PENGEMBANGAN SENSOR-CLOUD PADA SMART CITY UNTUK MENGHADIRKAN KETERSEDIAAN DATA WAKTU NYATA

I Made Murwantara

Abstract


Pengembangan dan operasional dari sebuah Smart-City bergantung sepenuhnya pada lebih dari satu kelompok sumber data waktu nyata. Bentuk integrasi data ini kemungkinan dapat terwujud melalui manajemen Sensor-Fusion. Sumber daya utama untuk mencapai tujuan ini adalah denga keberadaan suatu kelompok sensor virtual yang dapat dipercaya kinerjanya yang adaptif terhadap perubahan lingkungan seperti permasalahan pengiriman data. Kestabilan operasional dari jaringan sensor harus dikedepankan karena sistem ini bergantung pada kondisi stabil tersebut. Menanggapi hal tersebut, suatu sistem waktu nyata yang terintegrasi secara kompleks atau rumit, umumnya, mengalami ketidakstabilan pengaliran data yang berakibat pada munculnya faktor penyimpangan. Dalam artikel ini, suatu pemikiran mengenai Sensor-Cloud yang menyediakan layanan pengaliran data waktu nyata dengan dasar berpikir bentuk virtualisasi akan diutarakan. Suatu pendekatan dengan konsep utama kombinasi dari Komputasi Awan, Internet of Things dan Akusisi data diajukan. Suatu demonstrasi sederhana untuk memperlihatkan kemampuan dari hasil penelitian ini akan diperlihatkan.

References


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[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", Working Paper, IEEE, 2017

[3] Safa Ben Atitallah, Maha Driss, Wadii Boulila, Henda Ben 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, 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-Martínez 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 Rakotonirainy, A "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] HerawatiM., & DjunaediA. (2020). 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. https://doi.org/10.29244/jp2wd.2020.4.1.63-73

[9] Hayashi, T., Sakaji, H., Matsushima, H. 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

[10] G. 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.

[11] 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 Made Murwantara, H Tjahyadi, P Yugopuspito, A Aribowo, IA 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] Martin, D., Kühl, N. & Satzger, G. Virtual Sensors. Bus Inf Syst Eng 63, 315–323 (2021). https://doi.org/10.1007/s12599-021-00689-w

[15] I Made Murwantara, "An Initial Framework of Dynamic Software Product Line Engineering for Adaptive Service" Robot. 2020. DOI:10.1109/ICOSICA49951.2020.9243199.

[16] João Gama, Indrė Žliobaitė, Albert Bifet, Mykola Pechenizkiy, and Abdelhamid Bouchachia. 2014. A survey on concept drift adaptation. ACM Comput. Surv. 46, 4, Article 44 (April 2014), 37 pages. https://doi.org/10.1145/2523813

[17] Yu, Hang and Liu, Tianyu and Lu, Jie and Zhang, Guangquan, " Automatic Learning to Detect Concept Drift", 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.

//remove to enable link on refferences

[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", Working Paper, IEEE, 2017

[3] Safa Ben Atitallah, Maha Driss, Wadii Boulila, Henda Ben 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, 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-Martínez 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 Rakotonirainy, A "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] HerawatiM., & DjunaediA. (2020). 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. https://doi.org/10.29244/jp2wd.2020.4.1.63-73

[9] Hayashi, T., Sakaji, H., Matsushima, H. 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

[10] G. 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.

[11] 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 Made Murwantara, H Tjahyadi, P Yugopuspito, A Aribowo, IA 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] Martin, D., Kühl, N. & Satzger, G. Virtual Sensors. Bus Inf Syst Eng 63, 315–323 (2021). https://doi.org/10.1007/s12599-021-00689-w

[15] I Made Murwantara, "An Initial Framework of Dynamic Software Product Line Engineering for Adaptive Service" Robot. 2020. DOI:10.1109/ICOSICA49951.2020.9243199.

[16] João Gama, Indrė Žliobaitė, Albert Bifet, Mykola Pechenizkiy, and Abdelhamid Bouchachia. 2014. A survey on concept drift adaptation. ACM Comput. Surv. 46, 4, Article 44 (April 2014), 37 pages. https://doi.org/10.1145/2523813

[17] Yu, Hang and Liu, Tianyu and Lu, Jie and Zhang, Guangquan, " Automatic Learning to Detect Concept Drift", 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.


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Computer Science Faculty | Universitas Pelita Harapan | ji.uphmedan@uph.edu