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The future of electric vehicles relies nearly entirely on the design, monitoring, and control of the vehicle battery and its associated systems. Along with an initial optimal design of the cell/pack-level structure, the runtime performance of the battery needs to be continuously monitored and optimized for a safe and reliable operation and prolonged life. Improved charging techniques need to be developed to protect and preserve the battery. The scope of this Special Issue is to address all the above issues by promoting innovative design concepts, modeling and state estimation techniques, charging/discharging management, and hybridization with other storage components.

state of charge (SOC) --- joint estimation --- lithium-ion battery --- variational Bayesian approximation --- dual extended Kalman filter (DEKF) --- measurement statistic uncertainty --- electric vehicles --- renewable energy sources --- microgrid --- economic dispatching --- capacity allocation --- cooperative optimization --- SOC --- second-order RC model --- model parameter optimization --- AUKF --- small-signal modeling --- battery energy storage system --- battery management system --- control --- stability --- dynamic response --- wireless power --- state-of-charge --- electric vehicle --- LiFePO4 batteries --- state of charge (SoC) --- Butler–Volmer equation --- Arrhenius --- Peukert --- coulomb efficiency --- back propagation neural network (BPNN) --- torque and battery distribution --- particle swarm optimization --- air-cooled BTMS --- compact lithium ion battery module --- ANN --- battery electric vehicles --- battery management --- hybrid energy storage --- n/a --- Butler-Volmer equation

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In this Special Issue on symmetry, we mainly discuss the application of symmetry in various structural health monitoring. For example, considering the health monitoring of a known structure, by obtaining the static or dynamic response of the structure, using different signal processing methods, including some advanced filtering methods, to remove the influence of environmental noise, and extract structural feature parameters to determine the safety of the structure. These damage diagnosis methods can also be effectively applied to various types of infrastructure and mechanical equipment. For this reason, the vibration control of various structures and the knowledge of random structure dynamics should be considered, which will promote the rapid development of the structural health monitoring. Among them, signal extraction and evaluation methods are also worthy of study. The improvement of signal acquisition instruments and acquisition methods improves the accuracy of data. A good evaluation method will help to correctly understand the performance with different types of infrastructure and mechanical equipment.

Technology: general issues --- History of engineering & technology --- real-time hybrid simulation --- H∞ control --- time delay --- mixed sensitivity --- structural health monitoring --- deep learning --- data anomaly detection --- convolutional neural network --- time–frequency extraction --- micro inertial measurement unit (MIMU) --- variational mode decomposition (VMD) --- Hilbert–Huang transform (HHT) --- frequency-domain integration approach (FDIA) --- torsion angle calculation --- offshore oil platform --- self-anchored suspension bridge --- cable clamp --- slippage --- force analysis --- high formwork --- ARMA --- BPNN --- stress trend prediction --- crack detection --- improved YOLOv4 --- concrete surface --- substructure shake table testing --- integration algorithm --- finite element method --- damper --- digital twin --- prestressed steel structure --- construction process --- safety assessment --- intelligent construction --- structural health monitoring (SHM) --- vibration --- frequency domain --- time domain --- time-frequency domain --- technical codes --- multiple square loops (MSL)-string --- seismic excitation --- dynamic response --- seismic pulse --- near and far field --- three-dimensional laser scanning --- surface flatness of initial support of tunnel --- curved surface fitting --- flatness calculation datum --- curvedcontinuous girder bridge --- collision response --- seismic mitigation --- pounding mitigation and unseating prevention --- heavy-duty vehicle --- road --- coupling model --- terrestrial laser scanning --- RGB --- genetic algorithm --- artificial neutral network --- real-time hybrid simulation --- H∞ control --- time delay --- mixed sensitivity --- structural health monitoring --- deep learning --- data anomaly detection --- convolutional neural network --- time–frequency extraction --- micro inertial measurement unit (MIMU) --- variational mode decomposition (VMD) --- Hilbert–Huang transform (HHT) --- frequency-domain integration approach (FDIA) --- torsion angle calculation --- offshore oil platform --- self-anchored suspension bridge --- cable clamp --- slippage --- force analysis --- high formwork --- ARMA --- BPNN --- stress trend prediction --- crack detection --- improved YOLOv4 --- concrete surface --- substructure shake table testing --- integration algorithm --- finite element method --- damper --- digital twin --- prestressed steel structure --- construction process --- safety assessment --- intelligent construction --- structural health monitoring (SHM) --- vibration --- frequency domain --- time domain --- time-frequency domain --- technical codes --- multiple square loops (MSL)-string --- seismic excitation --- dynamic response --- seismic pulse --- near and far field --- three-dimensional laser scanning --- surface flatness of initial support of tunnel --- curved surface fitting --- flatness calculation datum --- curvedcontinuous girder bridge --- collision response --- seismic mitigation --- pounding mitigation and unseating prevention --- heavy-duty vehicle --- road --- coupling model --- terrestrial laser scanning --- RGB --- genetic algorithm --- artificial neutral network

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Sensors are the eyes or/and ears of an intelligent system, such as UAV, AGV and robots. With the development of material, signal processing, and multidisciplinary interactions, more and more smart sensors are proposed and fabricated under increasing demands for homes, the industry, and military fields. Networks of sensors will be able to enhance the ability to obtain huge amounts of information (big data) and improve precision, which also mirrors the developmental tendency of modern sensors. Moreover, artificial intelligence is a novel impetus for sensors and networks, which gets sensors to learn and think and feed more efficient results back. This book includes new research results from academia and industry, on the subject of “Smart Sensors and Networks”, especially sensing technologies utilizing Artificial Intelligence. The topics include: smart sensors biosensors sensor network sensor data fusion artificial intelligence deep learning mechatronics devices for sensors applications of sensors for robotics and mechatronics devices

History of engineering & technology --- microelectromechanical systems --- inertial measurement unit --- long short term memory recurrent neural networks --- artificial intelligence --- deep learning --- CNN --- LSTM --- CO2 welding --- molten pool --- online monitoring --- mechanical sensor --- self-adaptiveness --- ankle-foot exoskeleton --- walking assistance --- visual tracking --- correlation filter --- color histogram --- adaptive hedge algorithm --- scenario generation --- autonomous vehicle --- smart sensor and device --- wireless sensor networks --- task assignment --- distributed --- reliable --- energy-efficient --- audification --- sensor --- visualization --- speech to text --- text to speech --- HF-OTH radar --- AIS --- radar tracking --- data fusion --- fuzzy functional dependencies --- maritime surveillance --- surgical robot end-effector --- clamping force estimation --- joint torque disturbance observer --- PSO-BPNN --- cable tension measurement --- queue length --- roadside sensor --- vehicle detection --- adverse weather --- roadside LiDAR --- data processing --- air pollution --- atmospheric data --- IoT --- machine learning --- RNN --- Sensors --- smart cities --- traffic flow --- traffic forecasting --- wireless sensor network --- fruit condition monitoring --- artificial neural network --- ethylene gas --- banana ripening --- unidimensional ACGAN --- signal recognition --- data augmentation --- link establishment behaviors --- DenseNet --- short-wave radio station --- landing gear --- adaptive landing --- vehicle classification --- FBG --- smart sensors --- outlier detection --- local outlier factor --- data streams --- air quality monitoring --- evacuation path --- multi-story multi-exit building --- temperature sensors --- multi-time-slots planning --- optimization --- microelectromechanical systems --- inertial measurement unit --- long short term memory recurrent neural networks --- artificial intelligence --- deep learning --- CNN --- LSTM --- CO2 welding --- molten pool --- online monitoring --- mechanical sensor --- self-adaptiveness --- ankle-foot exoskeleton --- walking assistance --- visual tracking --- correlation filter --- color histogram --- adaptive hedge algorithm --- scenario generation --- autonomous vehicle --- smart sensor and device --- wireless sensor networks --- task assignment --- distributed --- reliable --- energy-efficient --- audification --- sensor --- visualization --- speech to text --- text to speech --- HF-OTH radar --- AIS --- radar tracking --- data fusion --- fuzzy functional dependencies --- maritime surveillance --- surgical robot end-effector --- clamping force estimation --- joint torque disturbance observer --- PSO-BPNN --- cable tension measurement --- queue length --- roadside sensor --- vehicle detection --- adverse weather --- roadside LiDAR --- data processing --- air pollution --- atmospheric data --- IoT --- machine learning --- RNN --- Sensors --- smart cities --- traffic flow --- traffic forecasting --- wireless sensor network --- fruit condition monitoring --- artificial neural network --- ethylene gas --- banana ripening --- unidimensional ACGAN --- signal recognition --- data augmentation --- link establishment behaviors --- DenseNet --- short-wave radio station --- landing gear --- adaptive landing --- vehicle classification --- FBG --- smart sensors --- outlier detection --- local outlier factor --- data streams --- air quality monitoring --- evacuation path --- multi-story multi-exit building --- temperature sensors --- multi-time-slots planning --- optimization

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In this Special Issue on symmetry, we mainly discuss the application of symmetry in various structural health monitoring. For example, considering the health monitoring of a known structure, by obtaining the static or dynamic response of the structure, using different signal processing methods, including some advanced filtering methods, to remove the influence of environmental noise, and extract structural feature parameters to determine the safety of the structure. These damage diagnosis methods can also be effectively applied to various types of infrastructure and mechanical equipment. For this reason, the vibration control of various structures and the knowledge of random structure dynamics should be considered, which will promote the rapid development of the structural health monitoring. Among them, signal extraction and evaluation methods are also worthy of study. The improvement of signal acquisition instruments and acquisition methods improves the accuracy of data. A good evaluation method will help to correctly understand the performance with different types of infrastructure and mechanical equipment.

Technology: general issues --- History of engineering & technology --- real-time hybrid simulation --- H∞ control --- time delay --- mixed sensitivity --- structural health monitoring --- deep learning --- data anomaly detection --- convolutional neural network --- time–frequency extraction --- micro inertial measurement unit (MIMU) --- variational mode decomposition (VMD) --- Hilbert–Huang transform (HHT) --- frequency-domain integration approach (FDIA) --- torsion angle calculation --- offshore oil platform --- self-anchored suspension bridge --- cable clamp --- slippage --- force analysis --- high formwork --- ARMA --- BPNN --- stress trend prediction --- crack detection --- improved YOLOv4 --- concrete surface --- substructure shake table testing --- integration algorithm --- finite element method --- damper --- digital twin --- prestressed steel structure --- construction process --- safety assessment --- intelligent construction --- structural health monitoring (SHM) --- vibration --- frequency domain --- time domain --- time-frequency domain --- technical codes --- multiple square loops (MSL)-string --- seismic excitation --- dynamic response --- seismic pulse --- near and far field --- three-dimensional laser scanning --- surface flatness of initial support of tunnel --- curved surface fitting --- flatness calculation datum --- curvedcontinuous girder bridge --- collision response --- seismic mitigation --- pounding mitigation and unseating prevention --- heavy-duty vehicle --- road --- coupling model --- terrestrial laser scanning --- RGB --- genetic algorithm --- artificial neutral network

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Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. Artificial neural networks (ANNs) are one of the most popular tools of this kind. They are widely used in solving various classification and prediction tasks, for some time also in the broadly defined field of agriculture. They can form part of precision farming and decision support systems. Artificial neural networks can replace the classical methods of modelling many issues, and are one of the main alternatives to classical mathematical models. The spectrum of applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible.

artificial neural network (ANN) --- Grain weevil identification --- neural modelling classification --- winter wheat --- grain --- artificial neural network --- ferulic acid --- deoxynivalenol --- nivalenol --- MLP network --- sensitivity analysis --- precision agriculture --- machine learning --- similarity --- metric --- memory --- deep learning --- plant growth --- dynamic response --- root zone temperature --- dynamic model --- NARX neural networks --- hydroponics --- vegetation indices --- UAV --- neural network --- corn plant density --- corn canopy cover --- yield prediction --- CLQ --- GA-BPNN --- GPP-driven spectral model --- rice phenology --- EBK --- correlation filter --- crop yield prediction --- hybrid feature extraction --- recursive feature elimination wrapper --- artificial neural networks --- big data --- classification --- high-throughput phenotyping --- modeling --- predicting --- time series forecasting --- soybean --- food production --- paddy rice mapping --- dynamic time warping --- LSTM --- weakly supervised learning --- cropland mapping --- apparent soil electrical conductivity (ECa) --- magnetic susceptibility (MS) --- EM38 --- neural networks --- Phoenix dactylifera L. --- Medjool dates --- image classification --- convolutional neural networks --- transfer learning --- average degree of coverage --- coverage unevenness coefficient --- optimization --- high-resolution imagery --- oil palm tree --- CNN --- Faster-RCNN --- image identification --- agroecology --- weeds --- yield gap --- environment --- health --- crop models --- soil and plant nutrition --- automated harvesting --- model application for sustainable agriculture --- remote sensing for agriculture --- decision supporting systems --- neural image analysis