Here are the list of research projects of our lab
Digital Transformation on Power Transmission Line Inspection using Autonomous Drone and Deep Learning
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.
Research Grants:
- FY2022東京都市大学、理工学部・建築都市デザイン学部 、若手奨励支援予算、FY2022 Tokyo City University, Faculty of Science and Engineering/Faculty of Architecture and Urban Design, Young Encouragement Support Budget, Title: “Real-Time Detection of Component and Damage using Deep Learning in Autonomous Drone-Based Powerline Inspection”
- 東京都市大学の2023年度「重点推進研究-若手研究」2023 Tokyo City University (Priority Promotion Research – Young Researcher), Title: “Digital transformation of transmission line inspection using autonomous drones and deep learning”
Related Publications:
- 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.
Smart Home Energy Management using IoT and Deep Learning
Description: The rising cost and demand for energy have prompted numerous organizations to seek innovative methods of monitoring, controlling, and conserving energy. An intelligent Energy Management System (EMS) may assist in reducing costs while still meeting energy demand. Internet of Things (IoT) and Big Data are emerging technologies that can be utilized to better manage energy consumption in residential, commercial, and industrial sectors. In this research, we explore the utilization of IoT, Big Data, and Deep Learning to create smart home energy management systems.
Artificial Intelligence on Edge Computing for Health Monitoring
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 the edge computing device for real-time analysis and early diagnosis of diseases and health problem 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