Sensor Data Fusion in Multi-Sensor Weigh-In-Motion Systems [PDF]
Sensors, 2020 In this paper, we present the results of a comparison of two estimators of the gross vehicle weight (GVW) and the static load of individual axles of vehicles.
Janusz Gajda +2 more
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Sensor Data Fusion Analysis for Broad Applications [PDF]
SensorsSensor data fusion analysis plays a pivotal role in a variety of fields by integrating data from multiple sensors to produce more accurate, reliable, and comprehensive information than that achieved by individual sensors alone [...]
Natividad Duro
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Machine Learning-Based Sensor Data Fusion for Animal Monitoring: Scoping Review. [PDF]
Sensors (Basel), 2023 The development of technology, such as the Internet of Things and artificial intelligence, has significantly advanced many fields of study. Animal research is no exception, as these technologies have enabled data collection through various sensing ...
Aguilar-Lazcano CA +4 more
europepmc +2 more sources
UAV-based multi-sensor data fusion and machine learning algorithm for yield prediction in wheat. [PDF]
Precis Agric, 2023 Early prediction of grain yield helps scientists to make better breeding decisions for wheat. Use of machine learning (ML) methods for fusion of unmanned aerial vehicle (UAV)-based multi-sensor data can improve the prediction accuracy of crop yield.
Fei S +8 more
europepmc +2 more sources
Modeling and Fault Detection of Brushless Direct Current Motor by Deep Learning Sensor Data Fusion. [PDF]
Sensors (Basel), 2022 Only with new sensor concepts in a network, which go far beyond what the current state-of-the-art can offer, can current and future requirements for flexibility, safety, and security be met.
Suawa P +4 more
europepmc +2 more sources
Sensor Data Fusion for a Mobile Robot Using Neural Networks. [PDF]
Sensors (Basel), 2021 Mobile robots must be capable to obtain an accurate map of their surroundings to move within it. To detect different materials that might be undetectable to one sensor but not others it is necessary to construct at least a two-sensor fusion scheme.
Barreto-Cubero AJ +4 more
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Rolling Bearing Fault Diagnosis Using Multi-Sensor Data Fusion Based on 1D-CNN Model. [PDF]
Entropy (Basel), 2022 To satisfy the requirements of the end-to-end fault diagnosis of rolling bearings, a hybrid model, based on optimal SWD and 1D-CNN, with the layer of multi-sensor data fusion, is proposed in this paper.
Wang H, Sun W, He L, Zhou J.
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Sensor network data fusion methods
Mokslas: Lietuvos Ateitis, 2010 Sensor network data fusion is widely used in warfare, in areas such as automatic target recognition, battlefield surveillance, automatic vehicle control, multiple target surveillance, etc. Non-military use example are: medical equipment status monitoring,
Martynas Vervečka
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Multi-Sensor Data Fusion Method Based on Self-Attention Mechanism
Applied Sciences, 2023 In 3D reconstruction tasks, single-sensor data fusion based on deep learning is limited by the integrity and accuracy of the data, which reduces the accuracy and reliability of the fusion results. To address this issue, this study proposes a multi-sensor
Xuezhu Lin +5 more
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On the Accuracy of Fault Diagnosis for Rolling Element Bearings Using Improved DFA and Multi-Sensor Data Fusion Method. [PDF]
Sensors (Basel), 2020 Rolling element bearings are widely employed in almost every rotating machine. The health status of bearings plays an important role in the reliability of rotating machines. This paper deals with the principle and application of an effective multi-sensor
Song Q, Zhao S, Wang M.
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