Location System Research Articles

Enhancing Fault Identification, Classification and Location Accuracy in Transmission Lines

This research paper presents a proposed system for fault identification, classification and location in transmission lines using a Support Vector Machine (SVM)-based technique in conjunction with a Positive Sequence Analyzer. The objective is to develop an accurate and reliable method for identifying, classifying and locating different fault types in transmission lines. The proposed system leverages the capabilities of SVMs in handling high-dimensional feature spaces and the fault signature extraction capabilities of the Positive Sequence Analyzer. Experimental evaluations are conducted to assess the performance and effectiveness of the proposed system, comparing it with existing fault identification and classification methods. The results demonstrate the superior performance and robustness of the SVM-based technique utilizing the Positive Sequence Analyzer, providing a valuable contribution to fault management and system reliability in transmission line networks.

MLLoc: Machine Learning Location System Based on RAIM in Mobile Networks

MLLoc: Machine Learning Location System Based on RAIM in Mobile Networks

Automatic Localization of Soybean Seedlings Based on Crop Signaling and Multi-View Imaging.

Soybean is grown worldwide for its high protein and oil content. Weeds compete fiercely for resources, which affects soybean yields. Because of the progressive enhancement of weed resistance to herbicides and the quickly increasing cost of manual weeding, mechanical weed control is becoming the preferred method of weed control. Mechanical weed control finds it difficult to remove intra-row weeds due to the lack of rapid and precise weed/soybean detection and location technology. Rhodamine B (Rh-B) is a systemic crop compound that can be absorbed by soybeans which fluoresces under a specific excitation light. The purpose of this study is to combine systemic crop compounds and computer vision technology for the identification and localization of soybeans in the field. The fluorescence distribution properties of systemic crop compounds in soybeans and their effects on plant growth were explored. The fluorescence was mainly concentrated in soybean cotyledons treated with Rh-B. After a comparison of soybean seedlings treated with nine groups of rhodamine B solutions at different concentrations ranging from 0 to 1440 ppm, the soybeans treated with 180 ppm Rh-B for 24 h received the recommended dosage, resulting in significant fluorescence that did not affect crop growth. Increasing the Rh-B solutions reduced crop biomass, while prolonged treatment times reduced seed germination. The fluorescence produced lasted for 20 days, ensuring a stable signal in the early stages of growth. Additionally, a precise inter-row soybean plant location system based on a fluorescence imaging system with a 96.7% identification accuracy, determined on 300 datasets, was proposed. This article further confirms the potential of crop signaling technology to assist machines in achieving crop identification and localization in the field.

Applicability of a radiant-capacitive cooling and heating system in its cooling mode in Köppen-Geiger's A, B and C climate types

This study presents indoor temperature predictions of a novel radiant-capacitive cooling and heating system developed and tested in its cooling mode for ten locations within the latitude range 37.42°N and 12.4°S with annual Cooling Degree-Days (CDD, using the upper limit of the adaptive comfort range as base temperature) ranging between 657 and 1818 CDD. The system was tested experimentally in Curitiba, Brazil. Based on field data, predictive formulas were generated for the minimum, average and maximum indoor temperatures solely using outdoor temperatures as predictors. The aim was to assess the cooling potential and system performance of system in locations with climate types distinct from Curitiba's. The night-time radiative cooling potential was evaluated in each city in terms of sky temperature depression (DTsky, given in Kelvin-hour, Kh). The annual totals of DTsky ranged between 270 Kh and 2269 Kh for the evaluated cities. The system's performance was assessed in terms of offsets of the maximum and average indoor temperature relative to outdoors, and of percent reductions in CDD. Indoor temperature depressions reach mean values of up to 5.7 K and 5.8 K in cities with the highest nocturnal radiative cooling potentials, while the lowest average temperature depressions were observed in locations with the lowest cooling potential. Results show potential reductions of the indoor average temperature ranging between 1.3 K and 2.2 K, with a corresponding CDD offset ranging between 72.1 % and 95.3 %.

Multi-criteria optimal sizing and analysis of PV/wind/fuel cell/battery/diesel generator for rural electrification: A case study in Chad

Access to sustainable, clean, affordable, and reliable electricity is crucial for social and economic development, yet Sub-Saharan Africa (SSA) struggles significantly in this context. In CHAD, only 11.3% of the population is able to access electricity, making it one of the least electrified countries in SSA with the lowest clean energy access. In rural areas, electricity access falls to just 1.3%. This research applies and executes a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm using MATLAB R2023b to assess the techno-economic, environmental, and social impacts of a hybrid system based on optimal PV/Wind/Battery/Fuel Cell (FC)/Diesel generator (DG) sizing for rural electrification in CHAD. The proposed system's self-sufficiency index (SSSI) and the Annualized System Cost (ASC) were chosen as objective functions to guarantee the economic feasibility of the system, higher self-sufficiency, and lower dependence on external energy sources (DG). The simulation results show that the optimal size of the proposed system supplies the load demand by 100% of the renewable energy sources (RES) fraction, and the optimal capacities of the main components to supply the load demand are: Solar Power (493 KW), Wind Turbine (166 KW), Battery Energy Charge/Discharge (229180 kWh /221300 kWh), Hydrogen tank storage energy (83 874 kWh), Electrolyzer size (202 KW), Fuel cell size (144 KW). The evelized cost of electricity (LCOE) of 0.2982 $/kWh, which is 51.12% lower than the national unit production costs of electricity in rural areas of CHAD (0.61 $/kWh). This LCOE is also the lowest compared to previous works done using HOMER Pro for the country of CHAD. The results also give a levelized cost of hydrogen (LCOH) of 3.8563 US $/kg, lower than for all studies found in the literature for the country of Chad. The proposed system's yearly avoided greenhouse gas (GHG) emission is 374 640 kg. The proposed system will create five (5) new jobs (JCO) and improve the Human Development Index (HDI) of the study area by 17.66% (the obtained HDI is 0.4683, and the CHAD HDI is 0.398) with an SSSI of 51.14%. This study provides a better practical energy design tool in decision-making for designers, companies, investors, policymakers, and the Chadian government when implementing this type of system in particular rural locations.

Assessing Household Catastrophic Healthcare Expenditure and its Associated Factors: A Study in a North-Eastern State of India

Background: Out-of-pocket expenses (OOPE) are the primary means of funding healthcare costs in developing nations, and when the cost is too high, it leads to catastrophic healthcare expenditures (CHE). Aim & Objective: This study aimed to assess the proportion of households that faced CHE and also examined the associated factors that determine CHE at the household level. Methods and Material: Between September 2020 and February 2021, a cross-sectional study covering a sample of 771 households was conducted in four districts of Assam. A multistage sampling design was employed to select the sample households. Statistical analysis used: Binary logistic regression analysis has been performed to ascertain the factors that could determine household CHE. Results: 23% households had experienced CHE, high dependence on the private healthcare system. Monthly household income, duration of illness, presence of children under five years of age and elderly members, education of household head, and health insurance were the significant factors influencing CHE. Conclusions: The study identified the growing use of private healthcare services as a major concern that contributes to the prevalence of CHE. To make all healthcare services accessible and affordable and to lower OOP on healthcare, it is also crucial to improve the infrastructure and quality of the public healthcare system in rural and remote locations.

Frugal random exploration strategy for shape recognition using statistical geometry

Very distinct strategies can be deployed to recognize and characterize an unknown environment or a shape. A recent and promising approach, especially in robotics, is to reduce the complexity of the exploratory units to a minimum. Here, we show that this frugal strategy can be taken to the extreme by exploiting the power of statistical geometry and introducing different invariant features. We show that an elementary robot devoid of any orientation or location system, exploring randomly, can access global information about an environment such as the values of the explored area and perimeter. The explored shapes are of arbitrary geometry and may even nonconnected. From a dictionary, this most simple robot can thus identify various shapes such as famous monuments and even read a text. Published by the American Physical Society 2024

Wave Basin Tests of a Multi-Body Floating PV System Sheltered by a Floating Breakwater

The development of floating photovoltaic systems (FPV) for coastal and offshore locations requires a solid understanding of a design’s hydrodynamic performance through reliable methods. This study aims to extend insights into the hydrodynamic behavior of a superficial multi-body FPV system in mild and harsh wave conditions through basin tests at scale 1:10, with specific interest in the performance of hinges that interconnect the PV panels. Particular effort is put into correctly scaling the elasticity of the flexible hinges that interconnect the PV modules. Tests of a 5 × 3 FPV matrix are performed, with and without shelter, by external floating breakwater (FBW). The results show that the PV modules move horizontally in the same phase when the wave length exceeds the length of the FPV system, but shorter waves result in relative motions between modules and, for harsh seas, in hinge buckling. Relative motions suggest that axial loads are highest for the hinges that connect the center modules in the system and for normal wave incidence, while shear loads are highest on the outward hinges and for oblique incidence. The FBW reduces hinge loads as it attenuates the high-frequency wave energy that largely drives relative motions between PV modules.

Impact of space systems capabilities and their role as critical infrastructure

The cyber domain has led to growth in current satellite capabilities, which have become essential due to the increased use of both civil and military critical infrastructure (CI) management systems. In recent decades, outer space has proven to be an increasingly critical sector for the international management of commercial CI, with private operators acting on both multi- and transnational levels. However, the space domain is characterised by not only opportunities but also risks and threats. As the security implications of space were not sufficiently considered at the beginning of the space era, some of the predominant risks currently extend into the commercial sphere. These risks must be considered to ensure the resilience of connected CIs in outer space. Security is a vital issue in the cyber and space domains and should be considered in every phase of a space system's life cycle, from the development and manufacturing of space assets to their deployment and end of life. This involves CI in several sectors, each of which exhibits different but interrelated risks. For example, telecommunications and location systems increasingly require the use of CI, which creates a fragile interdependence that is extremely vulnerable to threats. This paper underlines the importance of recognising space systems as CI and emphasises the need for a better integration of these assets in a system-of-systems analysis. The consequences of global satellite disruption on terrestrial CI are used to support this view. In such a disruptive scenario, mitigation measures based on in-orbit servicing or responsive space capabilities, for example, would allow CI to be restored to first ensure national security followed by commercial activities. Moreover, this paper provides an overview of the legal and policy aspects of using space systems’ capabilities in CI to better understand their implications and encourage the development of recommendations.

LoRa Based Emergency Communication System

The location and human activity are usually used as one of the important parameters to monitor the health status in healthcare devices. However, nearly all existing location and monitoring systems have the limitation of short-range communication and high power consumption. In this project, we propose a new mechanism to collect and transmit monitoring information based on LoRa technology. The monitoring device with sensors can collect the real-time activity and location information and transmit them to the cloud server through IOT. The user can check all his history and current information through the specific designed mobile applications. Experiment was carried out to verify the communication, power consumption and monitoring performance of the entire system. This system can collect monitoring and activity information accurately and provide the long rang coverage with low power consumption. Index Terms—Lora, Forest, temperature, humidity, soil moisture

IOT Based Smart Bus Transportation

The developed IoT-based smart bus health monitor- ing system is expected to bring back the neat service and safety of public transportation at the rate of modern technology that will keep the track of information regarding bus condition. ITS (Intelligent transport systems) are comprised of sensor technolo- gies and communication systems that connect on-board terminal, the vehicular systems, and ’fixed location systems. This modus operandi of ICT (f information and communication technologies ) also encompasses problems of rail, air, and water transport apart from road transport. IoT can be used to support the betterment of public transportation; hence, the transportation systems can become more receptive and more efficient. This entails the live tracking, amount analysis, and user friendly interfaces which helps the commuter to have trustworthy information along with a superior transportation experience. Index Terms—Telemetry, Emergency alarm, mpu6050,GPS sen- sor , Accelerometer, RFID card, Load sensor.

Identification of cloud-to-ground lightning and intra-cloud lightning based on their radiated electric field signatures using different types of neural networks and machine learning classifiers

The scope of this paper is to test the efficiency of three different neural networks in the area of cloud-to-ground/intra-cloud lightning classification using a not very large data set of electric field data. Effective neural network learning verified for a small lightning event dataset but with whole 2-seconds particular record length is an important feature of fast and efficient procedures implemented into lightning location systems among which discrimination between cloud-to-ground and intra-cloud lightning is one of the most important task. Measurement data obtained at the Lightning Observatory in Rzeszow were used for the analysis. About 100 extremely low/medium frequency bandwidth electric field of cloud-to ground lightning registrations and the same number of intra-cloud lightning events were taken into account. During the study 81% of those registrations were dedicated for learning of neural networks while the remaining 19% were put into the testing set. All data were preselected manually with consideration of the electric field variation and information from the lightning location system database. Lightning events were selected uniformly with the well-pronounced presence of their basic components and reported distance to the registration station which ensured a wide variation of expected lightning electric field signatures. The multilayer perceptron neural network, the radial basis function neural network and the convolutional neural network were tested and compared in different configurations while distinguishing lightning. The results were compared with other conventional classification approaches, such as traditional machine learning methods as well as one a little more contemporary architecture, the long short-term memory neural network. The multilayer perceptron neural network achieved the best detection accuracy overall. Presented research is an extension of lightning identification studies available so far mainly based on the convolutional neural network by the results achieved using the multilayer perceptron neural network, the radial basis function neural network, the long short-term memory neural network and several machine learning-based classification methods.

Pinpointing pigs: performance and challenges of an ultra-wideband real-time location system for tracking growing-finishing pigs under practical conditions

Real-Time Location Systems (RTLSs) are promising precision livestock farming tools and have been employed in behavioural studies across various farm animal species. However, their application in research with fattening pigs is so far unexplored. The implementation of these systems has great potential to gain insight into pigs’ spatial behaviour such as the use of functional areas and pigs’ proximity to each other as indicators for social relationships. The aim of this study was therefore to validate the accuracy, precision, and data quality of the commercial Noldus Information Technology BV TrackLab system. We conducted different measurement sets: first, we performed static measurements in 12 pens at four different locations in each pen at three heights each using a single ultra-wideband tag (UWB). We recorded unfiltered x- and y-coordinates at 1 Hz. We repeated these measurements with six tags aligned in a 2 × 3 grid with varied spacing to test interference between the tags. We also tested dynamic performance by moving the tags along the centre line of the pens. Finally, we measured the data quality with 55 growing pigs in six pens, including the identification of location 'jumps' from the inside to the outside of the pen. Each pen housed ten animals fitted with a UWB tag attached to their farm ear tag. We collected data for 10 days and analysed seven 24-h periods of raw and filtered data. The mean accuracy of the RTLS measurements was 0.53 m (precision: 0.14 m) for single and 0.46 m (precision: 0.07 m) for grouped tags. Accuracy improved with increasing measurement height for single tags but less clearly for grouped tags (P [height single] = 0.01; P [height grouped] = 0.22). When tags were fitted to animals, 63.3% of the filtered data was lost and 21.8% of the filtered location estimates were outside the pens. Altogether, the TrackLab system was capable of fairly accurate and precise assignment of the functional areas where individual animals were located, but was insufficient for the analysis of social relationships. Furthermore, the frequent occurrence of gaps in signal transmission and the overall high data loss rates presented significant limitations. Additionally, the challenging hardware requirements for attaching sensors to the animals underline the need for further technological advances in RTLS for the application with growing-finishing pigs.

Analysis of within-pen and between-pen fenceline temporal contact networks in confined feedlot cattle

Though contact networks are important for describing the dynamics for disease transmission and intervention applications, individual animal contact and barriers between animal populations, such as fences, are not often utilized in the construction of these models. The objective of this study was to use contact network analysis to quantify contacts within two confined pens of feedlot cattle and the shared “fenceline” area between the pens at varying temporal resolutions and contact duration to better inform the construction of network-based disease transmission models for cattle within confined-housing systems. Two neighboring pens of feedlot steers were tagged with Real-Time Location System (RTLS) tags. Within-pen contacts were defined with a spatial threshold (SpTh) of 0.71 m and a minimum contact duration (MCD) of either 10 seconds (10 s), 30 seconds (30 s), or 60 seconds (60 s). For the fenceline network location readings were included within an area extending from 1 m on either side of the shared fence. “Fenceline” contacts could only occur between a steer from each pen. Static, undirected, weighted contact networks for within-pen networks and the between-pen network were generated for the full study duration and for daily (24-h), 6-h period, and hourly networks to better assess network heterogeneity. For the full study duration network, the two within-pen networks were densely homogenous. The within-pen networks showed more heterogeneity when smaller timescales (6-h period and hourly) were applied. When contacts were defined with a MCD of 30 s or 60 s, the total number of contacts seen in each network decreased, indicating that most of the contacts observed in our networks may have been transient passing contacts. Cosine similarity was moderate and stable across days for within pen networks. Of the 90 total tagged steers between the two pens, 86 steers (46 steers from Pen 2 and 40 steers from Pen 3) produced at least one contact across the shared fenceline. The total network density for the network created across the shared fenceline between the two pens was 17%, with few contacts at shorter timescales and for MCD of 30 s or 60 s. Overall, the contact networks created here from high-resolution spatial and temporal contact observation data provide estimates for a contact network within commercial US feedlot pens and the contact network created between two neighboring pens of cattle. These networks can be used to better inform pathogen transmission models on social contact networks.

Design and performance evaluation of an off-grid hybrid solar system in a remote location: A case study of Legundi Island

Legundi Island, located in Lampung Bay, Indonesia, has high solar energy potential but still relies on Diesel Power Plants. This research aims to design a hybrid Solar Power Plant and Diesel Power plant system that is environmentally friendly and reliable. Analysis was conducted using the Homer software.•This research designs a hybrid Solar Power Plant system with a capacity of 170.2 kWp and a battery of 1,036 kWh, integrated with three existing Diesel Power Plants units with a capacity of 200 kW.•This system can generate electricity of 296,391 kWh/year with a renewable energy fraction reaching 79.9% and an electricity surplus of 0.988%.•Fuel consumption decreased by 79.3% compared to the existing Diesel Power Plant system.

ТРАНСПОРТНЫЕ КОРИДОРЫ МЕЖДУ ЮГОМ ДАЛЬНЕВОСТОЧНОГО ФЕДЕРАЛЬНОГО ОКРУГА И СЕРВЕРО-ВОСТОЧНЫМ КИТАЕМ: ПРОСТРАНСТВЕННЫЙ АНАЛИЗ РАЗМЕЩЕНИЯ

This article presents s study of the spatial system of location of transport corridors between the south of the Far Eastern Federal District and Northeast China. On this basis, the specifics of its functioning are clarified. The importance of various categories of transport corridors in connecting communications between Russia and China have been determined. Territorial reserves for the development of the cross-border transport network of these countries has identified.

Critical Design Considerations on Continuous Frequency Modulation Localization Systems

Real-time locating systems (RTLSs) suffer from clock synchronization inaccuracy among their distributed reference nodes. Conventional systems require periodic time synchronization and typically necessitate a two-way ranging (TWR) clock synchronization protocol to eliminate their measurement errors. Particularly, frequency-modulated continuous-wave (FMCW) time-based location systems pose unique design considerations on the TWR that have a significant impact on the quality of their measurements. In this paper, a valid operation design diagram is proposed for the case of an FMCW time-based TWR synchronization protocol. The proposed diagram represents an intersection area of two boundary curves that indicate the functionality of the system at a given frequency bandwidth, spectral length, and clock synchronization ambiguity. It presents an intuitive illustration of the measurement’s expected accuracy by indicating a larger intersection area for relaxed design conditions and vice versa. Furthermore, the absence of a working condition can easily be detected before proceeding with the actual system development. To demonstrate the feasibility of the proposed diagram, four scenarios with different design constraints were evaluated in a Monte-Carlo model of a basic TWR system. Moreover, an experimental measurement setup demonstrated the validity of the proposed diagram. Both the simulation and experimental outcomes show that the indicated valid conditions and the distribution of the measurements’ accuracy are in very good agreement.

Fault Detection and Diagnosis in Electric Vehicle Systems using IoT and Machine Learning: A Support Vector Machine Approach

This research examines blame discovery and determination in electric vehicle (EV) frameworks utilizing Internet of Things (IoT) information and machine learning calculations, centring on a Support Vector Machine (SVM) approach. The study points to improving the unwavering quality and security of EV operations by precisely recognizing and diagnosing flaws in real time. The test comes about illustrates the adequacy of the SVM-based approach, with an exactness of 95%, accuracy of 94%, review of 96%, and F1-score of 95%. Comparative investigation with elective calculations such as k-Nearest Neighbors, Decision Tree, and Random Forest underscores the predominant execution of SVM in blame discovery and determination. The SVM calculation shows negligible misclassifications over distinctive blame classes, highlighting its strength and viability. This inquiry contributes to the headway of blame location strategies in EV frameworks and gives profitable bits of knowledge into the commonsense usage of machine learning strategies for improving framework unwavering quality. Moving forward, the discoveries clear the way for assist investigations in optimizing blame location systems and expanding their appropriateness to other spaces such as mechanical mechanization and renewable vitality frameworks.

Influence of lightning current waveforms of cloud-to-ground lightning with multi-return strokes on the lightning withstand level of 500 kV transmission lines

The most common factor causing line tripping is lightning strokes, and it is necessary to conduct research on the lightning withstand level (LWL). The statistical results of lightning location systems (LLS) in various regions of China indicate that the total proportion of cloud-to-ground lightning with multi-return strokes in nature is 30% to 50%. The traditional method of lightning protection design for 500 kV lines based on the current waveform of single lightning strokes is no longer enough to effectively protect existing transmission lines. Therefore, in this paper an electromagnetic transient simulation model for 500 kV lines was established, to compare the LWL difference between single and multiple lightning strokes. The influence of the tower height, the grounding resistance, and the lightning current waveforms are all simulated and discussed. It is found that the back flashover LWL of 500 kV lines is significantly influenced by the lightning current waveforms. Meanwhile, reducing the grounding resistance cannot effectively increase the LWL of 500 kV lines when the tower is too high and the rise time of the lightning current is too short. It is proposed that the lightning current waveforms should be fully considered while calculating the LWL of 500 kV lines, both single and multiple lightning currents, providing a reference for practical engineering construction.

Social network analysis to predict social behavior in dairy cattle

Dairy cattle are frequently housed in free stalls with limited space, impacting social interactions between individuals. Social behavior in dairy cattle is gaining recognition as a valuable tool for identifying sick animals, but its application is hampered by the complexities of analyzing social interactions in intensive housing systems. In this context, precision livestock technologies present the opportunity to continuously monitor dyadic spatial associations on dairy farms. The aim of this study is to evaluate the accuracy of predicting social behavior of dairy cows using social network analysis. Daily social networks were built using the position data from 149 cows over 14 consecutive days of the study period. We applied the separable temporal exponential random graph models to estimate the likelihood of formation and persistence of social contacts between dairy cows individually and to predict the social network on the subsequent day. The correlation between the individual degree centrality values, the number of established social contacts per individual, between the predicted and observed networks ranged from 0.22 to 0.49 when the structural information from network triangles was included in the model. This study presents a novel approach for predicting animal social behavior in intensive housing systems using spatial association information obtained from a real-time location system. The results indicate the potential of this approach as a crucial step toward the larger goal of identifying disruptions in dairy cows expected social behavior.