YOLO-LIO: A Real-Time Enhanced Detection and Integrated Traffic Monitoring System for Road Vehicles Rachmat Muwardi, Haiyang Zhang, Hongmin Gao, Mirna Yunita, Rizky Rahmatullah, et al. Algorithms, 2026 Traffic violations and road accidents remain significant challenges in developing safe and efficient transportation systems. Despite technological advancements, improving vehicle detection accuracy and enabling real-time traffic management remain critical research priorities. This study proposes YOLO-LIO, an enhanced vehicle detection framework designed to address these challenges by improving small-object detection and optimizing real-time deployment. The system introduces multi-scale detection, virtual zone filtering, and efficient preprocessing techniques, including grayscale transformation, Laplacian variance calculation, and median filtering to reduce computational complexity while maintaining high performance. YOLO-LIO was rigorously evaluated on five datasets, GRAM Road-Traffic Monitoring (99.55% accuracy), MAVD-Traffic (99.02%), UA-DETRAC (65.14%), KITTI (94.21%), and an Author Dataset (99.45%), consistently demonstrating superior detection capabilities across diverse traffic scenarios. Additional system features include vehicle counting using a dual-line detection strategy within a virtual zone and speed detection based on frame displacement and camera calibration. These enhancements enable the system to monitor traffic flow and vehicle speeds with high accuracy. YOLO-LIO was successfully deployed on Jetson Nano, a compact, energy-efficient hardware platform, proving its suitability for real-time, low-power embedded applications. The proposed system offers an accurate, scalable, and computationally efficient solution, advancing intelligent transportation systems and improving traffic safety management.
Phase Laser Ranging Radar Based on IoT Communication Ketty Siti Salamah, Trie Maya Kadarina, Puput Dani Prasetyo Adi, Rachmat Muwardi, Rizky Rahmatullah, et al. International Conference on Computer and Communication Engineering Iccce, 2025
HorGait: Advancing Gait Recognition With Efficient High-Order Spatial Interactions in LiDAR Point Clouds Jiaxing Hao, Yanxi Wang, Zhigang Chang, Hongmin Gao, Zihao Cheng, et al. IEEE Access, 2025 Gait recognition is a remote biometric technology that utilizes the dynamic characteristics of human movement to identify individuals even under various extreme lighting conditions. Due to the limitation in spatial perception capability inherent in 2D gait representations, LiDAR can directly capture 3D gait features and represent them as point clouds, reducing environmental and lighting interference in recognition while significantly advancing privacy protection. For complex 3D representations, shallow networks fail to achieve accurate recognition, making vision Transformers the foremost prevalent method. However, the prevalence of dumb patches has limited the widespread use of Transformer architecture in gait recognition. This paper proposes a method named HorGait, which utilizes a hybrid model with a Transformer architecture for gait recognition on the planar projection of 3D point clouds from LiDAR. Specifically, it employs a hybrid model structure called LHM Block to achieve input adaptation, long-range, and high-order spatial interaction of the Transformer architecture. Additionally, it uses large convolutional kernel CNNs to segment the input representation, replacing attention windows to reduce dumb patches. Extensive experiments demonstrated that HorGait achieved a Rank-1 accuracy of 82.54% on the SUSTech1K dataset, surpassing the state-of-the-art Transformer architecture method by 8.33%. This confirms the hybrid model’s ability to execute the complete Transformer process and excel in point cloud planar projection. The outstanding performance of HorGait offers new insights for the future application of the Transformer architecture in gait recognition.
Design of New Traffic System YOLO-LIO: Light-Traffic Intercept and Observation Rachmat Muwardi, Haiyang Zhang, Hongmin Gao, Mirna Yunita, Yanxi Wang, et al. Proceeding 2024 International Conference on Radar Antenna Microwave Electronics and Telecommunications Icramet 2024, 2024 Vehicle detection is an area of active development aimed at enhancing driving safety and ensuring compliance with traffic regulations. Despite ongoing efforts, accidents and traffic violations continue to pose significant challenges, leading to disruptions in driving. In response to these issues, the author aims to develop a more efficient traffic management system to improve driver organization and driving behavior. To achieve this, the author proposes using YOLO-LIO as the neural network of choice for the Traffic System. The effectiveness of YOLO-LIO was evaluated using three datasets: the Montevideo Audio and Video Dataset (MAVD), the GARM Road-Traffic Monitoring dataset (GRAM-RTM), and a custom dataset created by the author. The results highlight the superior performance of YOLO-LIO in vehicle detection tasks, achieving accuracy rates of $\\mathbf{9 9. 0 2 \\%}$ on the MAVD dataset, $\\mathbf{9 9. 5 5 \\%}$ on the GRAM-RTM dataset, and $\\mathbf{9 9. 3 2 \\%}$ on the custom dataset. This demonstrates the model’s high effectiveness across various datasets. Additionally, the author conducted experiments incorporating OCR technology with the YOLO-LIO algorithm in the Traffic System. The system achieved an accuracy of $\\mathbf{8 0. 2 1 \\%}$ in vehicle number detection, demonstrating its effectiveness. This result reflects the overall performance of the entire system process, from data input to the final detection output, ensuring a comprehensive and accurate detection mechanism. Compared to other algorithms such as YOLOv3 + OCR, YOLOv4, and Faster R-CNN, YOLO-LIO + OCR, they have exhibited significantly better performance. These promising results highlight the potential of YOLO-LIO in creating a robust Traffic System that can significantly enhance road safety and traffic regulation compliance.
The automatic and manual railroad door systems based on IoT Setiyo Budiyanto, Freddy Artadima Silaban, Lukman Medriavin Silalahi, Triyanto Pangaribowo, Muhammad Hafizd Ibnu Hajar, et al. Indonesian Journal of Electrical Engineering and Computer Science, 2021
Research and Design of Fast Special Human Face Recognition System Rachmat Muwardi, Huangyao Qin, Hongmin Gao, Harun Usman Ghifarsyam, Muhammad Hafizd Ibnu Hajar, et al. 2020 2nd International Conference on Broadband Communications Wireless Sensors and Powering Bcwsp 2020, 2020
RECENT SCHOLAR PUBLICATIONS
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Phase Laser Ranging Radar Based on IoT Communication KS Salamah, TM Kadarina, PDP Adi, R Muwardi, R Rahmatullah, ... 2025 10th International Conference on Computer and Communication Engineering … , 2025 2025
Design and Implementation of a Real-Time Monitoring System for a 150 kV Substation with Multi-Platform Notification and Visualization: English EAY Kartika, R Muwardi, R Rahmatullah, M Yunita, Y Yuliza, AW Dani Internet of Things and Artificial Intelligence Journal 5 (2), 409-418 , 2025 2025
HorGait: Advancing Gait Recognition With Efficient High-Order Spatial Interactions in LiDAR Point Clouds J Hao, Y Wang, Z Chang, H Gao, Z Cheng, C Wu, X Zhao, P Fang, ... IEEE Access , 2025 2025 Citations: 2
Multinode LoRa-MQTT of Design Architecture and Analyze Performance for Dual Protocol Network IoT. R Rahmatullah, H Gao, RP Utama, PDP Adi, J Mubashir, R Muwardi, ... International Journal of Advanced Computer Science & Applications 16 (1) , 2025 2025 Citations: 6
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Optimization of YOLOv4-tiny algorithm for vehicle detection and vehicle count detection embedded system R Muwardi, IP Nugroho, KS Salamah, M Yunita, R Rahmatullah, ... Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) 10 (3), 639-648 , 2024 2024 Citations: 10
Horgait: A hybrid model for accurate gait recognition in lidar point cloud planar projections J Hao, Y Wang, Z Chang, H Gao, Z Cheng, C Wu, X Zhao, P Fang, ... arXiv preprint arXiv:2410.08454 , 2024 2024 Citations: 3
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Kalman Filter for tracking a noisy cosinusoidal signal with constant amplitude PW Kusuma, MH Habaebi, GPN Hakim, R Muwardi, MR Islam 2023 9th International Conference on Computer and Communication Engineering … , 2023 2023 Citations: 1
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MOST CITED SCHOLAR PUBLICATIONS
Design Sistem Keamanan Pintu Menggunakan Face Detection R Muwardi, RR Adisaputro Jurnal Teknologi Elektro 12, 113-119 , 2021 2021 Citations: 31
Network Security Monitoring System Via Notification Alert R Muwardi, H Gao, HU Ghifarsyam, M Yunita, A Arrizki, J Andika Journal of Integrated and Advanced Engineering (JIAE) 1 (2), 113-122 , 2021 2021 Citations: 24
Human object detection for real-time camera using mobilenet-SSD R Muwardi, JMR Permana, H Gao, M Yunita Journal of Integrated and Advanced Engineering (JIAE) 3 (2), 141-150 , 2023 2023 Citations: 16
The automatic and manual railroad door systems based on IoT S Budiyanto, FA Silaban, LM Silalahi, T Pangaribowo, MHI Hajar, ... Indonesian Journal of Electrical Engineering and Computer Science 21 (3 … , 2021 2021 Citations: 13
Research and Design of Fast Special Human Face Recognition System R Muwardi, H Qin, H Gao, HU Ghifarsyam, MHI Hajar, M Yunita 2020 2nd International Conference on Broadband Communications, Wireless … , 2020 2020 Citations: 12
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Delivery of data digital high frequency radio wave using advanced encryption standard security mechanism S Budiyanto, LM Silalahi, FA Silaban, R Muwardi, H Gao 2021 International Seminar on Intelligent Technology and Its Applications … , 2021 2021 Citations: 11
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Modification of Control Oil Feeding with PLC Using Simulation Visual Basic and Neural Network Analysis Y Yuliza, R Muwardi, DW Pratama, MH Santoso, M Yunita Jurnal Ilmiah Teknik Elektro Komputer dan Informatika 8, 38-50 , 2022 2022 Citations: 9
Optimize image processing algorithm on arm cortex-a72 and a53 R Muwardi, M Yunita, H Ghifarsyam, H Juliyanto Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika 8 (3), 399-409 , 2022 2022 Citations: 8
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Smart Cupboards at Community Learning Activity Center Wiyata Utama IUV Simanjuntak, LM Silalahi, KS Salamah, F Supegina, R Muwardi ABDIMAS: Jurnal Pengabdian Masyarakat 7 (2), 749-755 , 2024 2024 Citations: 4
Design human object detection yolov4tiny algorithm on ARM cortex-a72 and a53 R Muwardi, A Faizin, PDP Adi, R Rahmatullah, Y Wang, M Yunita, ... Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) 9 (4), 1168-1178 , 2023 2023 Citations: 4
Monitoring chicken livestock process using Vento Application at a farm F Andika, R Muwardi, M Yunita, MA Purba Journal of Integrated and Advanced Engineering (JIAE) 2 (2), 77-88 , 2022 2022 Citations: 4
Horgait: A hybrid model for accurate gait recognition in lidar point cloud planar projections J Hao, Y Wang, Z Chang, H Gao, Z Cheng, C Wu, X Zhao, P Fang, ... arXiv preprint arXiv:2410.08454 , 2024 2024 Citations: 3
Fiber Optic Attenuation Analysis Based on Mamdani Fuzzy Logic in Gambir Area, Central Jakarta Y Yuliza, N Sari, R Muwardi, L Lenni, Y Rahmawati Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) 8 (4), 610 , 2022 2022 Citations: 3