Considering a future scenario in which a driverless Electric Vehicle (EV) needs an automatic charging system without human intervention. In this regard, there is a requirement for a fully automatable, fast, safe, cost-effective, and reliable charging infrastructure that provides a profitable business model and fast adoption in the electrified transportation systems. These qualities can be comprehended through wireless charging systems. Wireless Power Transfer (WPT) is a futuristic technology with the advantage of flexibility, convenience, safety, and the capability of becoming fully automated. In WPT methods resonant inductive wireless charging has to gain more attention compared to other wireless power transfer methods due to high efficiency and easy maintenance. This literature presents a review of the status of Resonant Inductive Wireless Power Transfer Charging technology also highlighting the present status and its future of the wireless EV market. First, the paper delivers a brief history throw lights on wireless charging methods, highlighting the pros and cons. Then, the paper aids a comparative review of different type’s inductive pads, rails, and compensations technologies done so far. The static and dynamic charging techniques and their characteristics are also illustrated. The role and importance of power electronics and converter types used in various applications are discussed. The batteries and their management systems as well as various problems involved in WPT are also addressed. Different trades like cyber security economic effects, health and safety, foreign object detection, and the effect and impact on the distribution grid are explored. Prospects and challenges involved in wireless charging systems are also highlighting in this work. We believe that this work could help further the research and development of WPT systems.

/pdf/inductive-wireless-power-transfer-charging-for-electric-3o8fo82kdz.pdf

Inductive Wireless Power Transfer Charging for Electric Vehicles–A Review

An accurate and reliable Indoor Positioning System (IPS) applicable to most indoor scenarios has been sought for many years. The number of technologies, techniques, and approaches in general used in IPS proposals is remarkable. Such diversity, coupled with the lack of strict and verifiable evaluations, leads to difficulties for appreciating the true value of most proposals. This paper provides a meta-review that performed a comprehensive compilation of 62 survey papers in the area of indoor positioning. The paper provides the reader with an introduction to IPS and the different technologies, techniques, and some methods commonly employed. The introduction is supported by consensus found in the selected surveys and referenced using them. Thus, the meta-review allows the reader to inspect the IPS current state at a glance and serve as a guide for the reader to easily find further details on each technology used in IPS. The analyses of the meta-review contributed with insights on the abundance and academic significance of published IPS proposals using the criterion of the number of citations. Moreover, 75 works are identified as relevant works in the research topic from a selection of about 4000 works cited in the analyzed surveys.

https://www.mdpi.com/1424-8220/19/20/4507/pdf

A Meta-Review of Indoor Positioning Systems.

Navigation systems help users access unfamiliar environments. Current technological advancements enable users to encapsulate these systems in handheld devices, which effectively increases the popularity of navigation systems and the number of users. In indoor environments, lack of Global Positioning System (GPS) signals and line of sight with orbiting satellites makes navigation more challenging compared to outdoor environments. Radio frequency (RF) signals, computer vision, and sensor-based solutions are more suitable for tracking the users in indoor environments. This article provides a comprehensive summary of evolution in indoor navigation and indoor positioning technologies. In particular, the paper reviews different computer vision-based indoor navigation and positioning systems along with indoor scene recognition methods that can aid the indoor navigation. Navigation and positioning systems that utilize pedestrian dead reckoning (PDR) methods and various communication technologies, such as Wi-Fi, Radio Frequency Identification (RFID) visible light, Bluetooth and ultra-wide band (UWB), are detailed as well. Moreover, this article investigates and contrasts the different navigation systems in each category. Various evaluation criteria for indoor navigation systems are proposed in this work. The article concludes with a brief insight into future directions in indoor positioning and navigation systems.

/pdf/indoor-positioning-and-wayfinding-systems-a-survey-49mq36uclc.pdf

Indoor positioning and wayfinding systems: a survey

With the wide spread of the Internet of Things (IoT), wireless localization technology has provided various location-based applications and services. Radio frequency identification (RFID) has been widely used in objects’ identification and tracking. Combining with its excellent identification ability, RFID is also a promising technique for indoor localization. This paper provides the state-of-the-art of UHF RFID localization and gives an introduction of methods and applications. The major methods of UHF RFID localization have two types: 1) range-based and 2) range-free, reported in previous literature. The range-based methods obtain the distance or angle between the antenna and tag utilizing the received signal strength indicator (RSSI), time information or signal phase and estimate tag location further combining the scheme geometrical characteristics. The methods based on fingerprinting and non-fingerprinting are mainly discussed in the range-free domain. Finally, a comparative study of these surveyed works are presented and concluded with a future trend.

Review on UHF RFID Localization Methods

The exact location of objects, such as infrastructure, is crucial to the systematic understanding of the built environment. The emergence and development of the Internet of Things (IoT) have attracted growing attention to the low-cost location scheme, which can respond to a dramatic increasing amount of public infrastructure in smart cities. Various Radio Frequency IDentification (RFID)-based locating systems and noise mitigation methods have been developed. However, most of them are impractical for built environments in large areas due to their high cost, computational complexity, and low noise detection capability. In this paper, we proposed a novel noise mitigation solution integrating the low-cost localization scheme with one mobile RFID reader. We designed a filter algorithm to remove the influence of abnormal data. Inspired the sampling concept, a more carefully parameters calibration was carried out for noise data sampling to improve the accuracy and reduce the computational complexity. To achieve robust noise detection results, we employed the powerful noise detection capability of the random sample consensus (RANSAC) algorithm. Our experiments demonstrate the effectiveness and advantages of the proposed method for the localization and noise mitigation in a large area. The proposed scheme has potential applications for location-based services in smart cities.

https://www.mdpi.com/1424-8220/19/9/2143/pdf

A Robust Noise Mitigation Method for the Mobile RFID Location in Built Environment.

The Global Positioning System (GPS) is widely used in outdoor environmental positioning. However, GPS cannot support indoor positioning because there is no signal for positioning in an indoor environment. Nowadays, there are many situations which require indoor positioning, such as searching for a book in a library, looking for luggage in an airport, emergence navigation for fire alarms, robot location, etc. Many technologies, such as ultrasonic, sensors, Bluetooth, WiFi, magnetic field, Radio Frequency Identification (RFID), etc., are used to perform indoor positioning. Compared with other technologies, RFID used in indoor positioning is more cost and energy efficient. The Traditional RFID indoor positioning algorithm LANDMARC utilizes a Received Signal Strength (RSS) indicator to track objects. However, the RSS value is easily affected by environmental noise and other interference. In this paper, our purpose is to reduce the location fluctuation and error caused by multipath and environmental interference in LANDMARC. We propose a novel indoor positioning algorithm based on Bayesian probability and K-Nearest Neighbor (BKNN). The experimental results show that the Gaussian filter can filter some abnormal RSS values. The proposed BKNN algorithm has the smallest location error compared with the Gaussian-based algorithm, LANDMARC and an improved KNN algorithm. The average error in location estimation is about 15 cm using our method.

An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor.

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An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor.