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Create and program Internet of Things projects using the Espressif ESP32. Key Features Getting to know the all new powerful EPS32 boards and build interesting Internet of Things projects Configure your ESP32 to the cloud technologies and explore the networkable modules that will be utilised in your IoT projects A step-by-step guide that teaches you the basic to advanced IoT concepts with ESP32 Book Description ESP32 is a low-cost MCU with integrated Wi-Fi and BLE. Various modules and development boards-based on ESP32 are available for building IoT applications easily. Wi-Fi and BLE are a common network stack in the Internet of Things application. These network modules can leverage your business and projects needs for cost-effective benefits. This book will serve as a fundamental guide for developing an ESP32 program. We will start with GPIO programming involving some sensor devices. Then we will study ESP32 development by building a number of IoT projects, such as weather stations, sensor loggers, smart homes, Wi-Fi cams and Wi-Fi wardriving. Lastly, we will enable ESP32 boards to execute interactions with mobile applications and cloud servers such as AWS. By the end of this book, you will be up and running with various IoT project-based ESP32 chip. What you will learn Understand how to build a sensor monitoring logger Create a weather station to sense temperature and humidity using ESP32 Build your own W-iFi wardriving with ESP32. Use BLE to make interactions between ESP32 and Android Understand how to create connections to interact between ESP32 and mobile applications Learn how to interact between ESP32 boards and cloud servers Build an IoT Application-based ESP32 board Who this book is for This book is for those who want to build a powerful and inexpensive IoT projects using the ESP32.Also for those who are new to IoT, or those who already have experience with other platforms such as Arduino, ESP8266, and Raspberry Pi.

Internet of things. --- Arduino (Programmable controller)

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This book covers the technological progress and developments of a large-scale wind energy conversion system along with its future trends, with each chapter constituting a contribution by a different leader in the wind energy arena. Recent developments in wind energy conversion systems, system optimization, stability augmentation, power smoothing, and many other fascinating topics are included in this book. Chapters are supported through modeling, control, and simulation analysis. This book contains both technical and review articles.

doubly-fed induction generator --- fault current limiters --- power system --- power smoothing --- fault characteristics --- prediction intervals --- wind forecast --- PI controller --- transmission line --- wake effect --- real fault cases --- reliability of electricity supplies --- load frequency control --- optimization --- reserve power --- battery energy storage system --- wind turbine allocation --- primary frequency control --- low voltage ride through (LVRT) --- de-loading --- fault ride-through --- fault diagnosis and isolation --- fractional order proportional-integral-differential controller --- multi-objective artificial bee colony algorithm --- Fault Ride Through (FRT) --- distance protection --- droop curve --- Distribution Static VAr Compensator(D-SVC) --- Distributed-Flexible AC Transmission system (D-FACTS) --- rotor inertia --- power wind turbine --- LPV observer --- doubly fed induction generator (DFIG) --- squirrel cage induction generator (SCIG) --- wind farm --- optimal control --- fuzzy logic controller (FLC) --- wind power forecasting --- wavelet neural network --- DFIG-based wind farm --- permanent magnet synchronous generator --- automatic generation control --- series dynamic braking resistor --- hardware-in-the-loop --- superconductor --- Distribution Static Synchronous Compensator (D-STATCOM) --- control wind turbine --- kinetic energy storage --- multiple sensor faults --- large-scale wind farm

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This book covers the technological progress and developments of a large-scale wind energy conversion system along with its future trends, with each chapter constituting a contribution by a different leader in the wind energy arena. Recent developments in wind energy conversion systems, system optimization, stability augmentation, power smoothing, and many other fascinating topics are included in this book. Chapters are supported through modeling, control, and simulation analysis. This book contains both technical and review articles.

doubly-fed induction generator --- fault current limiters --- power system --- power smoothing --- fault characteristics --- prediction intervals --- wind forecast --- PI controller --- transmission line --- wake effect --- real fault cases --- reliability of electricity supplies --- load frequency control --- optimization --- reserve power --- battery energy storage system --- wind turbine allocation --- primary frequency control --- low voltage ride through (LVRT) --- de-loading --- fault ride-through --- fault diagnosis and isolation --- fractional order proportional-integral-differential controller --- multi-objective artificial bee colony algorithm --- Fault Ride Through (FRT) --- distance protection --- droop curve --- Distribution Static VAr Compensator(D-SVC) --- Distributed-Flexible AC Transmission system (D-FACTS) --- rotor inertia --- power wind turbine --- LPV observer --- doubly fed induction generator (DFIG) --- squirrel cage induction generator (SCIG) --- wind farm --- optimal control --- fuzzy logic controller (FLC) --- wind power forecasting --- wavelet neural network --- DFIG-based wind farm --- permanent magnet synchronous generator --- automatic generation control --- series dynamic braking resistor --- hardware-in-the-loop --- superconductor --- Distribution Static Synchronous Compensator (D-STATCOM) --- control wind turbine --- kinetic energy storage --- multiple sensor faults --- large-scale wind farm --- doubly-fed induction generator --- fault current limiters --- power system --- power smoothing --- fault characteristics --- prediction intervals --- wind forecast --- PI controller --- transmission line --- wake effect --- real fault cases --- reliability of electricity supplies --- load frequency control --- optimization --- reserve power --- battery energy storage system --- wind turbine allocation --- primary frequency control --- low voltage ride through (LVRT) --- de-loading --- fault ride-through --- fault diagnosis and isolation --- fractional order proportional-integral-differential controller --- multi-objective artificial bee colony algorithm --- Fault Ride Through (FRT) --- distance protection --- droop curve --- Distribution Static VAr Compensator(D-SVC) --- Distributed-Flexible AC Transmission system (D-FACTS) --- rotor inertia --- power wind turbine --- LPV observer --- doubly fed induction generator (DFIG) --- squirrel cage induction generator (SCIG) --- wind farm --- optimal control --- fuzzy logic controller (FLC) --- wind power forecasting --- wavelet neural network --- DFIG-based wind farm --- permanent magnet synchronous generator --- automatic generation control --- series dynamic braking resistor --- hardware-in-the-loop --- superconductor --- Distribution Static Synchronous Compensator (D-STATCOM) --- control wind turbine --- kinetic energy storage --- multiple sensor faults --- large-scale wind farm

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This book discusses the basic requirements and constraints in building a brain–computer interaction system. These include the technical requirements for building the signal processing module and the acquisition module. The major aspects to be considered when designing a signal acquisition module for a brain–computer interaction system are the human brain, types and applications of brain–computer systems, and the basics of EEG (electroencephalogram) recording. The book also compares the algorithms that have been and that can be used to design the signal processing module of brain–computer interfaces, and describes the various EEG-acquisition devices available and compares their features and inadequacies. Further, it examines in detail the use of Emotiv EPOC (an EEG acquisition module developed by Emotiv) to build a complete brain–computer interaction system for driving robots using a neural network classification module.

Brain-computer interfaces. --- Arduino (Programmable controller) --- Engineering. --- Artificial intelligence. --- Computational Intelligence. --- Control, Robotics, Mechatronics. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Computational intelligence. --- Control engineering. --- Robotics. --- Mechatronics. --- Mechanical engineering --- Microelectronics --- Microelectromechanical systems --- Automation --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Programmable controllers --- Intelligence, Computational --- Artificial intelligence --- Soft computing

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Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties:

n/a --- self-organization --- signal source localization --- multi-robot system --- sensor deployment --- parallel technique --- shape normalization --- genetic algorithm --- multiple robots --- optimization --- improved potential field --- optimal configuration --- autonomous docking --- asymmetrical interaction --- comparison --- behaviors --- patterns --- self-assembly robots --- congestion control --- surface-water environment --- target recognition --- coordinate motion --- UAV swarms --- formation reconfiguration --- swarm robotics --- swarm intelligence --- artificial bee colony algorithm --- obstacle avoidance --- fish swarm optimization --- search algorithm --- robotics --- time-difference-of-arrival (TDOA) --- formation --- mobile robots --- formation control --- meta-heuristic --- event-triggered communication --- search --- virtual structure --- 3D model identification --- surveillance --- event-driven coverage --- scale-invariant feature transform --- system stability --- Swarm intelligence algorithm --- bionic intelligent algorithm --- unmanned aerial vehicle --- underwater environment --- artificial flora (AF) algorithm --- swarm behavior --- weighted implicit shape representation --- Cramer–Rao low bound (CRLB) --- environmental perception --- particle swarm optimization --- modular robots --- cooperative target hunting --- virtual linkage --- multi-AUV --- consensus control --- panoramic view --- nonlinear disturbance observer --- sliding mode controller --- path optimization --- Swarm Chemistry --- multi-agents --- Cramer-Rao low bound (CRLB)