will rely on such condition. However, an integrated complex real-time system usually has also some kind of deviation factors as a result of unstable data streaming. In this work, we come up with the idea of Sensor-Cloud which provides real-time data streaming services with virtual environment in mind. A combination of Cloud Computing, Internet of Things and Data Acquisition is the core concept to the proposed approach. To support our proposed approach, a simplified demonstration shall be provided to show the capability of our method.
References
[1] J. Yang, Y. Kwon and D. Kim, "Regional Smart City Development Focus: The South Korean National Strategic Smart City Program", in IEEE Access, vol. 9, pp. 7193-7210, 2021, doi: 10.1109/ACCESS.2020.3047139.
[2] Lea, Rodger James, "Smart Cities:an overview of the technology trends driving smart cities", IEEE, 2017.
[3] S. B. Atitallah, M. Driss, W. Boulila, H. B. Ghézala, "Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions", Computer Science Review, Vol. 38, 2020, ISSN 1574-0137, DOI: 10.1016/j.cosrev.2020.100303.
[4] Pujianto Yugopuspito, Alessandro Luiz Kartika, I Made Murwantara, "Identifikasi Data Drifting pada Aplikasi Internet of Things (IoT)", Jurnal ISD, Vol. 6, No. 2, Juli 2021, ISSN 2528-5114.
[5] O. B. Mora-Sánchez, E. López-Neri, E. J. Cedillo-Elias, E. Aceves-MartÃÂnez and V. M. Larios, "Validation of IoT Infrastructure for the Construction of Smart Cities Solutions on Living Lab Platform", in IEEE Transactions on Engineering Management, vol. 68, no. 3, pp. 899-908, June 2021, doi: 10.1109/TEM.2020.3002250.
[6] Loke, Seng and A. Rakotonirainy, The Automated City: Internet of Things and Ubiquitous Artificial Intelligence, 1 ed., Springer, Cham, Switzerland, 2021, doi: 10.1007/978-3-030-82318-4.
[7] Adeeb A. Kutty, Murat Kucukvar, Galal M. Abdella, Muhammet Enis Bulak, Nuri Cihat Onat, "Sustainability Performance of European Smart Cities: A Novel DEA Approach with Double Frontiers", Sustainable Cities and Society, Volume 81,2022, ISSN 2210-6707, DOI:10.1016/j.scs.2022.103777.
[8] M. Herawati, and A. Djunaedi, "Ketersediaan Data dalam Mendukung Smart City Readiness di Kota Surakarta", Journal of Regional and Rural Development Planning (Jurnal Perencanaan Pembangunan Wilayah Dan Perdesaan), 4(1), 63-73, 2020, https://doi.org/10.29244/jp2wd.2020.4.1.63-73.
[10] T. Hayashi, H. Sakaji, H. Matsushima, et al. “Data Combination for Problem-Solving: A Case of an Open Data Exchange Platform", Rev Socionetwork Strat 15, 521–534 (2021). https://doi.org/10.1007/s12626-021-00083-8 G.
[11] A. Gross, R. Nagi, K. Sambhoos, D. R. Schlegel, S. C. Shapiro and G. Tauer, "Towards hard+soft data fusion: Processing architecture and implementation for the joint fusion and analysis of hard and soft intelligence data," 2012 15th International Conference on Information Fusion, 2012, pp. 955-962. Varshney P.K. (2014) Sensor Fusion. In: Ikeuchi K. (eds) Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-31439-6_301.
[12] E. R. B. Sajonia and L. M. Dagsa, "IoT-Based Smart Street Light Monitoring System with Kalman Filter Estimation," 2021 6th International Conference on Development in Renewable Energy Technology (ICDRET), 2021, pp. 1-5, doi: 10.1109/ICDRET54330.2021.9751792.
[13] I. M. Murwantara, H. Tjahyadi, P. Yugopuspito, A. Aribowo, I. A. Lazarusli, "Towards adaptive sensor-cloud for Internet of Things", Journal TELKOMNIKA (Telecommunication Computing Electronics and Control), Vol. 16 (6), 2771-2781, 2018. DOI: 10.12928/telkomnika.v16i6.11557.
[14] D. Martin, N. Kühl, and G. Satzger, "Virtual Sensors". Bus Inf Syst Eng 63, 315–323 (2021). https://doi.org/10.1007/s12599-021-00689-w
[15] I. M. Murwantara, "An Initial Framework of Dynamic Software Product Line Engineering for Adaptive Service", Robot, 2020, DOI:10.1109/ICOSICA49951.2020.9243199.
[16] J. Gama, I. Žliobaite, A. Bifet, M. Pechenizkiy and A. Bouchachia, "A survey on concept drift adaptation", ACM Comput. Surv. 46, 4, Article 44, 2014, https://doi.org/10.1145/2523813.
[17] Yu, Hang and Liu, Tianyu and Lu, Jie and Zhang, Guangquan, "Automatic Learning to Detect Concept Drift", arxiv, 10.48550/ARXIV.2105.01419
[18] B. Donassolo, A. Legrand, P. Mertikopoulos and I. Fajjari, "Online Reconfiguration of IoT Applications in the Fog: The Information-Coordination Trade-Off", in IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 5, pp. 1156-1172, 1 May 2022, doi: 10.1109/TPDS.2021.3097281.
[2] Lea, Rodger James, "Smart Cities:an overview of the technology trends driving smart cities", IEEE, 2017.
[3] S. B. Atitallah, M. Driss, W. Boulila, H. B. Ghézala, "Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions", Computer Science Review, Vol. 38, 2020, ISSN 1574-0137, DOI: 10.1016/j.cosrev.2020.100303.
[4] Pujianto Yugopuspito, Alessandro Luiz Kartika, I Made Murwantara, "Identifikasi Data Drifting pada Aplikasi Internet of Things (IoT)", Jurnal ISD, Vol. 6, No. 2, Juli 2021, ISSN 2528-5114.
[5] O. B. Mora-Sánchez, E. López-Neri, E. J. Cedillo-Elias, E. Aceves-MartÃÂnez and V. M. Larios, "Validation of IoT Infrastructure for the Construction of Smart Cities Solutions on Living Lab Platform", in IEEE Transactions on Engineering Management, vol. 68, no. 3, pp. 899-908, June 2021, doi: 10.1109/TEM.2020.3002250.
[6] Loke, Seng and A. Rakotonirainy, The Automated City: Internet of Things and Ubiquitous Artificial Intelligence, 1 ed., Springer, Cham, Switzerland, 2021, doi: 10.1007/978-3-030-82318-4.
[7] Adeeb A. Kutty, Murat Kucukvar, Galal M. Abdella, Muhammet Enis Bulak, Nuri Cihat Onat, "Sustainability Performance of European Smart Cities: A Novel DEA Approach with Double Frontiers", Sustainable Cities and Society, Volume 81,2022, ISSN 2210-6707, DOI:10.1016/j.scs.2022.103777.
[8] M. Herawati, and A. Djunaedi, "Ketersediaan Data dalam Mendukung Smart City Readiness di Kota Surakarta", Journal of Regional and Rural Development Planning (Jurnal Perencanaan Pembangunan Wilayah Dan Perdesaan), 4(1), 63-73, 2020, https://doi.org/10.29244/jp2wd.2020.4.1.63-73.
[10] T. Hayashi, H. Sakaji, H. Matsushima, et al. “Data Combination for Problem-Solving: A Case of an Open Data Exchange Platform", Rev Socionetwork Strat 15, 521–534 (2021). https://doi.org/10.1007/s12626-021-00083-8 G.
[11] A. Gross, R. Nagi, K. Sambhoos, D. R. Schlegel, S. C. Shapiro and G. Tauer, "Towards hard+soft data fusion: Processing architecture and implementation for the joint fusion and analysis of hard and soft intelligence data," 2012 15th International Conference on Information Fusion, 2012, pp. 955-962. Varshney P.K. (2014) Sensor Fusion. In: Ikeuchi K. (eds) Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-31439-6_301.
[12] E. R. B. Sajonia and L. M. Dagsa, "IoT-Based Smart Street Light Monitoring System with Kalman Filter Estimation," 2021 6th International Conference on Development in Renewable Energy Technology (ICDRET), 2021, pp. 1-5, doi: 10.1109/ICDRET54330.2021.9751792.
[13] I. M. Murwantara, H. Tjahyadi, P. Yugopuspito, A. Aribowo, I. A. Lazarusli, "Towards adaptive sensor-cloud for Internet of Things", Journal TELKOMNIKA (Telecommunication Computing Electronics and Control), Vol. 16 (6), 2771-2781, 2018. DOI: 10.12928/telkomnika.v16i6.11557.
[14] D. Martin, N. Kühl, and G. Satzger, "Virtual Sensors". Bus Inf Syst Eng 63, 315–323 (2021). https://doi.org/10.1007/s12599-021-00689-w
[15] I. M. Murwantara, "An Initial Framework of Dynamic Software Product Line Engineering for Adaptive Service", Robot, 2020, DOI:10.1109/ICOSICA49951.2020.9243199.
[16] J. Gama, I. Žliobaite, A. Bifet, M. Pechenizkiy and A. Bouchachia, "A survey on concept drift adaptation", ACM Comput. Surv. 46, 4, Article 44, 2014, https://doi.org/10.1145/2523813.
[17] Yu, Hang and Liu, Tianyu and Lu, Jie and Zhang, Guangquan, "Automatic Learning to Detect Concept Drift", arxiv, 10.48550/ARXIV.2105.01419
[18] B. Donassolo, A. Legrand, P. Mertikopoulos and I. Fajjari, "Online Reconfiguration of IoT Applications in the Fog: The Information-Coordination Trade-Off", in IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 5, pp. 1156-1172, 1 May 2022, doi: 10.1109/TPDS.2021.3097281.
Downloads
Published
2022-07-28
Issue
Section
Artikel
License
Copyright (c) 2022 Journal Information System Development (ISD)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Penulis yang menerbitkan jurnal ini menyetujui persyaratan berikut:
- Penulis memiliki hak cipta dan memberikan hak untuk publikasi pertama jurnal dengan karya yang secara simultan dilisensikan di bawah Creative Commons Attribution License yang memungkinkan orang lain untuk berbagi karya dengan pengakuan kepengarangan karya dan publikasi awal dalam jurnal ini.
- Penulis dapat membuat perjanjian kontrak tambahan yang terpisah untuk distribusi non-eksklusif versi jurnal yang diterbitkan dari karya tersebut (misalnya, mempostingnya ke repositori institusional atau menerbitkannya dalam sebuah buku), dengan pengakuan atas publikasi awalnya di jurnal ini.
- Penulis diizinkan dan didorong untuk memposting karya mereka secara online (misalnya, dalam repositori institusional atau di situs web mereka) sebelum dan selama proses pengajuan, karena dapat menyebabkan pertukaran yang produktif, serta kutipan yang lebih awal dan lebih besar dari karya yang diterbitkan (Lihat Pengaruh Akses Terbuka).
