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As the century begins, natural resources are under increasing pressure, threatening public health and development. As a result, the balance between man and nature has been disrupted, with climatic changes whose effects are starting to be irreversible. Due to the relationship between the quality of the indoor built environment and its energy demand, thermal comfort issues are still relevant in the disciplinary debate. This is also because the indoor environment has a potential impact on occupants' health and productivity, affecting their physical and psychological conditions. To achieve a sustainable compromise in terms of comfort and energy requirements, several challenging questions must be answered with regard to design, technical, engineering, psychological, and physiological issues and, finally, potential interactions with other IEQ issues that require a holistic way to conceive the building envelope design. This Special Issue collected original research and review articles on innovative designs, systems, and/or control domains that can enhance thermal comfort, work productivity, and wellbeing in a built environment, along with works considering the integration of human factors in buildings’ energy performance.

History of engineering & technology --- smart broiler chamber --- ventilation system --- wind velocity --- age of air --- computational fluid dynamics --- simulation analysis --- user awareness --- energy consumption --- individual metering --- feedback strategies --- N-ZEB --- IoT --- Trombe wall --- thermal comfort --- passive heating systems --- heat accumulation --- thermal comfort models --- thermal comfort assessment --- Fanger’s models --- moderate environments --- sport facilities --- desert cooler --- evaporative cooling --- indoor air quality --- liquid desiccant --- effectiveness model --- moisture removal --- PMV --- comfort indices --- software --- app --- building simulation --- health and comfort --- evaluation indicators --- work environments --- indoor environmental quality --- indoor comfort --- human health --- clothing thermal insulation --- thermoregulation model --- Tanabe model --- infrared camera --- indoor air quality (IAQ) --- hybrid ventilation --- demand controlled ventilation (DCV) --- internet of things (IoT) --- soft-sensor --- convolution neural networks --- draught --- cooling period --- open office --- thermal sensation --- biological structure and composition --- tissue temperature --- bioheat model --- MRI analysis --- sensitivity analysis

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The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text processing, medical applications, and IoT (Internet of Things). The probability of a successful outcome from a neural network is linked to selection of an appropriate network architecture and training algorithm. Accordingly, much of the recent research on neural networks has been devoted to the study and proposal of novel architectures, including solutions tailored to specific problems. This book gives significant contributions to the above-mentioned fields by merging theoretical aspects and relevant applications.

facial image analysis --- facial nerve paralysis --- deep convolutional neural networks --- image classification --- Chinese text classification --- long short-term memory --- convolutional neural network --- Arabic named entity recognition --- bidirectional recurrent neural network --- GRU --- LSTM --- natural language processing --- word embedding --- CNN --- object detection network --- attention mechanism --- feature fusion --- LSTM-CRF model --- elements recognition --- linguistic features --- POS syntactic rules --- action recognition --- fused features --- 3D convolution neural network --- motion map --- long short-term-memory --- tooth-marked tongue --- gradient-weighted class activation maps --- ship identification --- fully convolutional network --- embedded deep learning --- scalability --- gesture recognition --- human computer interaction --- alternative fusion neural network --- deep learning --- sentiment attention mechanism --- bidirectional gated recurrent unit --- Internet of Things --- convolutional neural networks --- graph partitioning --- distributed systems --- resource-efficient inference --- pedestrian attribute recognition --- graph convolutional network --- multi-label learning --- autoencoders --- long-short-term memory networks --- convolution neural Networks --- object recognition --- sentiment analysis --- text recognition --- IoT (Internet of Thing) systems --- medical applications

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As the century begins, natural resources are under increasing pressure, threatening public health and development. As a result, the balance between man and nature has been disrupted, with climatic changes whose effects are starting to be irreversible. Due to the relationship between the quality of the indoor built environment and its energy demand, thermal comfort issues are still relevant in the disciplinary debate. This is also because the indoor environment has a potential impact on occupants' health and productivity, affecting their physical and psychological conditions. To achieve a sustainable compromise in terms of comfort and energy requirements, several challenging questions must be answered with regard to design, technical, engineering, psychological, and physiological issues and, finally, potential interactions with other IEQ issues that require a holistic way to conceive the building envelope design. This Special Issue collected original research and review articles on innovative designs, systems, and/or control domains that can enhance thermal comfort, work productivity, and wellbeing in a built environment, along with works considering the integration of human factors in buildings’ energy performance.

History of engineering & technology --- smart broiler chamber --- ventilation system --- wind velocity --- age of air --- computational fluid dynamics --- simulation analysis --- user awareness --- energy consumption --- individual metering --- feedback strategies --- N-ZEB --- IoT --- Trombe wall --- thermal comfort --- passive heating systems --- heat accumulation --- thermal comfort models --- thermal comfort assessment --- Fanger’s models --- moderate environments --- sport facilities --- desert cooler --- evaporative cooling --- indoor air quality --- liquid desiccant --- effectiveness model --- moisture removal --- PMV --- comfort indices --- software --- app --- building simulation --- health and comfort --- evaluation indicators --- work environments --- indoor environmental quality --- indoor comfort --- human health --- clothing thermal insulation --- thermoregulation model --- Tanabe model --- infrared camera --- indoor air quality (IAQ) --- hybrid ventilation --- demand controlled ventilation (DCV) --- internet of things (IoT) --- soft-sensor --- convolution neural networks --- draught --- cooling period --- open office --- thermal sensation --- biological structure and composition --- tissue temperature --- bioheat model --- MRI analysis --- sensitivity analysis

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Recent years have seen a vast development in various methodologies for object detection and feature extraction and recognition, both in theory and in practice. When processing images, videos, or other types of multimedia, one needs efficient solutions to perform fast and reliable processing. Computational intelligence is used for medical screening where the detection of disease symptoms is carried out, in prevention monitoring to detect suspicious behavior, in agriculture systems to help with growing plants and animal breeding, in transportation systems for the control of incoming and outgoing transportation, for unmanned vehicles to detect obstacles and avoid collisions, in optics and materials for the detection of surface damage, etc. In many cases, we use developed techniques which help us to recognize some special features. In the context of this innovative research on computational intelligence, the Special Issue “Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments” present an excellent opportunity for the dissemination of recent results and achievements for further innovations and development. It is my pleasure to present this collection of excellent contributions to the research community. - Prof. Marcin Woźniak, Silesian University of Technology, Poland –

Traffic sign detection and tracking (TSDR) --- advanced driver assistance system (ADAS) --- computer vision --- 3D convolutional neural networks --- machine learning --- CT brain --- brain hemorrhage --- visual inspection --- one-class classifier --- grow-when-required neural network --- evolving connectionist systems --- automatic design --- bio-inspired techniques --- artificial bee colony --- image analysis --- feature extraction --- ship classification --- marine systems --- citrus --- pests and diseases identification --- convolutional neural network --- parameter efficiency --- vehicle detection --- YOLOv2 --- focal loss --- anchor box --- multi-scale --- deep learning --- neural network --- generative adversarial network --- synthetic images --- tool wear monitoring --- superalloy tool --- image recognition --- object detection --- UAV imagery --- vehicular traffic flow detection --- vehicular traffic flow classification --- vehicular traffic congestion --- video classification --- benchmark --- semantic segmentation --- atrous convolution --- spatial pooling --- ship radiated noise --- underwater acoustics --- surface electromyography (sEMG) --- convolution neural networks (CNNs) --- hand gesture recognition --- fabric defect --- mixed kernels --- cross-scale --- cascaded center-ness --- deformable localization --- continuous casting --- surface defects --- 3D imaging --- defect detection --- object detector --- object tracking --- activity measure --- Yolo --- deep sort --- Hungarian algorithm --- optical flows --- spatiotemporal interest points --- sports scene --- CT images --- convolutional neural networks --- hepatic cancer --- visual question answering --- three-dimensional (3D) vision --- reinforcement learning --- human–robot interaction --- few shot learning --- SVM --- CNN --- cascade classifier --- video surveillance --- RFI --- artefacts --- InSAR --- image processing --- pixel convolution --- thresholding --- nearest neighbor filtering --- data acquisition --- augmented reality --- pose estimation --- industrial environments --- information retriever sensor --- multi-hop reasoning --- evidence chains --- complex search request --- high-speed trains --- hunting --- non-stationary --- feature fusion --- multi-sensor fusion --- unmanned aerial vehicles --- drone detection --- UAV detection --- visual detection --- n/a --- human-robot interaction

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Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publishing the results, among others.

Research & information: general --- Geography --- geographic information system (GIS) --- pocket beaches --- coastal management --- Interreg --- climate change --- remote sensing --- drone --- Sicily --- Malta --- Gozo --- Comino --- systematic literature review --- anomaly intrusion detection --- deep learning --- IoT --- resource constraint --- IDS --- evapotranspiration --- penman-monteith equation --- artificial neural network --- canopy conductance --- Ziz basin --- water quality --- satellite image analysis --- modeling approach --- nitrate --- dissolved oxygen --- chlorophyll a --- time series analysis --- environmental monitoring --- water extraction --- modified normalized difference water index (MNDWI) --- machine learning algorithm --- hyperspectral --- proximal sensing --- panicle initiation --- normalized difference vegetation index (NDVI) --- green ring --- internode-elongation --- Sentinel 1 and 2 --- Copernicus Sentinels --- crop classification --- food security --- agricultural monitoring --- data analysis --- SAR --- random forest --- 3D bale wrapping method --- equal bale dimensions --- mathematical model --- minimal film consumption --- optimal bale dimensions --- round bales --- Sentinel-2 --- SVM --- RF --- Boufakrane River watershed --- irrigation requirements --- water resources --- sustainable land use --- agriculture --- invasive plants --- precision agriculture --- rice farming --- site-specific weed management --- nitrogen prediction --- 1D convolution neural networks --- cucumber --- crop yield improvement --- mango leaf --- CCA --- vein pattern --- leaf disease --- cubic SVM --- chlorophyll-a concentration --- transfer learning --- overfitting --- data augmentation --- guava disease --- plant disease detection --- crops diseases --- entropy --- features fusion --- machine learning --- object-based classification --- density estimation --- histogram --- land use --- crop fields --- soil tillage --- data fusion --- multispectral --- sensor --- probe --- temperature profile --- forest roads --- simulation --- autonomous robots --- smart agriculture --- environmental protection --- photogrammetry --- path planning --- internet of things --- modeling --- convolutional neural networks --- machine vision --- computer vision --- modular robot --- selective spraying --- vision-based crop and weed detection --- Faster R-CNN --- YOLOv5 --- band selection --- CNN --- NDVI --- hyperspectral imaging --- crops --- urban flood --- Sentinel-1a --- Synthetic Aperture Radar (SAR) --- 3D Convolutional Neural Network --- multi-temporal data --- land use classification --- GIS --- Coatzacoalcos --- algorithms --- clustering --- pest control --- site-specific --- virtual pests --- rice plant --- weed --- hyperspectral imagery --- sustainable agriculture --- green technologies --- Internet of Things --- natural resources --- sustainable environment --- IoT ecosystem --- hyperspectral remoting sensing --- crop mapping --- image classification --- deep transfer learning --- hyperparameter optimization --- metaheuristic --- soil attribute --- ordinary Kriging --- rational sampling numbers --- spatial heterogeneity --- sampling --- soil pH --- spatial variation --- ordinary kriging --- Land Use/Land Cover --- LISS-III --- Landsat --- Vision Transformer --- Bidirectional long-short term memory --- Google Earth Engine --- Explainable Artificial Intelligence