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Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

optical sensor --- spectral analysis --- response surface sampling --- sensor evaluation --- electromagnetic induction --- multivariate water quality parameters --- mandarin orange --- crop inspection platform --- SPA-MLR --- object tracking --- feature selection --- simultaneous measurement --- diseases --- genetic algorithms --- processing of sensed data --- electrochemical sensors --- thermal image --- ECa-directed soil sampling --- handheld --- recognition patterns --- salt concentration --- clover-grass --- bovine embedded hardware --- weed control --- soil --- field crops --- vineyard --- connected dominating set --- water depth sensors --- SS-OCT --- wheat --- striped stem-borer --- silage --- geostatistics --- detection --- NIR hyperspectral imaging --- electronic nose --- machine learning --- virtual organizations of agents --- packing density --- data validation and calibration --- dataset --- Wi-SUN --- temperature sensors --- geoinformatics --- gas sensor --- X-ray fluorescence spectroscopy --- vegetable oil --- photograph-grid method --- Vitis vinifera --- WSN distribution algorithms --- laser-induced breakdown spectroscopy --- irrigation --- quality assessment --- energy efficiency --- wireless sensor network (WSN) --- geo-information --- Fusarium --- texture features --- weeds --- discrimination --- big data --- soil moisture sensors --- meat spoilage --- land cover --- stereo imaging --- near infrared sensors --- biological sensing --- compound sensor --- pest management --- moisture --- plant localization --- heavy metal contamination --- artificial neural networks --- spectral pre-processing --- moisture content --- apparent soil electrical conductivity --- data fusion --- semi-arid regions --- smart irrigation --- back propagation model --- wireless sensor network --- energy balance --- light-beam --- fluorescent measurement --- agriculture --- precision agriculture --- deep learning --- spectroscopy --- hulled barely --- dielectric probe --- RPAS --- water supply network --- rice leaves --- mobile app --- gradient boosted machines --- hyperspectral camera --- one-class --- nitrogen --- LiDAR --- total carbon --- chemometrics analysis --- rice --- agricultural land --- on-line vis-NIR measurement --- CARS --- obstacle detection --- stratification --- neural networks --- regression estimator --- Kinect --- proximity sensing --- distributed systems --- pest --- noninvasive detection --- texture feature --- soil mapping --- classification --- soil salinity --- visible and near-infrared reflectance spectroscopy --- germination --- computer vision --- hyperspectral imaging --- diffusion --- dielectric dispersion --- UAS --- random forests --- case studies --- total nitrogen --- thermal imaging --- cameras --- dry matter composition --- near-infrared --- salt tolerance --- deep convolutional neural networks --- soil type classification --- water management --- preprocessing methods --- wireless sensor networks (WSN) --- remote sensing image classification --- precision plant protection --- radar --- spatial variability --- GF-1 satellite --- plant disease --- naked barley --- leaf area index --- CIE-Lab --- change of support --- radiative transfer model --- 3D reconstruction --- plant phenotyping --- vine --- near infrared --- vegetation indices --- remote sensing --- greenhouse --- time-series data --- scattering --- sensor --- crop area --- speckle --- spatial data --- grapevine breeding --- wide field view --- partial least squares-discriminant analysis --- spiking --- area frame sampling --- chromium content --- machine-learning --- RGB-D sensor --- pest scouting --- PLS --- Capsicum annuum --- spatial-temporal model --- drying temperature --- boron tolerance --- ambient intelligence --- laser wavelength --- fuzzy logic --- dynamic weight --- landslide --- management zones --- real-time processing --- event detection --- crop monitoring --- apple shelf-life --- rice field monitoring --- wireless sensor --- birth sensor --- proximal sensor

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The editors of this Special Issue titled “Intelligent Control in Energy Systems” have attempted to create a book containing original technical articles addressing various elements of intelligent control in energy systems. In response to our call for papers, we received 60 submissions. Of those submissions, 27 were published and 33 were rejected. In this book, we offer the 27 accepted technical articles as well as one editorial. Authors from 15 countries (China, Netherlands, Spain, Tunisia, United Sates of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and the Czech Republic) elaborate on several aspects of intelligent control in energy systems. The book covers a broad range of topics including fuzzy PID in automotive fuel cell and MPPT tracking, neural networks for fuel cell control and dynamic optimization of energy management, adaptive control on power systems, hierarchical Petri Nets in microgrid management, model predictive control for electric vehicle battery and frequency regulation in HVAC systems, deep learning for power consumption forecasting, decision trees for wind systems, risk analysis for demand side management, finite state automata for HVAC control, robust ?-synthesis for microgrids, and neuro-fuzzy systems in energy storage.

energy management system --- artificial neural network --- control architecture --- intelligent buildings --- sensitivity analysis --- neural networks --- active balance --- photovoltaic system --- fast frequency response --- artificial intelligence --- MPPT operation --- model uncertainty --- load frequency control --- decision tree --- multi-agent control --- hybrid power plant --- Fault Ride Through Capability --- optimization --- small scale compressed air energy storage (SS-CAES) --- smart micro-grid --- current distortion --- hybrid electric vehicle --- parameter estimation --- railway --- ANFIS --- solar monitoring system --- urban microgrids --- phase-load balancing --- model reduction --- high-speed railway --- energy internet --- coordination of reserves --- differential evolution --- photovoltaic array --- ancillary service --- adjacent areas --- instantaneous optimization minimum power loss --- model predictive control --- HVAC systems --- sliding mode control --- MPPT: maximum power point tracking --- power oscillations --- thyristor --- interaction minimization --- occupancy model --- fuzzy logic controller --- power transformer winding --- RLS --- integrated energy systems --- vibration characteristics --- battery safety --- error estimation --- error compensation --- static friction --- convolutional neural network --- forecasting --- continuous voltage control --- medium voltage --- bridgeless SEPIC PFC converter --- building climate control --- PEM fuel cell --- proton exchange membrane fuel cell --- compound structured permanent-magnet motor --- occupancy-based control --- four phases interleaved boost converter --- long short term memory --- line switching --- lithium-ion battery pack --- back propagation (BP) neural network --- doubly-fed induction generator --- double forgetting factors --- current controller design --- repetitive controller --- exhaust gas recirculation (EGR) valve system --- neural network controller --- step-up boost converter --- internal short circuit resistance --- electric power consumption --- electric vehicle --- multiphysical field analysis --- energy efficiency --- multi-energy complementary --- system identification --- ?-synthesis --- network sensitivity --- intelligent control --- ?-class function --- frequency support --- multi-step forecasting --- frequency containment reserve --- orthogonal least square --- rule-based control --- industrial process --- hierarchical Petri nets --- wind integrated power system --- probabilistic power flow --- voltage controlling --- adaptive backstepping --- AC-DC converters --- line loss --- demand side management --- energy systems --- short-circuit experiment --- winding-fault characteristics --- neutral section --- stochastic power system operating point drift --- neural network algorithm --- operation limit violations --- fractional order fuzzy PID controller --- preventive control --- AC static switch --- battery packs --- model-based fault detection --- automotive application --- nonlinear power systems --- adaptive damping control --- pilot point --- energy management --- position control --- frequency control dead band --- fuzzy --- voltage violations --- distribution network planning --- frequency regulation --- energy management strategy --- multiple-point control --- electric meter --- polynomial expansion --- commercial/residential buildings --- system modelling --- three-stage --- soft internal short circuit --- demand response