Present Situation and Development Trend of Indoor Positioning Technology

In recent years, indoor and outdoor positioning technology for the blind has attracted much more attention. The outdoor positioning technology has relatively matured. However, three-dimensional indoor positioning technology is facing many problems. Due to low positioning accuracy as well as slow positioning speed, there is no ideal implementation system at present. Light Fidelity (LiFi) technology is a new wireless transmission technology that uses the visible light spectrum, such as the light emitted by a light bulb, to transmit data. It transmits signals through the changing light of LED lights. When LED lights are properly laid out in the building, not only the function of lighting but also that of transmitting information are met at the same time. It is a good way to solve indoor positioning problems. This article studies an indoor positioning glasses for blind based on the LiFi technology. Different from other indoor positioning technologies such as ultrasound and wireless fidelity (WiFi), the design of indoor positioning glasses for the blind will propose new ideas of three-dimensional indoor positioning problems for the blind.

Understanding the indoor whereabouts of individuals and objects is important, especially for those who fall within the 71% of visually impaired individuals with a school education, students in 450 special education units and many other areas and aspects in Sri Lanka. Researchers have declared that, there isn’t any particularly good localization system, and the performance should be evaluated considering the approach and application. The most well-known indoor positioning (IP) technologies that have been historically deployed are Bluetooth, Wi-Fi, RFID (radio frequency identification), IR (Infrared), and UV (ultraviolet) whereas received signal strength (RSSI), fingerprinting, and triangulation methods have been used as common IP techniques. The combination of both IP technologies and techniques creates an IP system, and the integration of machine learning and IoT with the structured system essentially delivers an accurate and more advanced system. This paper contains a detailed, analytical review of a developed indoor positioning system derived from the existing indoor localization techniques, localization technologies, localization systems, algorithms, and performance matrixes. This also provides a comprehensive comparison between numerous existing systems to justify the proposed solution. This project has been developed to achieve better accuracy through low-cost deployment as an effective system to fill the gap in the scarcity of positioning systems in the world. This paper presents a descriptive introduction and problem definition, a critical discussion of results, machine learning models, benefits of the project, and future works. As later justified, ESP32 microcontroller and BLE beacons are utilized with RSSI fingerprinting method to develop this IP system and, as a part of the project, two data visualization methods have been introduced here using NodeRED dashboard and LC display. Overall, this project was developed with an effective combination of RSSI fingerprinting, IoT protocols, machine learning, and data interpretation methods. KEYWORDS: Indoor positioning, RSSI, Fingerprinting, Machine Learning, MQTT, ESP32, BLE beacons, NodeRED

According to the paper published at 2010-2013 Indoor Positioning and Indoor Navigation (IPIN), this paper classify the indoor position technology to four classes by technical characteristics. The developing trends and main characteristics of future indoor position technology are deduced based on the paper data published by IPIN. The bottlenecks of indoor position technology was proposed. Finally, the future development trend of indoor position technology was predicted.

High-precision indoor positioning technology is regarded as one of the core components of artificial intelligence (AI) and Internet of Things (IoT) applications. Over the past decades, society has observed a burgeoning demand for indoor location-based services (iLBSs). Concurrently, ongoing technological innovations have been instrumental in establishing more accurate, particularly meter-level indoor positioning systems. In scenarios where the penetration of satellite signals indoors proves problematic, research efforts focused on high-precision intelligent indoor positioning technology have seen a substantial increase. Consequently, a stable assortment of location sources and their respective positioning methods have emerged, characterizing modern technological resilience. This academic composition serves to illuminate the current status of meter-level indoor positioning technologies. An in-depth overview is provided in this paper, segmenting these technologies into distinct types based on specific positioning principles such as geometric relationships, fingerprint matching, incremental estimation, and quantum navigation. The purpose and principles underlying each method are elucidated, followed by a rigorous examination and analysis of their respective technological strides. Subsequently, we encapsulate the unique attributes and strengths of high-precision indoor positioning technology in a concise summary. This thorough investigation aspires to be a catalyst in the progression and refinement of indoor positioning technologies. Lastly, we broach prospective trends, including diversification, intelligence, and popularization, and we speculate on a bright future ripe with opportunities for these technological innovations.

At present, location technology divides into outdoor location technology and indoor location technology. Comparing with other indoor location methods, ultra-wide band (UWB)indoor location technology has the advantages of strong anti-multipath interference ability and signal penetration ability. But, when this method faces large obstacles or metal obstacles, non line of sight (NLOS) will still occur. Indoor location system is a part of our project Home Care System for The Elderly. The NLOS of Indoor location system reduces the reliability of Home Care System for The Elderly. In order to improve the accuracy of location and efficiency of operation, an NLOS detection method based on k-nearest neighbors (KNN) algorithm is proposed. This algorithm modeled the training samples to find the K value with the highest recognition accuracy. The experimental results show that The NLOS detection accuracy of this method is 78% in the simulated apartment scene. With the same number of samples, the accuracy of the widely used Convolutional Neural Networks (CNN) algorithm is 67%. The experimental results show that KNN algorithm is more suitable for Home Care System for The Elderly for it can keep high accuracy with less requirement for the number of samples than CNN.

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this special issue present recent advances and new developments in indoor localization systems and technologies, proposing novel or improved methods with increased performance, providing insight into various aspects of quality control, and also introducing some unorthodox positioning methods.

As the communication field continues to evolve, positioning technology has emerged as a crucial and valuable research avenue. Particularly, indoor positioning presents an innovative and trending direction in this technology. During the research process of indoor positioning, it is essential to consider the impact of various environmental disturbances on positioning accuracy. Additionally, efforts should be geared towards minimizing these environmental influences on the positioning system's performance and reducing the complexity of the positioning algorithm. The ideal scenario for indoor positioning involves using a relatively straightforward positioning algorithm to obtain results with high positioning accuracy. That said, it is a challenging balance to strike, given the intricate factors that influence the effectiveness of indoor positioning. This paper focuses on the Time Difference of Arrival (TDOA) localization method. We explore the TDOA-based triangle centroid algorithm, Fang's algorithm, and Chan's algorithm, all prominent methods in this field. Each of these approaches presents unique strengths and challenges, offering diverse solutions to address the complexity of indoor positioning. Their comparative analysis will provide insights into the development of efficient, accurate, and straightforward indoor positioning techniques.

BackgroundHospital-acquired infections are still amongst the major problems health systems are facing. Their occurrence can lead to higher morbidity and mortality rates, increased length of hospital stay, and higher costs for both hospital and patients. Performing hand hygiene is a simple and inexpensive prevention measure, but healthcare workers’ compliance with it is often far from ideal. To raise awareness regarding hand hygiene compliance, individual behaviour change and performance optimization, we aimed to develop a gamification solution that collects data and provides real-time feedback accurately in a fun and engaging way.MethodsA Design Science Research Methodology (DSRM) was used to conduct this work. DSRM is useful to study the link between research and professional practices by designing, implementing and evaluating artifacts that address a specific need. It follows a development cycle (or iteration) composed by six activities. Two work iterations were performed applying gamification components, each using a different indoor location technology. Preliminary experiments, simulations and field studies were performed in an Intensive Care Unit (ICU) of a Portuguese tertiary hospital. Nurses working on this ICU were in a focus group during the research, participating in several sessions across the implementation process.ResultsNurses enjoyed the concept and considered that it allows for a unique opportunity to receive feedback regarding their performance. Tests performed on the indoor location technology applied in the first iteration regarding distances estimation presented an unacceptable lack of accuracy. Using a proximity-based technique, it was possible to identify the sequence of positions, but beacons presented an unstable behaviour. In the second work iteration, a different indoor location technology was explored but it did not work properly, so there was no chance of testing the solution as a whole (gamification application included).ConclusionsCombining automated monitoring systems with gamification seems to be an innovative and promising approach, based on the already achieved results. Involving nurses in the project since the beginning allowed to align the solution with their needs. Despite strong evolution through recent years, indoor location technologies are still not ready to be applied in the healthcare field with nursing wards.

Time reversal-based indoor positioning system (TRIPS) is a promising technology for the centimeter-accuracy indoor positioning, since it exploits the rich multipath propagation in indoor environments as a specific signature for each location. In TRIPS, a database is first constructed via channel probing. Well-calibrated devices are usually assumed in this process, i.e., no hardware impairments. However, a low cost terminal to be located, whose typical impairment is the I/Q imbalance (IQI) at the front-end transmitter, can significantly influence the TRIPS performance. More specifically, IQI creates an interference image of the signal that reduces the metric value used in TRIPS and hence decreases the localization accuracy. In this paper, we analytically investigate the impact of the IQI on the metric of TRIPS. A closed-form approximation of the localization metric inherent to the IQI is derived. In order to improve the TRIPS performance, an effective IQI mitigation method is proposed. Numerical simulations are carried out to validate the derived analytical expression under the IQI impact and the proposed compensation method.

In the world of Industry 4.0 digital era ecosystem, there is a tendency to improve and evolve the theoretical and practical applications of Occupational Health and Safety to meet the new standards, and requirements. The technological advances improve the hardware and software developments to improve the OHS issues with new dimensions like IIoT, industrial big data, artificial intelligence, machine learning, sensor fusion and autonomous agents.Among those various cyber-physical system components, technological improvements and challenges trigger new standards and approaches for occupational health and safety issues, directly related to human life and health. The Occupational Health and Safety (OHS) 4.0 is a new approach that aims to proactively, and preventively protect employees’ health and safety in the workplace, environment, environment, and equipment with the individual/team; by using the relevant components of Industry 4.0 concepts. This will also lead to the digital transformation of the OHS 4.0 procedures and approaches.In this article, the Indoor Positioning System (IPS) applications and technologies such as indoor tracking, asset monitoring systems and the wireless communication infrastructures have analyzed, and compared according to their usability for OHS 4.0. A road map has developed and explained for implementing these systems and a comparison matrix with the OHS processes.

With wireless communications technology development, more and more indoor positioning technology has been used in exhibitions. This paper shows the difference between traditional indoor positioning technology and new generation of indoor positioning technology. Besides, this paper introduces several kinds of common indoor positioning technology and contrasts their precision and relative merit. Finally it gives a case to show how to design exhibitions based on the new generation of indoor positioning technology.

Passive ultra-high frequency (UHF) radio frequency identification (RFID) provides an attractive technology for indoor positioning and localization. It offers contactless communication, non line-of-sight readability, compactness, and low cost. Localization techniques and algorithms have been actively researched recently from accuracy point of view. However, less attention has been paid to the antenna and its effects on the achieved localization accuracy. Particularly, wearable antennas in human localization applications are key components affecting the achieved accuracy and reliability. In this paper, we elaborate on the material choice for wearable UHF RFID patch antennas. Two highly attractive and flexible conductive electro-textiles are discussed and compared: anisotropic embroidered textile structure and uniform commercially available copper fabric. A patch tag antenna is designed for each electro-textile to operate at 866 MHz. The on-body readability and Received Signal Strength (RSS) in office environment for the antennas are recorded and analyzed. Based on the results we decide on the antenna feasibility in localization applications.

Geomagnetic field–based positioning and navigation technologies have gradually evolved into an important alternative to satellite navigation, particularly for mechanical equipment and engineering systems operating in GPS-denied or GPS-challenged environments. From the perspective of engineering equipment applications, this paper provides a systematic review of the current state of development and key issues in geomagnetic navigation and positioning technologies. First, the physical characteristics of the Earth’s magnetic field and representative magnetic sensor are summarized, with an emphasis on their deployment approach on equipment platforms. Subsequently, commonly used geomagnetic positioning and navigation methods and algorithms are systematically reviewed, and their adaptability and engineering performance are analyzed. Furthermore, representative application cases of geomagnetic navigation in aerial, terrestrial, and underwater domains are reviewed to demonstrate the practical potential and engineering value of this technology in equipment systems. Finally, the major challenges encountered in engineering applications of geomagnetic navigation are discussed, and future development trends are outlined. This review aims to provide systematic references and technical guidance for bridging fundamental research on geomagnetic positioning and navigation with engineering implementation on equipment platforms.

This paper presents research performed on indoor positioning technologies to identify a technology that would be best to implement in a prototype at Kettering University's campus. The indoor positioning techniques evaluated are mainly based on beacon sources including Bluetooth, Wi-Fi, Geomagnetic, Visual Light Communication (VLC), and Ultra-Wideband (UW). Target-side wearable sensors will be considered. The algorithms commonly used for calculating the user's position will be discussed, including Trilateration, Fingerprinting, and K-Nearest-Neighbor.

With the increasing demand for location-based services, indoor localization technology based on wireless sensor networks (WSNs) has recently received significant attention. Bluetooth low energy (BLE) has become a research hotspot among the numerous WSNs due to its ubiquitous deployment, low-power consumption, and low cost. Many previous BLE-based indoor localization technologies can only use received signal strength indication (RSSI) for localization in the 2-D plane and achieve coarse accuracy. However, high-accuracy location information is required in an increasing number of applications, e.g., elderly fall detection for medical applications, which urgently requires a new BLE-based localization technology in 3-D space. To this end, we propose Spotlight, an angle-based fine-grained indoor localization system in 3-D space using BLE sensors. The critical idea of the Spotlight is to measure the angle-of-arrival (AoA) and elevation-of-angle (EoA) of the signal from the target to the BLE receivers and utilize them to achieve accurate 3-D localization. Specifically, we develop an offset elimination algorithm and data stitching algorithm, utilizing the second-order cone (SoC) programming to obtain accurate angle estimates. Then, the simulated annealing algorithm (SAA) is used to search for the target location in 3-D space. Finally, we develop the prototype system with commercial off-the-shelf (COTS) BLE sensors and conduct extensive experiment measurements in real-world scenarios. The results demonstrate that the proposed system can achieve a median localization error of 36 cm in the 2-D plane and 48 cm in the 3-D space.