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Wireless sensor networks, due to their various applications in many fields and limited power consumption, have attracted much attention recently. Most previous methods have focused on providing energy-saving strategies to elevate the lifetime of sensor networks. Another aggressive but different approach is to wirelessly recharge sensor nodes to increase the lifetime of the sensor networks. This book collects articles that address state-of-the-art technologies and new developments for wireless rechargeable sensor networks (WRSNs), including the latest hot topics such as charger deployment, charger scheduling, wireless energy transfer, mobile charger design, energy-harvesting technique, and energy provisioning. We believe that the accepted articles present the most up-to-date progress in algorithms and theory for robust wireless sensor networks with respect to different networking problems.

wireless rechargeable sensor networks --- multiple mobile chargers --- charge scheduling --- genetic algorithm --- sustainable networks --- Wireless Sensor Network --- Dijkstra routing algorithm --- load balance --- power consumption --- energy harvesting --- wireless sensor network --- environmental monitoring --- clustering --- energy efficiency --- network lifetime --- transmission power --- distributed networks --- fingerprinting --- localization --- ray-tracing --- wireless sensors --- hybrid method --- wireless charger deployment

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The synergy between artificial intelligence and power and energy systems is providing promising solutions to deal with the increasing complexity of the energy sector. Multi-agent systems, in particular, are widely used to simulate complex problems in the power and energy domain as they enable modeling dynamic environments and studying the interactions between the involved players. Multi-agent systems are suitable for dealing not only with problems related to the upper levels of the system, such as the transmission grid and wholesale electricity markets, but also to address challenges associated with the management of distributed generation, renewables, large-scale integration of electric vehicles, and consumption flexibility. Agent-based approaches are also being increasingly used for control and to combine simulation and emulation by enabling modeling of the details of buildings’ electrical devices, microgrids, and smart grid components. This book discusses and highlights the latest advances and trends in multi-agent energy systems simulation. The addressed application topics include the design, modeling, and simulation of electricity markets operation, the management and scheduling of energy resources, the definition of dynamic energy tariffs for consumption and electrical vehicles charging, the large-scale integration of variable renewable energy sources, and mitigation of the associated power network issues.

EV charging --- multi-agent system --- digital twin --- customer satisfaction indicator --- smart microgrid --- energy management system --- real-time optimization --- immune system algorithm --- economic dispatch --- energy consumption --- wireless sensor network --- cooperation --- collaboration --- ontology --- energy sector --- scoping review --- decision-aid --- distributed energy resources --- distribution system operator --- reactive power management --- uncertainty --- day-ahead market --- balancing market --- bilateral trading --- market design --- variable renewable energy --- agent-based simulation --- MATREM system --- congestion management --- dynamic tariff --- agent-based distribution networks --- demand response --- routing protocols --- performance parameters --- Wireless Sensor Network (WSN)

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The synergy between artificial intelligence and power and energy systems is providing promising solutions to deal with the increasing complexity of the energy sector. Multi-agent systems, in particular, are widely used to simulate complex problems in the power and energy domain as they enable modeling dynamic environments and studying the interactions between the involved players. Multi-agent systems are suitable for dealing not only with problems related to the upper levels of the system, such as the transmission grid and wholesale electricity markets, but also to address challenges associated with the management of distributed generation, renewables, large-scale integration of electric vehicles, and consumption flexibility. Agent-based approaches are also being increasingly used for control and to combine simulation and emulation by enabling modeling of the details of buildings’ electrical devices, microgrids, and smart grid components. This book discusses and highlights the latest advances and trends in multi-agent energy systems simulation. The addressed application topics include the design, modeling, and simulation of electricity markets operation, the management and scheduling of energy resources, the definition of dynamic energy tariffs for consumption and electrical vehicles charging, the large-scale integration of variable renewable energy sources, and mitigation of the associated power network issues.

History of engineering & technology --- EV charging --- multi-agent system --- digital twin --- customer satisfaction indicator --- smart microgrid --- energy management system --- real-time optimization --- immune system algorithm --- economic dispatch --- energy consumption --- wireless sensor network --- cooperation --- collaboration --- ontology --- energy sector --- scoping review --- decision-aid --- distributed energy resources --- distribution system operator --- reactive power management --- uncertainty --- day-ahead market --- balancing market --- bilateral trading --- market design --- variable renewable energy --- agent-based simulation --- MATREM system --- congestion management --- dynamic tariff --- agent-based distribution networks --- demand response --- routing protocols --- performance parameters --- Wireless Sensor Network (WSN)

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Wireless sensor networks are penetrating our daily lives, and they are starting to be deployed even in an industrial environment. The research on such industrial wireless sensor networks (IWSNs) considers more stringent requirements of robustness, reliability, and timeliness in each network layer. This Special Issue presents the recent research result on industrial wireless sensor networks. Each paper in this Special Issue has unique contributions in the advancements of industrial wireless sensor network research and we expect each paper to promote the relevant research and the deployment of IWSNs.

History of engineering & technology --- (m,k)-firm model --- adaptive real-time routing --- traffic management --- industrial wireless multimedia sensor network --- WLAN --- MAC --- full duplex --- spatial group --- OFDMA --- IEEE 802.11be --- energy-efficiency --- industrial wireless sensor networks --- reference node selection --- time synchronization --- disaster --- hazards --- cluster-tree --- remote sensing --- industrial wireless sensor network --- distributed scheduling --- weight factor --- ad-hoc network --- fairness --- ISA 100.11a --- wireless networked control systems --- link stability --- protocols for Industrial Wireless Sensor Networks (IWSN) --- IWSN standards --- IEEE 802.15.4 --- WirelessHART --- ISA100.11a --- real-time communications in IWSN --- Wireless Networked Control Systems (WNCSs) --- IWSN testbeds and applications

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Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones.

Research & information: general --- wildfire --- satellite vegetation indices --- live fuel moisture --- empirical model function --- Southern California --- chaparral ecosystem --- forest fire --- forest recovery --- satellite remote sensing --- vegetation index --- burn index --- gross primary production --- South Korea --- land subsidence --- PS-InSAR --- uneven settlement --- building construction --- Beijing urban area --- floodplain delineation --- inaccessible region --- machine learning --- flash flood --- risk --- LSSVM --- China --- Himawari-8 --- threshold-based algorithm --- remote sensing --- dryness monitoring --- soil moisture --- NIR-Red spectral space --- Landsat-8 --- MODIS --- Xinjiang province of China --- SDE --- PE --- groundwater level --- compressible sediment layer --- tropical cyclone formation --- WindSat --- disaster monitoring --- wireless sensor network --- debris flow --- anomaly detection --- deep learning --- accelerometer sensor --- total precipitable water --- Himawari-8 AHI --- random forest --- deep neural network --- XGBoost