An AI-Powered Automatic License Plate Recognition System with an Azure IoT Hub Interface for Vehicle Identification and Tracking Deekshitha Angadi, Naveena Budda, Koteshwar Goud Surga, Ravi Killamsetty, Bharath Kumar Suryadevara, Sandeep Reddy Sabbella, Narsimlu Kemsaram 2025 10th International Conference on Research in Intelligent Computing in Engineering Rice 2025, 2025 Automatic license plate detection and recognition systems are crucial in modern intelligent transportation systems, including traffic control, toll collection, and parking management. This paper presents a real-time, AI-driven, Azure IoT-based automatic license plate recognition system tailored for Indian traffic environments. The system utilizes an Intel RealSense D435i depth camera paired with an Nvidia Jetson Xavier NX to capture vehicle images and extract license plate numbers using a lightweight deep learning pipeline: YOLOv8 for detection and EasyOCR for robust optical character recognition. The recognized license plate text is enriched with location and timestamp metadata and transmitted to the cloud through the Azure IoT Edge runtime. At the cloud level, the Azure IoT Hub enables seamless ingestion and routing of telemetry data to various services, including Azure Stream Analytics, SQL Database, and App Services. This infrastructure supports AIbased analytics, real-time alerting, and long-term data storage. A Web and mobile application interface - powered by Azure APIs and Power BI dashboards - allows traffic authorities to visualize vehicle data, monitor violations, and receive alerts for blocked or duplicated plates. The system achieves a detection accuracy of 95.4 % and an OCR precision of 92.3 % while maintaining an average throughput of 15 FPS. This scalable, low-latency automatic license plate recognition system offers an effective solution for intelligent traffic management and law enforcement in smart city applications. The proposed system offers a scalable and adaptable solution for automated license plate recognition in various applications.
Virtual Reality Applications for Enhancing Human-Robot Interaction: A Gesture Recognition Perspective Sandeep Reddy Sabbella, Sara Kaszuba, Francesco Leotta, Daniele Nardi Proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents Iva 2023, 2023 Human-Robot Interaction (HRI) has become increasingly important as robots have been integrated into various daily life aspects. Gesture recognition plays a crucial role in non-verbal communication in HRI. Indeed, the real-time robot's interpretation of human gestures is essential for enhancing the overall user experience. To this aim, improving the accuracy and efficiency of gesture recognition in HRI could be achieved by integrating Virtual Reality (VR) technology. In this article, we describe the development of virtually-generated avatars and a gesture recognition system that uses machine learning techniques to allow ground robots to recognize gestures performed by both digital agents and actual humans. Nevertheless, we address some existing challenges by presenting a set of gesture definitions, data generation, and system evaluation using virtual reality simulation. Our findings and results highlight the importance of addressing these challenges to enable effective gesture recognition in HRI. In particular, we demonstrate that the adoption of VR can significantly increase the system's accuracy and efficiency, improving the overall user experience.
Speech Act Classification in Collaborative Robotics Sara Kaszuba, Sandeep Reddy Sabbella, Francesco Leotta, Daniele Nardi IEEE International Workshop on Robot and Human Communication Ro Man, 2023 Collaborative robots seamlessly share the space with humans in production scenarios such as those involved in smart manufacturing and agriculture, thus raising several human safety concerns. Since a collaboration between humans and robots is performed through communicative acts, applying accurate techniques for understanding them is of the utmost importance to guarantee the overall safety of the human. A preliminary classification of the communicative acts into categories is required to increase the accuracy of adopted methods and the promptness of the response. This paper evaluates a speech communicative act classification methodology in the challenging scenario of precision agriculture using Virtual Reality (VR). Our proposal can easily be applied to any production scenario involving collaborative robots.
S-AvE: Semantic active vision exploration and mapping of indoor environments for mobile robots Vincenzo Suriani, Sara Kaszuba, Sandeep R. Sabbella, Francesco Riccio, Daniele Nardi 2021 10th European Conference on Mobile Robots Ecmr 2021 Proceedings, 2021 In order to operate and to understand human commands, robots must be provided with a knowledge representation integrating both geometric and symbolic knowledge. In the literature, such a representation is referred to as a semantic map that enables the robot to interpret user commands by grounding them to its sensory observations. However, even though a semantic map is key to enable cognition and high-level reasoning, it is a complex challenge to address due to generalization to various scenarios. As a consequence, commonly used techniques do not always guarantee rich and accurate representations of the environment and of the objects therein. In this paper, we set aside from previous approaches by attacking the problem of semantic mapping from a different perspective. While proposed approaches mainly focus on generating a reliable map starting from sensory observations often collected with a human user teleoperating the mobile platform, in this paper, we argue that the process of semantic mapping starts at the data gathering phase and it is a combination of both perception and motion. To tackle these issues, we design a new family of approaches to semantic mapping that exploit both active vision and domain knowledge to improve the overall mapping performance with respect to other map-exploration methodologies.
RECENT SCHOLAR PUBLICATIONS
An AI-Powered Automatic License Plate Recognition System with an Azure IoT Hub Interface for Vehicle Identification and Tracking D Angadi, N Budda, KG Surga, R Killamsetty, BK Suryadevara, ... 2025 10th International Conference on Research in Intelligent Computing in … , 2025 2025
Multimodal communication for enhancing human robot interaction: virtual simulations to real robots SR Sabbella Università degli Studi di Roma" La Sapienza" , 2025 2025
Assessing Multimodal Communication in Human-Robot Interaction: A User Study SR Sabbella, AT Salomons, F Leotta, D Nardi International Conference on Social Robotics, 56-70 , 2024 2024
Generating and Evaluating Synthetic Data in Virtual Reality Simulation Environments for Pose Estimation SR Sabbella, P Serrarens, F Leotta, D Nardi 2024 33rd IEEE International Conference on Robot and Human Interactive … , 2024 2024 Citations: 1
Evaluating gesture recognition in virtual reality SR Sabbella, S Kaszuba, F Leotta, P Serrarens, D Nardi arXiv preprint arXiv:2401.04545 , 2024 2024 Citations: 7
Testing human-robot interaction in virtual reality: experience from a study on speech act classification S Kaszuba, SR Sabbella, F Leotta, P Serrarens, D Nardi arXiv preprint arXiv:2401.04534 , 2024 2024 Citations: 3
Empowering collaboration: A pipeline for human-robot spoken interaction in collaborative scenarios S Kaszuba, J Caposiena, SR Sabbella, F Leotta, D Nardi International Conference on Social Robotics, 95-107 , 2023 2023 Citations: 1
Gesture recognition for human-robot interaction through virtual characters SR Sabbella, S Kaszuba, F Leotta, D Nardi International Conference on Social Robotics, 160-170 , 2023 2023 Citations: 4
Virtual reality applications for enhancing human-robot interaction: A gesture recognition perspective SR Sabbella, S Kaszuba, F Leotta, D Nardi Proceedings of the 23rd ACM International Conference on Intelligent Virtual … , 2023 2023 Citations: 9
Speech act classification in collaborative robotics S Kaszuba, SR Sabbella, F Leotta, D Nardi 2023 32nd IEEE International Conference on Robot and Human Interactive … , 2023 2023 Citations: 2
S-ave: Semantic active vision exploration and mapping of indoor environments for mobile robots V Suriani, S Kaszuba, SR Sabbella, F Riccio, D Nardi 2021 European conference on mobile robots (ECMR), 1-8 , 2021 2021 Citations: 8
Rosmeery: Robotic simulated environment for evaluation and benchmarking of semantic mapping algorithms S Kaszuba, SR Sabbella, V Suriani, F Riccio, D Nardi arXiv preprint arXiv:2105.07938 , 2021 2021 Citations: 3
Fire and Smoke Detection for Smart Cities Using Deep Neural Networks and Edge Computing on Embedded Sensors S Scardapane, G Trovini, SR Sabbella 2021 Citations: 2
MOST CITED SCHOLAR PUBLICATIONS
Virtual reality applications for enhancing human-robot interaction: A gesture recognition perspective SR Sabbella, S Kaszuba, F Leotta, D Nardi Proceedings of the 23rd ACM International Conference on Intelligent Virtual … , 2023 2023 Citations: 9
S-ave: Semantic active vision exploration and mapping of indoor environments for mobile robots V Suriani, S Kaszuba, SR Sabbella, F Riccio, D Nardi 2021 European conference on mobile robots (ECMR), 1-8 , 2021 2021 Citations: 8
Evaluating gesture recognition in virtual reality SR Sabbella, S Kaszuba, F Leotta, P Serrarens, D Nardi arXiv preprint arXiv:2401.04545 , 2024 2024 Citations: 7
Gesture recognition for human-robot interaction through virtual characters SR Sabbella, S Kaszuba, F Leotta, D Nardi International Conference on Social Robotics, 160-170 , 2023 2023 Citations: 4
Testing human-robot interaction in virtual reality: experience from a study on speech act classification S Kaszuba, SR Sabbella, F Leotta, P Serrarens, D Nardi arXiv preprint arXiv:2401.04534 , 2024 2024 Citations: 3
Rosmeery: Robotic simulated environment for evaluation and benchmarking of semantic mapping algorithms S Kaszuba, SR Sabbella, V Suriani, F Riccio, D Nardi arXiv preprint arXiv:2105.07938 , 2021 2021 Citations: 3
Speech act classification in collaborative robotics S Kaszuba, SR Sabbella, F Leotta, D Nardi 2023 32nd IEEE International Conference on Robot and Human Interactive … , 2023 2023 Citations: 2
Fire and Smoke Detection for Smart Cities Using Deep Neural Networks and Edge Computing on Embedded Sensors S Scardapane, G Trovini, SR Sabbella 2021 Citations: 2
Generating and Evaluating Synthetic Data in Virtual Reality Simulation Environments for Pose Estimation SR Sabbella, P Serrarens, F Leotta, D Nardi 2024 33rd IEEE International Conference on Robot and Human Interactive … , 2024 2024 Citations: 1
Empowering collaboration: A pipeline for human-robot spoken interaction in collaborative scenarios S Kaszuba, J Caposiena, SR Sabbella, F Leotta, D Nardi International Conference on Social Robotics, 95-107 , 2023 2023 Citations: 1
An AI-Powered Automatic License Plate Recognition System with an Azure IoT Hub Interface for Vehicle Identification and Tracking D Angadi, N Budda, KG Surga, R Killamsetty, BK Suryadevara, ... 2025 10th International Conference on Research in Intelligent Computing in … , 2025 2025
Multimodal communication for enhancing human robot interaction: virtual simulations to real robots SR Sabbella Università degli Studi di Roma" La Sapienza" , 2025 2025
Assessing Multimodal Communication in Human-Robot Interaction: A User Study SR Sabbella, AT Salomons, F Leotta, D Nardi International Conference on Social Robotics, 56-70 , 2024 2024
