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Object location in indoor environments is challenging when there is no physical contact, a field of view, reflective materials, and an excess of obstacles. Several works propose using Radio Frequency Identification technology (RFID) and machine learning methods to develop location systems in those situations. However, using an object as a target class slows learning and prediction in large-scale environments. To circumvent such problems, we proposed a location system that uses hierarchical classification. We divided the environment into regions to reduce the classifier’s training and the number of predicted classes. To define the regions, we used clustering techniques, indicating which clustering technique achieves the best performance in the proposed scenario. The main contribution of this work is a high-precision location system for large-scale environments. The results showed the proposed system’s implantation in a real environment with 400 target objects with 5 cm of location precision. The accuracy for region detection is 99.36%, while for identifying the object is 99.94%. Additionally, with the proposed hierarchical approach, we showed a reduction of 38.16% and 58.39% in processing time and classifier model size.

Most scientific contributions addressing cyber-security issues in water distribution networks present proposals of detection systems and very few propose location systems. A novel methodology for detection and location of cyber-attacks in water distribution networks (WDNs) is proposed in this paper. Structural analysis and autoencoder neural networks are effectively combined with a the control chart Adaptive Exponentially Weighted Moving Average (AEWMA). In the training phase, the proposed detection and location framework only requires data from normal operating conditions and knowledge about the behavioral model of the system which represents an advantage over previous works that demand for additional data of cyber-attacks. Among other advantages of the proposed methodology are the high performance in the effective, robust and early detection and the effectiveness of the location strategy. The proposal was evaluated with the known case study BATADAL.

The article talks about our design of ultrasound-based localization system. The designed system is primarily intended for mobile robotics. The second part of this article is focused on the initial verification of the basic characteristics and accuracy of the position measurement. This location system is currently still in the process of improving the functions required for usage in mobile robotics. We are currently working on removing some types of interferences.

The municipal solid waste (MSW) management is an important part of building the smart city. Waste transfer station is an important link between the upper and the lower in the MSW management. Politic, environment and economy are all need to be considered in the waste transfer station location problem. Based on that, By establishing an optimized MSW transfer station location system based on internet of things, the locations of MSW transfer station is studied. Firstly, the Ward’s clustering approach is used to obtain the waste transfer station number in the city. And then a multi-objective model is established and NSGA-II is used to solve the model to obtain the Pareto frontier solution set of waste transfer station location coordinates. According the Google map, the optimal location coordinates of waste transfer station are obtained. Finally, a case study is conducted to demonstrate the practicality and efficiency of the proposed model and solution algorithm.

Impulse-radio ultra-wideband (IR-UWB) networks are gaining wide acceptance in short-to-medium range wireless sensing and positioning applications that require high accuracy. It is achieved generally via signal message exchange between ultra-wideband (UWB) transceiver nodes, where the signal propagating through their analog circuitry suffers transmitting and receiving antenna delays. Such delays, unless measured and properly corrected for, may induce an error in range estimation between UWB nodes and eventually affect the accuracy of real-time location systems (RTLSs) based on the IR-UWB. This paper presents a system to measure the antenna delays of UWB nodes. It provides comprehensive mathematical modeling, design, and implementation of the proposed antenna delay measurement system. Experimental evaluation in a line-of-sight (LOS) environment shows its effectiveness for maintaining the accuracy of the range measurement between UWB nodes by taking into consideration the antenna delays measured by the proposed system.

The purpose of this study is to investigate the effective indexes of damage to a building, with the aim of reducing the possible events caused by the earthquake and presenting a model based on spatial information systems. So, after collecting the data and information required by field method and statistical blocks, a spatial database was obtained. Then, the effectiveness of each of the criteria was based on the creation of a binary comparison matrix and questioning experts from the subject The study was obtained. In the end, in order to establish a link between the influential factors and the estimation of the final vulnerability of each building, a formula was presented in which all the effective factors were involved with the emphasis on the level of effectiveness of each building. Using expert selection software, the indexes were evaluated in terms of weight and value. Finally, the geospatial information system of GIS evaluated the magnitude and severity of the earthquake in different ranges and its consequences in terms of the indices studied for the buildings in the study area.

Location systems and their daily use in industry and individual users have become an inseparable part of our everyday functioning. However, often they are used in the so-called intelligent buildings. Unfortunately, just like location methods operating outside buildings are precise enough to determine our location (e.g. GPS systems for drivers), the situation of locating people inside the building is different, especially when such people cannot be equipped with additional devices (e.g. a transmitter signal). Nevertheless, it is essential in communication routes, large clusters of people, such as airports, railway stations or office spaces. At the same time, determine the number of people in space and the development of services that do not require direct contact (automatic patient/client registration) in times of a possible pandemic.

Unmanned Ground Vehicles (UGV) are devices capable of performing basic working movements without the operator being in their immediate working environment. Their capabilities include but are not limited to the perception of the environment with the use of sensors, determining the platform’s position, and planning and executing its movement. Ultra Wideband (UWB) is one of the wireless communication technologies which is increasingly used in location systems. This article presents the use of UWB technology in developing a guide localization system for a UGV (one of the stages of implementing a follow-me system). The article describes tests carried out on the developed testbed. Their aim was to determine the hardware configuration of the anchor arrangement characterized by the minimum number of lost data packets during operation. In order to determine the influence of the analysed variables on the output values, the method of global sensitivity analysis for neural networks was used.

The accuracy of the Bluetooth position, which has a high position speed, is not good. Visual information positioning takes more time, but its positioning accuracy is better. Since single positioning means cannot meet the needs of indoor positioning, we designed an indoor Location system based on fusion of Bluetooth signal and visual information in combination with their characteristics: According to the result of the rough positioning of the Bluetooth signal and the range of the Bluetooth positioning error, we can narrow the scope of the image database and use the visual information to locate the position with a high speed.; Then, according to the posterior probability distribution of the two kinds of positioning, we will integrate the two positioning results into the final positioning results. The simulation results show that the positioning performance of the system is better than that of pure Bluetooth positioning and visual information positioning.

Due to the large number of elderly people with physical and cognitive issues, there is a strong need to provide indoor location systems that help caregivers monitor as many people as possible and with the best quality possible. In this paper, a fuzzy indoor location methodology is proposed in a smart environment based on mobile devices and Bluetooth Low Energy (BLE) beacons where a set of Received Signal Strength Indicators (RSSI) is received by mobile devices worn by the inhabitants. The use of fuzzy logic and a fuzzy linguistic approach is proposed to deal with the imprecise nature of the RSSI values, which are influenced by external factors such as radio waves, causing significant fluctuations. A case study carried out at the Smart Lab of the University of Jaén (UJAmI Smart Lab) is presented to demonstrate the effectiveness of the proposed methodology, where our proposal is compared with a non-fuzzy logic approach, obtaining an accuracy of 91.63%, approximately 10 points higher than the methodology without using fuzzy logic. Finally, our theoretical proposal is accompanied by a description of the UJAmI Location system, which applies the theory to the functionality of locating elderly people in indoor environments.

In this work we performed a comparison between two different approaches to track a person in indoor environments using a locating system based on BLE technology with a smartphone and a smartwatch as monitoring devices. To do so, we provide the system architecture we designed and describe how the different elements of the proposed system interact with each other. Moreover, we have evaluated the system’s performance by computing the mean percentage error in the detection of the indoor position. Finally, we present a novel location prediction system based on neural embeddings, and a soft-attention mechanism, which is able to predict user’s next location with 67% accuracy.

The aim of this study was to model and evaluate the Specific Energy Absorption Rate (SAR) values in humans in proximity to fixed multi-antenna I-RFID readers of passive tags under various scenarios mimicking exposure when they are incorporated in Real-Time Location Systems (RTLS), or used to monitor Personal Protective Equipment (PPE). The sources of the electromagnetic field (EMF) in the modelled readers were rectangular microstrip antennas at a resonance frequency in free space of 866 MHz from the ultra-high frequency (UHF) RFID frequency range of 865-868 MHz. The obtained results of numerical modelling showed that the SAR values in the body 5 cm away from the UHF RFID readers need consideration with respect to exposure limits set by international guidelines to prevent adverse thermal effects of exposure to EMF: when the effective radiated power exceeds 5.5 W with respect to the general public/unrestricted environments exposure limits, and with respect to occupational/restricted environments exposure limits, when the effective radiated power exceeds 27.5 W. Results of a research tasks (II.PB.15, II.N.19) carried out within the National Programme “Improvement of safety and working conditions” partly supported in Poland in 2017–2019 and 2020–2022—within the scope of research and development—by the Ministry of Science and Higher Education/National Centre for Research and Development (Central Institute for Labour Protection—National Research Institute was the Programme’s main co-ordinator); grant ‘Architecture for Scalable, Self-human-centric, Intelligent, Secure, and Tactile next generation IoT’ (957258–ASSIST-IoT) funding from the European’s Union Horizon 2020 research innovation programme and the project ‘Electromagnetic Characterisation in Smart Environments of Healthcare and their involvement in Personnel. Occupational and Environmental Health’ (PI14CIII/00056) funding from Sub-Directorate-General for Research Assessment and Promotion in Spain (Instituto de Salud Carlos III). Sí

The need for real-time and high-precision localization in indoor or outdoor areas has increased considerably recently. Real-time location systems offer solutions for this need with different technologies. One of the solutions is to determine the location using the time difference of arrival of the signal between anchor and tag. In this study, a new algorithm is proposed for indoor localization of wearable smart devices. The algorithm, which is based on the time difference of arrival of the signal from the tag to the anchor, allows the localization with submeter accuracy. Thus, it will be possible to track the location of patients, personnel or objects in military, health and commercial areas using real-time, accurate and precise location information via wearable smart devices.

This letter proposes a method to apply the random forest (RF) algorithm for exploiting the multipath information and enhance the time difference of arrival (TDOA) localization systems performance. This new approach aims to enhance the performance of a location system in outdoor scenarios, where there are technical restrictions to deploy them in line-of-sight condition. A site-specific fingerprint is extracted with ray-tracing simulations to produce a multipath dataset. The signals are processed with a multidimensional cross-correlation function, called volume cross-correlation (VCC) function, to extract the multipath features from the TDOAs measurements. The machine learning framework searches the points in the scenario, trying to find the most likely to be the emitter position using the processed features and the radio map.

With the development of urbanization, the building structures are more and more complex, and various moving objects, such as human beings, robots and unmanned aerial vehicles, often travel through indoor and outdoor 3D space, which puts forward higher requirements for the accurate search and location in indoor and outdoor space. At present, most of the spatial location methods for indoor entities are carried out through 2D maps. However, the indoor environment is a complex 3D space, which increases the difficulty of the search process. In addition, 2D map cannot accurately display the 3D spatial position of the entity. Therefore, it is difficult for 2D maps to search and locate in complex environment. Therefore, how to quickly and effectively carry out spatial location query in complex indoor environment has become an urgent problem to be solved. Taking the library of Beijing University of Civil Engineering and Architecture as an example, this paper obtains the indoor 3D information of the library based on SLAM, processes and publishes the acquired 3D information on IndoorViewer, and uses its API in the book retrieval system. Finally, a book retrieval and location system based on real-scene 3D is finished.

Electromagnetic (EM) wave of enemy radar propagated by troposcatter can be utilized for beyond line-of-sight (b-LoS) location. To provide theoretical basis for passive troposcatter location system, channel characteristics including propagation loss, refraction effect and multipath fading are analyzed. Ray tracing method improved by tropospheric model is employed to describe the refraction effect. Correlation coefficient on the basis of transfer function is deduced to evaluate multipath fading. According to troposcatter characteristics, maximum operating range is estimated, cooperative energy detection is introduced to copy with the received signal without priori knowledge. The principle and accuracy of location algorithm based on azimuth is researched. Spatial smoothing is introduced under the situation that uncorrelated and coherent signals coexist. Through analyzing consequences, future directions for developing are suggested.

Millimeter-wave (mmWave) communications have emerged as one of the most promising options to vastly increase wireless data rates due to the high bandwidth they offer. Given the high path loss at mmWave frequencies, such systems require directional antennas to achieve a good communication range. Thus, the communicating devices need to align the beam directions of their mmWave antennas. Due to the high penetration loss, the paths between the antennas also need to be free of blocking obstacles. This makes an efficient and reliable operation of mmWave networks in dynamic environments very challenging. At the same time, the directionality reduces interference and allows to scale these networks to much higher access point and device densities. In this paper, we discuss the above-mentioned challenges and present techniques that allow mmWave networks to scale to high-density deployments, to adapt to dynamic and mobile environments, and to consistently achieve high data rates. This includes learning the environment to find different propagation paths, reacting timely to channel impairments such as blockage, and integrating mmWave networks with networks operating at a lower frequency for robustness. A key ingredient to enable these forms of adaptivity is the use of location information. Such mechanisms then turn a collection of very-high-speed but brittle mmWave links into an efficient, low-latency, and reliable network.

In view of the lack of accurate lightning trip out rate calculation method for overhead lines with ungrounded neutral points, this paper comprehensively considers the lightning protection configuration of transmission lines and the actual lightning activity parameters in the line corridor to carry out theoretical analysis, simulation calculation and scheme research. Firstly, based on the line account information and lightning location system monitoring data, based on the electrical geometry model to determine the impact of lightning on the line, an accurate calculation method of lightning trip out rate is proposed, and the method is used to calculate and verify the lightning trip out rate of a neutral point ungrounded line in a certain area. The results show that the lightning trip out rate calculation method can accurately calculate the lightning trip out rate of the line and the line corridor after considering the lightning characteristics of the line and the line corridor.

The number of older people is increasing in many countries. By 2030, it is estimated that 15% of the overall population will be comprised of people aged 65 and above. Hence, the monitoring and tracking of elder activities to ensure they live an active life has become a major research topic in recent years. In this work, an elderly sub-activity tracking system is developed to detect the sub-activity of the elderly based on their physical activities and indoor location. The physical activities tracking system and indoor location system is combined in this project to enhance the context of the elderly activities (i.e. sub-activities as defined in this project). An indoor location system is developed by using Bluetooth Low Energy (BLE) beacon and BLE scanners to measure the Received Signal Strength Indicator (RSSI) signal to detect the location of the elderly. The activity tracking is carried out via a waist wearable device worn by the elderly. Random forest and Support Vector Machine (SVM) are used as machine learning classifiers to predict the activity and indoor location with an accuracy of 95.03% and 86.58%, respectively. The data from activity tracking and indoor location sub-systems will then be combined to derive the sub-activity and push to an online Internet of Things (IoT) platform for remote monitoring and notification.

We have been developing a bus location system using LoRa for the community buses in Nonoichi city, Japan. The conventional system has covered only one route and have had reliability problems that communication is done incorrectly in rare cases, sometimes the bus position display is incorrect. Therefore, we decided to cover the entire city of Nonoichi with LoRa network and support all routes running in the city. We also considered adopting multi-channel communication and multiple gateways to improve the reliability of the system. In this article, we describe a multi-channel and multiple gateways scheme to improve reliability.

With the growth of the power grid, the distribution network, which is the end of the power grid, faces problems such as difficult fault location and labor shortages. This paper proposes a fault location algorithm based on the existing distribution network automation information system. The data for the fault location algorithm come from the equipment ledger, telemetry signals, fault location information system, and lightning location information system. Fault location algorithms include multi-interval optimal fault location algorithms and a combination of deep optimal search and breadth optimal search. A set of fault location systems is designed, and historical fault data are imported for experimental verification. The results show that the fault location system based on this algorithm has accurate system positioning and a fast response, which greatly reduces the time for fault finding.

This paper proposes the ability to estimate the origin-destination (OD) of bus passengers with IoT bus location system. This system detects the bus stops where passengers board and deboard the bus based on their feature amounts obtained by intelligently analyzing the video taken inside the bus, and estimates congestion level of bus and OD data. Moreover, we implemented and verified the mechanism for providing these estimated information to Synerex that is proposed as a mechanism for exchanging information about user demand and service provider supply.

In order to further improve the positioning accuracy of indoor positioning based on visible light communication, this paper proposes an RSS fingerprint database location algorithm based on Lambert optimization model, which significantly improves the positioning accuracy. The Internet of Things technology is used to realize the connection between devices and mobile phones, and the positioning information is transmitted to mobile phone clients in real time. To test this system, a visible light indoor positioning system based on STM32F407 development platform was built, which verified that the positioning error of the system was basically stable within 30 mm in the area of 800 mm * 800 mm. This system has stable signal transmission, high precision, small time consuming and low cost of power consumption, which has a good development and application value.

This paper performs a feasibility analysis to find the best-fitting solution in terms of quality/price ratio for designing and developing a Real-Time Location System for Indoor Positioning inside healthcare facilities. In particular, an overall comparison of all the available solutions is done, highlighting pros and cons of each technology (WiFi, RFID, WLAN, Ultra-Wide Band, Bluetooth Low Energy, ZigBee, magnetic fields, infrareds, ultrasounds, computer-vision and Pedestrian Data-Reckoning) for accuracy, price, coverage, infrastructure development and installation, and maintenance. A preliminary scope-review is also produced, which summarizes the obtained outcomes in similar studies. In the results section the proposed system is illustrated via flowcharts and block diagrams, both for off-site and on-site scenarios.

Research on Real-Time Location Systems (RTLS) for indoor environments establishes Bluetooth Low Energy as a promising technological low-cost solution for various environments. However, in indoor environments, there are numerous obstacles such as furniture, walls, partitions, etc. that will cause obstructions to Bluetooth signals. This research established the effect of Perspex on Bluetooth transmission in an indoor environment. This research extends on our previous research which evaluated RTLS technologies, RTLS constraints, and an energy efficient design model for sensor detection in indoor environments. Perspex was chosen for this research as it is used as a common shield used to minimize COVID transmission in an office environment. In general, the 3 mm and 5 mm Perspex did not have a significant impact on Bluetooth transmission.

In intelligent environments, one of the most common available input data is location. It can be easily captured with little additional infrastructure thanks to the ever-present smartphones or smartwatches that enable new opportunities and services in the field of pervasive computing and sensing. However, in some cases, such as in an elderly care context, it is useful to infer additional information, such as identifying unusual activities or abnormal behaviors of monitored users. In this paper, a system that uses location data to infer additional semantic information about a user's behavior is presented. The semantic location data can then be transformed into behavioral indicators that can be used to analyze the user's activities. In order to infer user activities, the proposed system requires a minimal infrastructure.

In this work, we proposed an indoor location system that makes use of a Raspberry Pi embedded computer and WiFi signals to guide a person inside a region of the faculty of Electrical and Electronic at Universidad Nacional de Ingenieria, Peru. The main advantage with similar indoor location systems like beacons or RFID technology is that the presented system does not require additional hardware since it makes use of the pre-installed WiFi routers. The experimental tests show promising results, achieving a location accuracy of 92.31%.

Existing indoor location systems do not easily scale at low cost while maintaining high accuracy. We present EasiTrack, an indoor tracking system that achieves decimeter accuracy using a single commodity WiFi Access Point (AP) under Non-Line-Of-Sight conditions and can deploy at scale with (almost) zero cost. We build a fully functional real-time system with a satellite-like architecture, which enables EasiTrack to support an unlimited number of clients. We have demonstrated EasiTrack in a number of different scenarios to track both humans and machines. The results reveal that EasiTrack achieves a decimeter median accuracy and a

The length of the single-phase line of the Sutong GIL tunnel is about 6km, and the length of a single gas chamber is about 100m. Because the GIL adopts a fully sealed design, it is difficult for the existing methods to accurately locate the fault when discharge and overheat faults occur during operation. In order to meet the long-distance fault location requirement of Sutong GIL, this paper analyzed the breakdown, propagation and attenuation characteristics of ultrasonic signals in GIL through test. The test results show that the frequency of the ultrasonic signal generated by breakdown should be distributed in the frequency of 40$\sim$60kHz, 100$\sim$150kHz, 230$\sim$250kHz and 500$\sim$530kHz. In addition, the attenuation of ultrasonic signal is 70% and 89% after passing through the gas chamber basin and expansion joint. Based on the above research results, this paper designed the configuration and parameters of the sensors, communication scheme and protection scheme of the long-distance GIL ultrasonic fault location system in detail, and verified the fault location function of the system through engineering app-cations.

This paper describes the prototype of an automatic system for real-time determination and with a precise geographical location of the weather conditions in the environment of the car in which it is installed. The system we made, which we named it the Real Time Weather Location System, uses multiple sensors to retrieve weather data that it transmits to a central server and displays on a map accurate information about the weather conditions in different areas. Our system system is useful for alerting the authorities for natural disasters, such as: floods, storms, massive snowfalls, etc. Given the widespread use of motor vehicles, our system can be a viable alternative to current weather monitoring systems with a direct impact on the safety of car traffic participants as well as residents. At the same time, we designed and built the Real Time Weather Location System so that it is accessible to a wide range of car owners. The future development of our system aims at its compatibility with the means of railway and naval transport.

The paper presents the results of modeling a combined radio communication and radar system using OFDM as a sounding signal. The main circuit and system solutions are considered, allowing to combine radio communication and radar into a multifunctional system.

People often spend time in buildings such as offices, hospitals, factory workspaces, and other interiors. Today, positioning and navigation are of great importance in such environments. Global Positioning System (GPS), which is commonly used for location information, cannot be used indoors. Therefore, we need the new technology of the real-time location system. In this research, the use of Bluetooth Low Energy (BLE) RSSI was investigated. The mathematical filters median, mod, max, mean were tried to ensure the accuracy of RSSI. A different triangulation algorithm was used to calculate the positioning. In the study, all calculations and algorithms have been tried in real environments and the results have been recorded. With this work, better algorithms for indoor positioning with BLE technology have been developed and the position accuracy has been improved.

As mobile devices are, highly adopted, indoor location tracking systems started to emerge. Companies can use these indoor location-tracking systems to better understand their customers and get an insight into their intentions and needs. In this paper, different indoor location tracking systems are evaluated. Since there are various evaluation perspectives, the problem is defined as a multi-criteria decision-making (MCDM) problem, and a decision model containing ten criteria, and five alternatives are formed. In this study, we use Interval Valued Type-2 Intuitionistic Fuzzy WASPAS method to solve the problem.

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.

The article deals with the issues of combining information in a two-position small-size radar system to improve the system's resolution when mapping the underlying surfaces in the front side view area. This radar system also serves to improve the accuracy of azimuthal coordinates of physical objects and information sensors detected in the view area. This information is used in the optical two-position system, located on the same small UAVs on which the small-size on-board radars are based, which allows the positioning of cameras on detected objects with high accuracy. The high precision positioning of the cameras allows the combination of the two-position optical system information and radar information. The result of this combination allows to clarify the coordinates of the edges of the underlying surfaces, in particular the coastal zone, as well as to improve the reliability of the classification of underlying surfaces and detected physical objects.

Ultra wide band (UWB)-based real-time location systems (RTLSs) have been widely adopted in the manufacturing industry for tracking tools, materials, and ensuring safety. Researchers in the construction domain have investigated similar uses for UWB-based RTLSs on construction jobsites. However, most of these investigations comprised small-scale experiments using average accuracy only to demonstrate use cases for the technology. Furthermore, they did not consider alternative deployment scenarios for practically feasible deployment of the technology. To overcome these limitations, a series of experiments were performed to study the feasibility of a commercially available RTLS on the construction jobsites. The focus of the work was on feasibility in terms of accuracy analysis of the system for a large experimental site, the level of effort requirements for deployment, and the impact of deployment alternatives on the accuracy of the system. The results found that average accuracy was found to be a misleading indicator of the perceived system performance (i.e., 95th percentile values were considerably higher than average values). Moreover, accuracy is significantly affected by the deployment alternatives. Collectively, the results arising from the study could help construction/safety managers in decision making related to the deployment of UWB-based RTLSs for their construction sites.

The problem of determining the object’s position has recently become an active research area, due to the increased demand for accurate outdoor and indoor positioning. This paper presents a preliminary testing campaign of the Decawave MDEK1001 development kit which uses UWB transmissions to determine the position of a tag in a real-time location system. The performance is evaluated in terms of positioning accuracy, and measurement error variation of the tag coordinates. The results analysis highlights the potential of the system and provides guidelines on how to increase the positioning accuracy.

In this work we proposed an indoor location system that makes use of a mobile phone and WiFi signal levels to determine the location of a person in the museum “Eduardo de Habich” at the Universidad Nacional de Ingenieria, Peru. Therefore, by determining the location, additional information such as recommendations, multimedia, an more could be shown to each user in order to have a better user experience. The main advantage with similar indoor location systems such as Beacons or RFID technology is that the proposed system does not require additional hardware as it only uses pre-installed WiFi hotspots. The experimental tests show promising results, achieving a location accuracy of 93.61%, which is useful for similar navigation tasks.

The paper deals with application possibilities of indoor RTLS (real-time location system) mobile robot navigation. The aim is to point out one of the possibilities of practical RTLS implementation in practice. The work describes the connection procedure between localization technology and the TurtleBot2 mobile robot in the ROS (Robot Operating system) environment. The first part of the work is focused on configuration of the selected RTLS technology, which works on the UWB (ultra-wideband) principle. The configuration as well as the subsequent location data acquisition are already implemented in ROS. The second part of the work deals with TurtleBot2 navigation based on the obtained location data. At the end of the paper are the results summarized obtained in the premises of a robotic laboratory.

Lightning discharges have been widely studied in many physical and engineering fields, being responsible for hazardous events such as human injuries, damages to transmission lines and wind turbines, wildfires ignitions and adverse impacts on the aviation sector. An improved understanding of the phenomenon is important for warning and safety applications, in order to perform reliable risk assessment to respond to impacts. The introduction of Lightning Location Systems (LLS) helped mitigating threats since 1920. This contribution is focused on LLSs for intra-cloud and cloud-to-ground discharges, aiming at presenting an overview on the working principles of the most used techniques to locate lightning. The companion paper will describe in detail the performances of the main LLS and present examples of some existing LLS networks, with particular attention to the ones that operate in the Mediterranean areas.

Analyzing and researching the levitation and guidance sensor fault location system of high-speed maglev train, we developed an offline testing method of sensor fault location system, which can carry on the fast positioning of sensor boards, and greatly improve the efficiency of maintenance. The research results have certain reference value for maintenance work of Shanghai maglev engineering demonstration line.

To improve detection performance of passive location system based on troposcatter, we propose a blind signal detection algorithm. According to our algorithm, complementary ensemble empirical mode decomposition decomposes the received signal into several intrinsic mode functions (IMFs). To reconstruct the signal and background noises, difference between the entropy of adjacent IMFs is utilized as a standard. Different IMFs are utilized to estimate threshold of energy detection algorithm and energy level of received signal. Simulation examples indicate that the proposed algorithm can blindly and effectively detect the signal.

The lightning location system in Anhui province are introduced. Under the environment of SQL Server 2005, lightning location system database is established, unifying the lightning location data storage form and promoting the application of lightning location data and its secondary development. In combination with Doppler radar products, lightning nowcasting warning system has been developed. Strengthened The live monitoring, nowcasting forecast of lightning and early warning products published through web benefit the public a lot and supply the reference for forecasters in the process of early warning signal production.