Research Projects
I have been doing research on ubiquitous intelligent system to be implemented in smart health, smart agriculture, and smart home/office. I’m also doing research on network and security topics.
Smart Health
Keywords: Health monitoring, early diagnosis, machine/deep learning, microservices, edge computing
Description: Big data and Internet-of-Things (IoT) systems can be incredibly valuable in health monitoring, as they can help to gather, store, analyze, and visualize large amounts of health-related data in real-time. A big data system for health monitoring should be able to scale up to handle large volumes of data, ensure data security and privacy, and provide real-time processing and analytics. In this research, we develop a smart health monitoring system for real-time analysis and early diagnosis of diseases and health problems using machine/deep learning
Related Publications:
- Simanjuntak E, Surantha N. Multiple time series database on microservice architecture for IoT-based sleep monitoring system. Journal of Big Data. 2022 Dec;9(1):1-9.
- N. Surantha, O. K. Utomo, E. M. Lionel, I. D. Gozali and S. M. Isa, “Intelligent Sleep Monitoring System based on Microservices and Event-Driven Architecture,” in IEEE Access, doi: 10.1109/ACCESS.2022.3167637.
- N. Surantha, T.F. Lesmana, S.M. Isa, “Sleep Stage Classification using Extreme Learning Machine and Particle Swarm Optimization for Healthcare Big Data”, Journal of Big Data, Springer Open, Vol. 8, No. 14, 2021. https://doi.org/10.1186/s40537-020-00406-6
- N. Surantha, Alvin C, Lusiana T. ENHANCING HEALTH MONITORING SYSTEM PERFORMANCE WITH GEO-IP DNS BASED LOAD BALANCING. Int J Innov Comput Inf Control ICIC Int c. 2021;17(6):1937–53.
- R. Rohmantri and N. Surantha, “Arrhythmia Classification using 2D Convolutional Neural Network” International Journal of Advanced Computer Science and Applications(IJACSA), 11(4), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110427
- N. Surantha, C. Adiwiputra, O. K. Utomo, S. M. Isa and B. Soewito, “IoT System for Sleep Quality Monitoring using Ballistocardiography Sensor” International Journal of Advanced Computer Science and Applications (IJACSA), 11(1), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110126
Smart Home/Office
Keywords: face recognition, object detection, indoor positioning system, intruder detection, machine/deep learning
Description: In this research, we develop a IoT-based smart home/office system for various applications using machine/deep learning.
Related Publications:
- Surantha N, Sugijakko B. Lightweight face recognition-based portable attendance system with liveness detection. Internet of Things. 2024 Apr 1;25:101089. https://doi.org/10.1016/j.iot.2024.101089
- Surantha N, Yose E, Isa SM. Low-Resolution Face Recognition for CCTV and Edge-Powered Smart Attendance Systems. In2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC) 2024 Jul 2 (pp. 676-681). IEEE. 10.1109/COMPSAC61105.2024.00097
- R. Saputra, N. Surantha, “Smart and real-time door lock system for an elderly user based on face recognition”, Bulletin of Electrical Engineering and Informatics, Vol. 10., No. 3, 2021. https://doi.org/10.11591/eei.v10i3.2955
- V. Simadiputra, N. Surantha, “Rasefiberry: Secure and Efficient Raspberry-Pi based Gateway for Smarthome IoT Architecture” Bulletin of Electrical Engineering and Informatics, Vol. 10, No. 2, 2021. https://doi.org/10.11591/eei.v10i2.2741
- Surantha, N., Liujaya, S., Sunardy, A., Harvy, I., Design and Evaluation of Indoor Positioning System for User Access Management in Data Center,(2019)International Journal on Communications Antenna and Propagation (IRECAP), 9 (6), pp. 393-402. https://doi.org/10.15866/irecap.v9i6.17026
- Surantha, N., & Wicaksono, W. R. (2019). An IoT based House Intruder Detection and Alert System using Histogram of Oriented Gradients. Journal of Computer Science, 15(8), 1108-1122. https://doi.org/10.3844/jcssp.2019.1108.1122
Smart Agriculture
Keywords: nutrient control, smart hydroponic, smart urban farming, machine/deep learning
Description: In this research, we develop a IoT-based smart agriculture system for various applications using machine/deep learning.
Related Publications:
- Vincentdo, V.; Surantha, N. Nutrient Film Technique-Based Hydroponic Monitoring and Controlling System Using ANFIS. Electronics 2023, 12, 1446. https://doi.org/10.3390/electronics12061446
- Atmaja P, Surantha N. , Smart hydroponic based on nutrient film technique and multistep fuzzy logic. International Journal of Electrical & Computer Engineering (2088-8708). 2022 Jun 1;12(3).
- Herman, N. Surantha, ”Smart Hydroculture Control System based on IoT and Fuzzy Logic,” International Journal of Innovative Computing, Information and Control, Vol. 16, No. 1, pp.207-221, Feb. 2020. 10.24507/ijicic.16.01.207
Network and Cyber Security
Keywords: software-defined network, 5G network, Kubernetes, network attack detection using machine/deep learning.
Description: In this research, we focus on the development and evaluation of next-generation network.
Related Publications:
- Surantha N, Putra NA. Integrated SDN-NFV 5G Network Performance and Management-Complexity Evaluation. Future Internet. 2022 Dec;14(12):378.
- N. Surantha, Z. Hakim, “Network Performance and Management-complexity Evaluation of Software- Defined Access Network in Multi-Tenancy Scenario”, International Journal on Communications Antenna and Propagation (IRECAP), Vol. 11., No. 1, Jan. 2021 https://doi.org/10.15866/irecap.v11i1.19208
- Surantha, N., Ivan, F. (2020). Secure Kubernetes Networking Design Based on Zero Trust Model: A Case Study of Financial Service Enterprise in Indonesia. In: Barolli, L., Xhafa, F., Hussain, O. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing . IMIS 2019. Advances in Intelligent Systems and Computing, vol 994. Springer, Cham. https://doi.org/10.1007/978-3-030-22263-5_34
- G. Habibi and N. Surantha, “XSS Attack Detection With Machine Learning and n-Gram Methods,” 2020 International Conference on Information Management and Technology (ICIMTech), Bandung, Indonesia, 2020, pp. 516-520, doi: 10.1109/ICIMTech50083.2020.9210946.
- A.S. Putra and N. Surantha, “Internal Threat Defense using Network Access Control and Intrusion Prevention System” International Journal of Advanced Computer Science and Applications(IJACSA), 10(9), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100948
Digital Transformation in Electrical Power Engineering
Description: Power Transmission Line (PTL) systems require routine inspections for early damage detection and maintenance to transmit high-voltage electric power efficiently and continuously. Previously, these inspections have been performed using line crawling, inspection robots, and a helicopter. However, these conventional solutions are sluggish, expensive, and risky. The recent development of drones, high-resolution cameras, single board computers (SBC), and deep learning technology enables PTL inspection using drones. In this research, we develop a power transmission line inspection system using autonomous drone and deep learning.
Keywords: power line inspection, machine/deep learning, autonomous drone, object detection, damage detection
Related Publications:
- Surantha N, Yamashina E, Sato Y, Iwao T. Power Transmission Line Component Detection Using YOLOv7 on Single-Board Computer Platforms. In2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring) 2024 Jun 24 (pp. 1-6). IEEE.
- Surantha N, Sukizaki Y, Yamashina E, Iwao T. Power Transmission Line Component Detection using YOLO V3 on Raspberry Pi. In2023 22nd International Symposium on Communications and Information Technologies (ISCIT) 2023 Oct 16 (pp. 139-144). IEEE.
- N. Surantha, T. Iwao, Z. Ren and H. Morishita, “Digital Transformation on Power Transmission Line Inspection using Autonomous Drone and Deep Learning,” 2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI), Singapore, Singapore, 2022, pp. 80-86, doi: 10.1109/RAAI56146.2022.10092983.