TY - BOOK ID - 124998067 TI - Intelligent Sensors for Positioning, Tracking, Monitoring, Navigation and Smart Sensing in Smart Cities AU - Li, Tiancheng AU - Yan, Junkun AU - Cao, Yue AU - Bajo, Javier PY - 2021 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - History of engineering & technology KW - clustering KW - data fusion KW - target detection KW - Grey Wolf Optimizer KW - Fireworks Algorithm KW - hybrid algorithm KW - exploitation and exploration KW - GNSS KW - MIMU KW - odometer KW - state constraints KW - simultaneous localization and mapping (SLAM) KW - range-only SLAM KW - sum of Gaussian (SoG) filter KW - cooperative approach KW - automatic fare collection system KW - passenger flow forecasting KW - time series decomposition KW - singular spectrum analysis KW - ensemble learning KW - extreme learning machine KW - wheeled mobile robot KW - path panning KW - laser simulator KW - fuzzy logic KW - laser range finder KW - Wi-Fi camera KW - sensor fusion KW - local map KW - odometry KW - deep learning KW - softmax KW - decision-making KW - classification KW - sensor data KW - Internet of Things KW - extended target tracking KW - gamma-Gaussian-inverse Wishart KW - Poisson multi-Bernoulli mixture KW - 5G IoT KW - indoor positioning KW - tracking KW - localization KW - navigation KW - positioning accuracy KW - single access point positioning KW - fuzzy inference KW - calibration KW - car-following KW - Takagi–Sugeno KW - Kalman filter KW - microscopic traffic model KW - continuous-time model KW - LoRa KW - positioning KW - LoRaWAN KW - TDoA KW - map matching KW - compass KW - automotive LFMCW radar KW - radial velocity KW - lateral velocity KW - Doppler-frequency estimation KW - waveform KW - signal model KW - tensor modeling KW - smart community system KW - power efficiency KW - object-detection coprocessor KW - histogram of oriented gradient KW - support vector machine KW - block-level once sliding detection window KW - multi-shape detection-window UR - https://www.unicat.be/uniCat?func=search&query=sysid:124998067 AB - The rapid development of advanced, arguably, intelligent sensors and their massive deployment provide a foundation for new paradigms to combat the challenges that arise in significant tasks such as positioning, tracking, navigation, and smart sensing in various environments. Relevant advances in artificial intelligence (AI) and machine learning (ML) are also finding rapid adoption by industry and fan the fire. Consequently, research on intelligent sensing systems and technologies has attracted considerable attention during the past decade, leading to a variety of effective applications related to intelligent transportation, autonomous vehicles, wearable computing, wireless sensor networks (WSN), and the internet of things (IoT). In particular, the sensors community has a great interest in novel, intelligent information fusion, and data mining methods coupling AI and ML for substantial performance enhancement, especially for the challenging scenarios that make traditional approaches inappropriate. This reprint book has collected 14 excellent papers that represent state-of-the-art achievements in the relevant topics and provides cutting-edge coverage of recent advances in sensor signal and data mining techniques, algorithms, and approaches, particularly applied for positioning, tracking, navigation, and smart sensing. ER -