Series-1 (Mar. - Apr. 2026)Mar. - Apr. 2026 Issue Statistics
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| Paper Type | : | Research Paper |
| Title | : | Energy Efficient FPGA Architecture For Slam Front End Processing |
| Country | : | India |
| Authors | : | Bezawada Geetha Madhuri || Bhukya Vijaya Sri || Badarla Rushika || Boddu Yeswanth Kumar || Dr. N. Samba Murthy |
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: | 10.9790/2834-2102010104  |
Abstract: Simultaneous Localization and Mapping (SLAM) is a core capability for autonomous robots, drones, and embedded vision systems, but its front-end processing—including sensor data acquisition, feature extraction, and data association—demands high computational throughput with strict power constraints. This paper presents an energy-efficient FPGA-based architecture for SLAM front-end processing, optimized for real-time performance.....
Key Words: Energy-efficient computing, FPGA architecture, SLAM front-end, real-time processing, hardware acceleration, embedded systems, feature extraction, low-power design, parallel processing, autonomous navigation.
[1].
H. Durrant-Whyte And T. Bailey,“Simultaneous Localization And Mapping: Part I,”Ieee Robotics & Automation Magazine, Vol. 13, No. 2, Pp. 99–110, June 2025.
[2].
T. Bailey And H. Durrant-Whyte,“Simultaneous Localization And Mapping (Slam): Part Ii,”Ieee Robotics & Automation Magazine, Vol. 13, No. 3, Pp. 108–117, Sept. 2024.
[3].
M. Montemerlo, S. Thrun, D. Koller, And B. Wegbreit,“Fastslam: A Factored Solution To The Simultaneous Localization And Mapping Problem,”Proceedings Of The Aaai National Conference On Artificial Intelligence, 2021.
[4].
R. Smith, M. Self, And P. Cheeseman,“Estimating Uncertain Spatial Relationships In Robotics,” Autonomous Robot Vehicles, Springer, Pp. 167–193, 2019.
[5].
J. Engel, T. Schöps, And D. Cremers,“Orb-Slam: A Versatile And Accurate Monocular Slam System,” Ieee Transactions On Robotics, Vol. 31, No. 5, Pp. 1147–1163, Oct. 2023
- Citation
- Abstract
- Reference
- Full PDF
| Paper Type | : | Research Paper |
| Title | : | Research On Infrared Fault Detection Of Substation Equipment Based On Deep Learning |
| Country | : | China |
| Authors | : | Ruxin Gao || Hao Ding |
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: | 10.9790/2834-2102010513 |
Abstract: The reliable operation of power systems cannot be achieved without efficient and precise operation and maintenance methods. Based on the problems existing in actual operation and maintenance, and starting from the demand orientation, this paper focuses on the characteristics of low efficiency, reliance on judgment experience, and uncertainty of manual inspection in substations, and proposes a target detection method based on deep learning and YOLOv7. This method is an improvement on the traditional target detection. Through ablation and comparison experiments, the improved model can enhance detection accuracy, reduce the network model, and increase detection speed compared with the traditional model.....
Key Words: Substation inspection Data augmentation Bidirectional feature pyramid network "Lightweight; Defect detection.
[1]
Song, Y. , Deng, P. , Cai, M. , & Chen, F. . (2014). The Application Of Inspection Robot In Substation Inspection.Springer, Cham.
[2]
Rong, X. , & Liu, Y. . (2024). Research On The Cultivation Of Artificial Intelligence Professionals In Vocational Colleges.Journal Of Education And Educational Research,10(2), 251-256.
[3]
Vilakazi, C. B. , & Marwala, T. . (2006). Bushing Fault Detection And Diagnosis Using Extension Neural Network.IEEE.
[4]
Mete, M. , Sakoglu, U. , Spence, J. S. , Devous, M. D. , Harris, T. S. , & Adinoff, B. . (2016). Successful Classification Of Cocaine Dependence Using Brain Imaging: A Generalizable Machine Learning Approach.Bmc Bioinformatics,17(13), 357.
[5]
Xiao, L. , Chen, G. , Man, Y. , Xiao, W. , Yuan, L. , & Tao, Q. . (2024). Belt Abnormal High-Temperature Detection Algorithm Based On Improved Yolov7-Tiny.2024 IEEE 7th Information Technology, Networking, Electronic And Automation Control Conference (ITNEC), 936-941.