SAFETYLIT WEEKLY UPDATE

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Sensors (Basel)

Journal Volume: 23
Journal Issue: 12
Journal Year: 2023
Articles in SafetyLit: 20

360° map establishment and real-time simultaneous localization and mapping based on equirectangular projection for autonomous driving vehicles

Acoustic roughness measurement of railway tracks: running surface detection and compensation of lateral movements for optical measurements on a train

Automated road defect and anomaly detection for traffic safety: a systematic review

DDD TinyML: a TinyML-based driver drowsiness detection model using deep learning

Development of DMPS-EMAT for long-distance monitoring of broken rail

DrunkChain: blockchain-based IoT system for preventing drunk driving-related traffic accidents

Evaluation of roadside LiDAR-based and vision-based multi-model all-traffic trajectory data

Fall recognition based on an IMU wearable device and fall verification through a smart speaker and the IoT

Forest fire smoke detection based on deep learning approaches and unmanned aerial vehicle images

Fusion object detection and action recognition to predict violent action

Lane detection algorithm in curves based on multi-sensor fusion

Multi-task learning radar transformer (MLRT): a personal identification and fall detection network based on IR-UWB radar

Performance improvement during attitude motion of a vehicle using aerodynamic-surface-based anti-jerk predictive controller

Real-time vehicle detection from UAV aerial images based on improved YOLOv5

Recent progress in lithium-ion battery safety monitoring based on fiber Bragg grating sensors

Satellite video moving vehicle detection and tracking based on spatiotemporal characteristics

Sensor-based classification of primary and secondary car driver activities using convolutional neural networks

Trip-related fall risk prediction based on gait pattern in healthy older adults: a machine-learning approach

Vibrotactile alerting to prevent accidents in highway construction work zones: an exploratory study

YOLO-GW: quickly and accurately detecting pedestrians in a foggy traffic environment