This is our latest selection of worldwide publications and patents in english on Open Source Intelligence (OSINT), between many scientific online journals, classified and focused on OSINT, data mining, social media analysis, web scraping, geolocation, metadata analysis, threat intelligence and open data.
Moving Target Geolocation and Trajectory Prediction Using a Fixed-Wing UAV in Cluttered Environments
Published on 2025-03-10 by Yong Zhou, Dengqing Tang, Han Zhou, Xiaojia Xiang @MDPI
Abstract: The application of UAVs in surveillance, disaster management, and military operations has surged, necessitating robust and real-time tracking systems for moving targets. However, accurately tracking and predicting the trajectories of ground targets pose significant challenges due to factors such as target occlusion, varying speeds, and dynamic environments. To address these challenges and advance the capabilities of UAV-based tracking systems, a novel vision-based approach is introduced in this [...]
Our summary: Real-time tracking, geolocation, and trajectory prediction of moving ground targets using a fixed-wing UAV in cluttered environments. Enhanced UAV autonomy and decision-making capabilities through an integrated algorithm combining object detection, target geolocation, and trajectory estimation. Validation through real flight experiments showcasing effectiveness and feasibility.
geolocation, trajectory prediction, UAV, moving target
Publication
Enhancing Smart Cities’ Resilience Through Competency Assessment and Open Data Utilization
Published on 2025-03-05 by Isabel Ramos, Victor Barros, Angelika Kokkinaki, Chrysostomi Maria Kyrillou, Alkis Thrassou, Katharina Ebner, Christian Ansch�tz, Panos Fitsilis, Paraskevi Tsoutsa, Theodor Panagiotakopoulos, Achilles Kameas @MDPI
Abstract: The increasing frequency of natural catastrophes and other disasters has underscored the importance of resilience as a core competence for smart cities so that they efficiently manage unforeseen crises. The increasing recognition of resilience in the context of smart cities leads to examining the role and context for the role of the “Smart City Resilience Officer” (SCRO). This article addresses this research gap by exploring the significance of resilience in smart cit[...]
Our summary: Importance of resilience for smart cities, role of Smart City Resilience Officer, self-assessment model for evaluating skills, significance of open data in enhancing resilience, competencies for SCROs, competency assessment methodology, resilience policies in Europe, large-scale training programs for developing competencies.
resilience, competency assessment, open data, smart cities
Publication
Improved Detection and Location of Small Crop Organs by Fusing UAV Orthophoto Maps and Raw Images
Published on 2025-03-04 by Huaiyang Liu, Huibin Li, Haozhou Wang, Chuanghai Liu, Jianping Qian, Zhanbiao Wang, Changxing Geng @MDPI
Abstract: Extracting the quantity and geolocation data of small objects at the organ level via large-scale aerial drone monitoring is both essential and challenging for precision agriculture. The quality of reconstructed digital orthophoto maps (DOMs) often suffers from seamline distortion and ghost effects, making it difficult to meet the requirements for organ-level detection. While raw images do not exhibit these issues, they pose challenges in accurately obtaining the geolocation data of detected smal[...]
Our summary: Improved detection and location of small crop organs through the fusion of UAV orthophoto maps and raw images using EasyIDP tool. Accelerated detection speed and improved accuracy achieved with SAHI-YOLOv10n framework. Creation of CCOD-Dataset for organ-level object detection in large-scale farmlands.
Precision Agriculture, UAV Monitoring, Object Detection, Geolocation Data
Publication
Artificial Intelligence-Based Fault Diagnosis for Steam Traps Using Statistical Time Series Features and a Transformer Encoder-Decoder Model
Published on 2025-03-03 by Chul Kim, Kwangjae Cho, Inwhee Joe @MDPI
Abstract: Steam traps are essential for industrial systems, ensuring steam quality and energy efficiency by removing condensate and preventing steam leakage. However, their failure results in energy loss, operational disruptions, and increased greenhouse gas emissions. This paper proposes a novel predictive maintenance system for steam traps that integrates statistical time series features and transformer encoder–decoder models for fault diagnosis and visualization. The proposed system combi[...]
Our summary: This paper presents a novel AI-based fault diagnosis system for steam traps using statistical time series features and a transformer encoder-decoder model. The system integrates IoT sensor data, operational parameters, open data, and machine learning for improved reliability and interpretability. Experiments in industrial plants showed superior defect detection accuracy and diagnostic reliability, with a 6.92% reduction in thermal energy and potential for sustainable manufacturing practices.
Artificial Intelligence, Fault Diagnosis, Transformer Encoder-Decoder Model, Predictive Maintenance
Publication
Research on Fault Recognition of Roadheader Based on Multi-Sensor and Multi-Layer Local Projection
Published on 2025-03-01 by Xiaodong Ji, Rui An, Hai Jiang, Yan Du, Weixiong Zheng @MDPI
Abstract: The working environment at coal mining faces is harsh, leading to high failure rates and significant maintenance issues with roadheaders. This study explores multi-layer dimensionality reduction of vibration signal features in complex environments to enhance the differentiation of different operational states of a roadheader, thereby achieving fault recognition of key components. Concurrently, reducing dimensionality in manifold spaces positively influences operational state differentiation. The[...]
Our summary: This study explores multi-layer dimensionality reduction of vibration signal features in complex environments to enhance the differentiation of different operational states of a roadheader, achieving fault recognition of key components. Utilizing locality-preserving projections (LPP) to extract low-dimensional manifold features, the study integrates manifold learning to conduct multi-sensor and multi-layer data mining, achieving a recognition success rate of 98.75% for samples.
Fault Recognition, Multi-Sensor, Manifold Learning, Vibration Signals
Publication
Collision Avoidance Behavior Mining Model Considering Encounter Scenarios
Published on 2025-02-28 by Shuzhe Chen, Chong Zhang, Lei Wu, Ziwei Wang, Wentao Wu, Shimeng Li, Haotian Gao @MDPI
Abstract: With the development of intelligent waterborne transportation, mining collision avoidance patterns based on spatiotemporal and motion data of ships are crucial for the autonomous navigation of intelligent ships, which requires accurate collision avoidance information under various encounter scenarios. Addressing the existing issues of low precision and false detection in data mining algorithms, this paper proposes a collision avoidance behavior mining model considering encounter scenarios. The m[...]
Our summary: With the development of intelligent waterborne transportation, mining collision avoidance patterns based on spatiotemporal and motion data of ships are crucial for the autonomous navigation of intelligent ships. Addressing the existing issues of low precision and false detection in data mining algorithms, this paper proposes a collision avoidance behavior mining model considering encounter scenarios. The model is based on the Automatic Identification System (AIS) and the International Regulations for Preventing Collisions at Sea (COLREGs).
collision avoidance, behavior mining model, encounter scenarios, spatiotemporal data
Publication
Cloud enabled augmented reality
Patent published on the 2025-02-19 in EP under Ref EP4510082 by NIANTIC INC [US] (Finman Ross Edward [us], Hu Si Ying Diana [us])
Abstract: An augmented reality system generates computer-mediated reality on a client device. The client device has sensors including a camera configured to capture image data of an environment and a location sensor to capture location data describing a geolocation of the client device. The client device creates a three-dimensional (3-D) map with the image data and the location data for use in generating virtual objects to augment reality. The client device transmits the created 3-D map to an external ser[...]
Our summary: An augmented reality system utilizes sensors on a client device to create a 3-D map for generating virtual objects, which can be updated and displayed in real-time through a cloud server.
cloud enabled, augmented reality, computer-mediated reality, 3-D map
Patent
Tripwire-based geolocation system
Patent published on the 2025-02-19 in EP under Ref EP4510511 by ALARM COM INC [US] (Murdock John [us], Bingham Jasper [us], Chien Allen [us], Trundle Stephen Scott [us])
Abstract: Methods, systems, and apparatus, including computer programs encoded on a non-transitory computer storage medium, for receiving user-defined routes, each route including a tripwire of multiple tripwires and a direction, and including an action of multiple actions executed by a subsystem of a home monitoring system, detecting a first signal at a first tripwire including a first direction, determining a set of user-defined routes including the first tripwire and the first direction, detecting a se[...]
Our summary: System for receiving user-defined routes with tripwires and directions, detecting signals at tripwires, and triggering actions based on signals.
Tripwire, geolocation system, user-defined routes, home monitoring system
Patent
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