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Le mobile laser scanning (MLS) est une méthode d'acquisition de nuages de points 3D qui permet une acquisition rapide et précise. Ce travail vise à développer une méthode de segmentation et de classification pour les nuages de points 3D relevés par MLS en environnement ferroviaire. La méthode se décompose en trois parties. La première est l'extraction du sol, des rails et des panneaux sur base des attributs du nuages. La seconde est le calcul de caractéristiques qui décrivent la structure du nuage. La dernière partie est la classification des éléments restants de l'infrastructure ferroviaire en utilisant le modèle de classification supervisée Random Forest. La méthode proposée obtient une exactitude globale de 99~\% avec un temps de traitement relativement rapide. Mobile laser scanning (MLS) is a 3D point cloud acquisition method that allows fast and accurate acquisition. This work aims to develop segmentation and classification method for 3D point clouds collected by MLS in a railway environment. The method consists of three parts. The first is the extraction of ground, rails and traffic signs based on cloud attributes. The second is the computation of features that describe the structure of the cloud. The last part is the classification of the remaining elements of the railway infrastructure using the Random Forest supervised classification model. The proposed method achieves an overall accuracy of 99~\% with a relatively fast processing time.

point cloud --- lidar --- mobile laser scanning --- segmentation --- classification --- Physique, chimie, mathématiques & sciences de la terre > Sciences de la terre & géographie physique

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Digital agriculture is gaining traction among scientists implementing different new and emerging sensor technologies to monitor complex soil–plant–atmosphere interactions in an accurate, cost-effective and user-friendly manner. This book presents some of the latest advances in this emerging area of research. The diversity of applications in which digital agriculture can make an important difference in day-to-day farming decision making makes this discipline an important focus of research internationally.

apple orchards --- modeling and simulation --- unmanned aerial vehicles --- fruit ripeness --- ethylene gas detection --- 3D crop modeling --- remote sensing --- on-ground sensing --- depth images --- parameter acquisition --- capacitor sensor --- deposit mass --- pesticide droplets --- formulations --- ionization --- CFD --- airflow field test --- monitoring method --- spectral sensor --- crop growth --- computer vision --- deep learning --- image processing --- pose estimation --- animal detection --- precision livestock --- Citrus sinensis L. Osbeck --- mechanical harvesting --- acceleration sensor --- vibration time --- logistic regression --- adaptive thresholding --- fruit detection --- parameter tuning --- phenotype --- phenotyping --- phenomics --- Triticum aestivum --- water deficit --- stress --- infrared --- leaf area index --- cocoa beans --- volatile compounds --- artificial neural networks --- VitiCanopy app --- bushfires --- infrared thermography --- near-infrared spectroscopy --- smoke taint --- artificial intelligence --- Kinect sensor --- RGB --- RGB-D --- image segmentation --- colour thresholding --- bunch area --- bunch volume --- point cloud --- mesh --- surface reconstruction --- image analysis --- cluster morphology --- machine learning --- non-invasive sensing technologies --- proximal sensing --- precision viticulture --- partial least square --- support vector machine --- Gaussian processes --- soybean --- pigeon pea --- guar --- tepary bean --- n/a

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“Smart Sensing Technologies for Agriculture” is a Special Issue of Sensors that includes 14 research papers on diverse topics about the measurement of physical, chemical, and biological characteristics of soil, plants, and animals related to modern farming practices.

History of engineering & technology --- moisture measurement --- Kalman filter --- model predictive control --- germination paper --- convolutional neural networks --- livestock --- lying posture --- standing posture --- Three-dimensional mapping --- quasi-3D inversion algorithm --- cation exchange capacity --- clay content --- sandy infertile soil --- optical micro-sensors --- crop protection --- precision agriculture --- infrared spectroscopy --- principal component analysis (PCA) --- partial least squares (PLS) --- droplet characterization --- apparent electrical conductivity (ECa) --- pH --- UAV --- boundary-line --- quantile regression --- law of minimum --- on-site detection --- ion-selective electrode (ISE) --- soil nitrate nitrogen (NO3−-N) --- soil moisture --- sensor fusion --- transfer learning --- deep learning --- body dimensions --- point cloud --- Kd-network --- feature recognition --- FFPH --- non-contact measurement --- X-ray fluorescence --- spectroscopy --- soil nutrients --- proximal soil sensing --- soil testing --- laser-induced breakdown spectroscopy --- LIBS --- elemental composition --- broiler surface temperature extraction --- thermal image processing --- head region locating --- adaptive K-means --- ellipse fitting --- harvesting robot --- gripper --- segmentation --- cutting point detection --- soil --- soil electrical resistivity --- autonomous robot --- real-time measurement --- precision farming --- mapping --- precision weeding --- multispectral imaging --- kinetic stereo imaging --- plant detection --- yield estimation --- machine vision --- willow tree

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This book presents the results of the successful Sensors Special Issue on Intelligent Vehicles that received submissions between March 2019 and May 2020. The Guest Editors of this Special Issue are Dr. David Fernández-Llorca, Dr. Ignacio Parra-Alonso, Dr. Iván García-Daza and Dr. Noelia Parra-Alonso, all from the Computer Engineering Department at the University of Alcalá (Madrid, Spain). A total of 32 manuscripts were finally accepted between 2019 and 2020, presented by top researchers from all over the world. The reader will find a well-representative set of current research and developments related to sensors and sensing for intelligent vehicles. The topics of the published manuscripts can be grouped into seven main categories: (1) assistance systems and automatic vehicle operation, (2) vehicle positioning and localization, (3) fault diagnosis and fail-x systems, (4) perception and scene understanding, (5) smart regenerative braking systems for electric vehicles, (6) driver behavior modeling and (7) intelligent sensing. We, the Guest Editors, hope that the readers will find this book to contain interesting papers for their research, papers that they will enjoy reading as much as we have enjoyed organizing this Special Issue

History of engineering & technology --- tracking-by-detection --- multi-vehicle tracking --- Siamese network --- data association --- Markov decision process --- driving behavior --- real-time monitoring --- driver distraction --- mobile application --- portable system --- simulation test --- dynamic driving behavior --- traffic scene augmentation --- corridor model --- IMU --- vision --- classification networks --- Hough transform --- lane markings detection --- semantic segmentation --- transfer learning --- autonomous --- off-road driving --- tire-road forces estimation --- slip angle estimation --- gauge sensors --- fuzzy logic system --- load transfer estimation --- simulation results --- normalization --- lateral force empirical model --- driver monitor --- lane departure --- statistical process control --- fault detection --- sensor fault --- signal restoration --- intelligent vehicle --- autonomous vehicle --- kinematic model --- visual SLAM --- sparse direct method --- photometric calibration --- corner detection and filtering --- loop closure detection --- road friction coefficient --- tire model --- nonlinear observer --- self-aligning torque --- lateral displacement --- Lyapunov method --- automatic parking system (APS) --- end-to-end parking --- reinforcement learning --- parking slot tracking --- deceleration planning --- multi-layer perceptron --- smart regenerative braking --- electric vehicles --- vehicle speed prediction --- driver behavior modeling --- electric vehicle control --- driver characteristics online learning --- objects’ edge detection --- stixel histograms accumulate --- point cloud segmentation --- autonomous vehicles --- scene understanding --- occlusion reasoning --- road detection --- advanced driver assistance system --- trajectory prediction --- risk assessment --- collision warning --- connected vehicles --- vehicular communications --- vulnerable road users --- fail-operational systems --- fall-back strategy --- automated driving --- advanced driving assistance systems --- illumination --- shadow detection --- shadow edge --- image processing --- traffic light detection --- intelligent transportation system --- lane-changing --- merging maneuvers --- game theory --- decision-making --- intelligent vehicles --- model predictive controller --- automatic train operation --- softness factor --- fusion velocity --- online obtaining --- hardware-in-the-loop simulation --- driving assistant --- driving diagnosis --- accident risk maps --- driving safety --- intelligent driving --- virtual test environment --- millimeter wave radar --- lane-change decision --- risk perception --- mixed traffic --- minimum safe deceleration --- automated driving system (ADS) --- sensor fusion --- multi-lane detection --- particle filter --- self-driving car --- unscented Kalman filter --- vehicle model --- Monte Carlo localization --- millimeter-wave radar --- square-root cubature Kalman filter --- Sage-Husa algorithm --- target tracking --- stationary and moving object classification --- localization --- LiDAR --- GNSS --- Global Positioning System (GPS) --- monte carlo --- autonomous driving --- robot motion --- path planning --- piecewise linear approximation --- multiple-target path planning --- autonomous mobile robot --- homotopy based path planning --- LiDAR signal processing --- sensor and information fusion --- advanced driver assistance systems --- autonomous racing --- high-speed camera --- real-time systems --- LiDAR odometry --- fail-aware --- sensors --- sensing --- percepction --- object detection and tracking --- scene segmentation --- vehicle positioning --- fail-x systems --- driver behavior modelling --- automatic operation

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This book presents the results of the successful Sensors Special Issue on Intelligent Vehicles that received submissions between March 2019 and May 2020. The Guest Editors of this Special Issue are Dr. David Fernández-Llorca, Dr. Ignacio Parra-Alonso, Dr. Iván García-Daza and Dr. Noelia Parra-Alonso, all from the Computer Engineering Department at the University of Alcalá (Madrid, Spain). A total of 32 manuscripts were finally accepted between 2019 and 2020, presented by top researchers from all over the world. The reader will find a well-representative set of current research and developments related to sensors and sensing for intelligent vehicles. The topics of the published manuscripts can be grouped into seven main categories: (1) assistance systems and automatic vehicle operation, (2) vehicle positioning and localization, (3) fault diagnosis and fail-x systems, (4) perception and scene understanding, (5) smart regenerative braking systems for electric vehicles, (6) driver behavior modeling and (7) intelligent sensing. We, the Guest Editors, hope that the readers will find this book to contain interesting papers for their research, papers that they will enjoy reading as much as we have enjoyed organizing this Special Issue

History of engineering & technology --- tracking-by-detection --- multi-vehicle tracking --- Siamese network --- data association --- Markov decision process --- driving behavior --- real-time monitoring --- driver distraction --- mobile application --- portable system --- simulation test --- dynamic driving behavior --- traffic scene augmentation --- corridor model --- IMU --- vision --- classification networks --- Hough transform --- lane markings detection --- semantic segmentation --- transfer learning --- autonomous --- off-road driving --- tire-road forces estimation --- slip angle estimation --- gauge sensors --- fuzzy logic system --- load transfer estimation --- simulation results --- normalization --- lateral force empirical model --- driver monitor --- lane departure --- statistical process control --- fault detection --- sensor fault --- signal restoration --- intelligent vehicle --- autonomous vehicle --- kinematic model --- visual SLAM --- sparse direct method --- photometric calibration --- corner detection and filtering --- loop closure detection --- road friction coefficient --- tire model --- nonlinear observer --- self-aligning torque --- lateral displacement --- Lyapunov method --- automatic parking system (APS) --- end-to-end parking --- reinforcement learning --- parking slot tracking --- deceleration planning --- multi-layer perceptron --- smart regenerative braking --- electric vehicles --- vehicle speed prediction --- driver behavior modeling --- electric vehicle control --- driver characteristics online learning --- objects’ edge detection --- stixel histograms accumulate --- point cloud segmentation --- autonomous vehicles --- scene understanding --- occlusion reasoning --- road detection --- advanced driver assistance system --- trajectory prediction --- risk assessment --- collision warning --- connected vehicles --- vehicular communications --- vulnerable road users --- fail-operational systems --- fall-back strategy --- automated driving --- advanced driving assistance systems --- illumination --- shadow detection --- shadow edge --- image processing --- traffic light detection --- intelligent transportation system --- lane-changing --- merging maneuvers --- game theory --- decision-making --- intelligent vehicles --- model predictive controller --- automatic train operation --- softness factor --- fusion velocity --- online obtaining --- hardware-in-the-loop simulation --- driving assistant --- driving diagnosis --- accident risk maps --- driving safety --- intelligent driving --- virtual test environment --- millimeter wave radar --- lane-change decision --- risk perception --- mixed traffic --- minimum safe deceleration --- automated driving system (ADS) --- sensor fusion --- multi-lane detection --- particle filter --- self-driving car --- unscented Kalman filter --- vehicle model --- Monte Carlo localization --- millimeter-wave radar --- square-root cubature Kalman filter --- Sage-Husa algorithm --- target tracking --- stationary and moving object classification --- localization --- LiDAR --- GNSS --- Global Positioning System (GPS) --- monte carlo --- autonomous driving --- robot motion --- path planning --- piecewise linear approximation --- multiple-target path planning --- autonomous mobile robot --- homotopy based path planning --- LiDAR signal processing --- sensor and information fusion --- advanced driver assistance systems --- autonomous racing --- high-speed camera --- real-time systems --- LiDAR odometry --- fail-aware --- sensors --- sensing --- percepction --- object detection and tracking --- scene segmentation --- vehicle positioning --- fail-x systems --- driver behavior modelling --- automatic operation