Use Of Global Positioning System Research Articles

SPATIAL DISTRIBUTION AND PATRONAGE OF RECREATIONAL FACILITIES IN UNIVERSITY OF ILORIN, NIGERIA

The paper examined the spatial distribution and patronage pattern of recreational facilities in the University of Ilorin (UNILORIN). The study used primary data, which were obtained through a structured questionnaire administered randomly to the selected academic and non - teaching staff of UNILORIN. Geo-spatial data on the locations of the recreational facilities were collected and analyzed with the use of Global Positioning System (GPS) and Nearest Neighbour Analysis respectively. Pearson’s Product Moment Correlation Analysis was employed to examine the relationship between residence and patronage of recreational facilities at 5% level of significance. With an Rn value of 1.47 (p=0.000378), the distribution of recreational facilities in UNILORIN was dispersed. The paper also observed that, there was no significant relationship between staff place of residence and their patronage of recreational facilities (r = 0.05, p value = 0.474). The study established that health benefits and pleasure with Enhancing Factor Index of 2.58 and 2.46 respectively, were the major enhancing factors of recreational facilities patronage. The paper concluded that locations of recreational facilities are far from each other and by implication the distribution is nor regular. The paper therefore recommended that future recreational facilities should be evenly distributed so as to foster more patronage by staff members of University of Ilorin.

SPATIAL DISTRIBUTION AND PATRONAGE OF RECREATIONAL FACILITIES IN UNIVERSITY OF ILORIN, NIGERIA

The paper examined the spatial distribution and patronage pattern of recreational facilities in the University of Ilorin (UNILORIN). The study used primary data, which were obtained through a structured questionnaire administered randomly to the selected academic and non - teaching staff of UNILORIN. Geo-spatial data on the locations of the recreational facilities were collected and analyzed with the use of Global Positioning System (GPS) and Nearest Neighbour Analysis respectively. Pearson’s Product Moment Correlation Analysis was employed to examine the relationship between residence and patronage of recreational facilities at 5% level of significance. With an Rn value of 1.47 (p=0.000378), the distribution of recreational facilities in UNILORIN was dispersed. The paper also observed that, there was no significant relationship between staff place of residence and their patronage of recreational facilities (r = 0.05, p value = 0.474). The study established that health benefits and pleasure with Enhancing Factor Index of 2.58 and 2.46 respectively, were the major enhancing factors of recreational facilities patronage. The paper concluded that locations of recreational facilities are far from each other and by implication the distribution is nor regular. The paper therefore recommended that future recreational facilities should be evenly distributed so as to foster more patronage by staff members of University of Ilorin.

Smartphone region-wise image indoor localization using deep learning for indoor tourist attraction.

Smart indoor tourist attractions, such as smart museums and aquariums, require a significant investment in indoor localization devices. The use of Global Positioning Systems on smartphones is unsuitable for scenarios where dense materials such as concrete and metal blocks weaken GPS signals, which is most often the case in indoor tourist attractions. With the help of deep learning, indoor localization can be done region by region using smartphone images. This approach requires no investment in infrastructure and reduces the cost and time needed to turn museums and aquariums into smart museums or smart aquariums. In this paper, we propose using deep learning algorithms to classify locations based on smartphone camera images for indoor tourist attractions. We evaluate our proposal in a real-world scenario in Brazil. We extensively collect images from ten different smartphones to classify biome-themed fish tanks in the Pantanal Biopark, creating a new dataset of 3654 images. We tested seven state-of-the-art neural networks, three of them based on transformers. On average, we achieved a precision of about 90% and a recall and f-score of about 89%. The results show that the proposal is suitable for most indoor tourist attractions.

GPS/BDS triple-frequency cycle slip detection and repair based on moving window global search method

Cycle slip detection and repair are crucial steps in achieving high accuracy in Global Navigation Satellite System (GNSS) data processing. The use of Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) triple frequency observations allows for more accurate detection and repair of cycle slips compared to single or dual frequency. This study presents a moving window global search method by selecting three sets of combined coefficients to construct geometry-free (GF) models to minimize the influence of the ionosphere, using a moving window to update the standard deviation of cycle slip estimation, applying the "3 σ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upsigma$$\\end{document}" criterion to constrain the range, and utilizing a global search method to detect and repair triple-frequency cycle slips. Through five sets of 1 Hz GNSS data experiments, the results demonstrate the effectiveness of this method in determining the position and size of triple-frequency cycle slips while avoiding multi-value problems. The detection success rate for GPS ranges from 98.0 to 100.0%, while BDS ranges from 92.0 to 100.0%. On average, GPS achieves a detection rate of 99.2%, and BDS reaches 96.7%, which is 0.8% and 1.8% higher than the direct rounding method, respectively. Compared to existing methods, it is also effective for the vast majority of small cycle slips within 2 cycles.

A framework for preventing unauthorized drone intrusions through radar detection and GPS spoofing

The increasing use of Global Positioning System (GPS)-based autonomous drones in various civilian and military applications has raised concerns about malicious or unintentionally harmful activities that can be carried through them. It is necessary to detect these intruding drones within protected areas and prevent their unauthorized access by denying them entry. We propose a framework that combines the detection of intruding drones using an L-band radar and then counters by transmitting fake GPS coordinates toward the drones, effectively redirecting them. This article explains the setup required to add to an existing monostatic radar that provides two-dimensional information, i.e., range and azimuth information, to enable the proposed setup to get the elevation angle of the drone. We propose a linear array design using digital receive-only beamforming techniques in the elevation domain to compute the elevation angle in addition to the range, velocity, and azimuth information being provided by the monostatic radar to get complete information about the intruding drone. The simulation of drone detection is followed by an examination of the impact of transmitting fabricated GPS coordinates to the drone. Experimental verification has been conducted to validate both the digital beamforming algorithm and the spoofing technique. This approach blocks the reception of actual GPS signals in the drone and replaces the drone's GPS coordinates with alternative, desired coordinates. The proposed framework can be used to prevent unauthorized drone intrusions in the protected area.

Monitoring Lokasi Komponen Alat Berat Berbasis Internet Of Things Pada PT. Thiess BSF Batakan

Abstract— In the digital era like today, every company is competing to innovate to reduce operational costs and increase productivity, one of which is PT. Thiess. Indirectly this also has an impact on the performance of every employee in the company to speed up and maximize work processes with minimal human resources without reducing aspects of occupational safety and health from both government regulations and company standards. As one of the employees who also acts as a researcher at PT. Thiess Balikpapan Support Facility (BSF), the researchers will discuss the problems in finding heavy equipment components. Based on the context of the difficulties described above, researchers will examine the use of Global Position System (GPS) technology. The process of making this prototype uses the NodeMCU ESP8266 microcontroller and GPSMV2 which also functions as a connection to the internet. The results of searching for GPS coordinates are made in the form of localhost using XAMPP, can be viewed in web form and forwarded to Google Maps.

A Study and Analysis of a New Hybrid Approach for Localization in Wireless Sensor Networks

Accurate localization of nodes in a wireless sensor network (WSN) is imperative for several important applications. The use of global positioning systems (GPS) for localization is the natural approach in most domains. In WSNs, however, the use of GPS is challenging because of the constrained nature of deployed nodes as well as the often inaccessible sites of WSN nodes deployment. Several approaches for localization without the use of GPS and harnessing the capabilities of the received signal strength indicator (RSSI) exist in literature, but each of these makes the simplifying assumption that all the WSN nodes are within the communication range of every other node. In this paper, we go beyond this assumption and propose a hybrid technique for node localization in large WSN deployments. The hybrid technique comprises a loose combination of a machine learning (ML) based approach for localization involving random forest and a multilateration approach. This hybrid approach takes advantage of the accuracy of ML localization and the iterative capabilities of multilateration. We demonstrate the efficacy of the proposed approach through experiments on a simulated set-up and follow it up with a feasibility demonstration through a prototypical implementation in the real world.

GPS-free synchronized pseudo-random number generators for internet-of-things

IntroductionSecuring wireless communications in internet-of-things (IoT) requires both generation and synchronization of random numbers in real-time. However, resource constraints on an IoT device limit the use of computationally intensive random number generators and the use of global positioning systems (GPS) for synchronization. In this paper, we propose a synchronized pseudo-random number generator (SPRNG) that uses a combination of a fast, low-complexity linear-feedback-shift-register (LFSR) based PRNG and a slow but secure, synchronized seed generator based on self-powered timers.MethodsA prototype synchronized self-powered timer (SSPT) array was fabricated in a standard silicon process and was used to generate dynamic random seeds for the LFSR. The SSPTs use quantum-mechanical tunneling of electrons to operate without any external power and are practically secure against tampering, snooping, and side-channel attacks (both power and electromagnetic).ResultsIn this work, we explore protocols to periodically and securely generate random bits using the self-powered timers for seeding the LFSR. We also show that the time-varying random seeds extend and break the LFSR periodic cycles, thus making it difficult for an attacker to predict the random output or the random seed. Using the National Institute of Standards and Technology (NIST) test suite we verify the randomness of the measured seeds from the fabricated ensemble of SSPTs together with the random bit sequences generated by a software-seeded LFSR.DiscussionsIn this modality, the proposed SPRNG could be used as a trusted platform module (TPM) on IoTs and used for verifying and authenticating secure transactions (e.g., software upgrades). Since the SPRNG system does not require access to GPS for synchronization, therefore it could be used in many resource-constrained and adversarial environments.

Spatial Analysis of Active Dumpsites Distribution Pattern in Port Harcourt Metropolis, Rivers State, Nigeria

The study analysed the distribution patterns of active dumpsites in Port Harcourt Metropolis, Rivers state, Nigeria. The study made use of locational data obtained through the use of Global Positioning System (GPS) and the data were subjected to analysis in ArcGIS environment. Nearest neighbour analysis was used to determine the significant distribution pattern. Findings showed that twenty-three active dumpsites were found in the entire Port Harcourt Metropolis and the distribution pattern of these dumpsites were significantly dispersed (Z=4225.54; p=0.0000). It is concluded that active dumpsites in Port Harcourt Metropolis are scattered all over and it is recommended that proper guidelines must be followed before an area can be sited to become a dumpsite. Also, there should be consideration of the environmental attributes so that the proportion of the effect can be minimized, while periodic monitoring of established dumpsites is essential to reduce the illegal siting of dumpsites.

Goats are able to adapt to virtual fencing; A field study in commercial goat herds on Norwegian farms

Virtual fencing technology has been developed over the last decades with the goal of giving farmers a flexible fence solution especially for remote rangeland. The latest technology is based on the use of Global Positioning System (GPS), mobile phone networks and internet applications. During the autumn of 2017 a field study was performed on eight commercial goat farms in Norway by using the Nofence virtual fencing technology. The main aim of the study was to describe the ability of goats to adapt to virtual fencing with three different sets of conditions. The first condition consisted of six groups with a total of 53 goats naïve to virtual fencing, that were introduced to and enclosed by a virtual fence. The second consisted of ten groups with a total of 92 goats already accustomed to virtual fencing being held on their regular pasture enclosed by a virtual fence. The third condition consisted of four groups with a total of 45 goats accustomed to virtual fencing that were moved to or given new rangeland areas enclosed by a virtual fence. All sets of conditions lasted for five days, and the number of audio cues and electric stimuli were automatically registered for all individual animals. A success ratio was calculated based on these measures. All variables were analyzed using a Generalized Linear Mixed Model with either a Poisson or Binomial distribution. The number of escapes were also registered. For the naïve goats, the mean number of audio cues and electric stimuli per goat were reduced from day one to day five, while the success ratio increased. On day one, 22 goats escaped whereas on day four and five no goats escaped. For the accustomed goats, the success ratio was significantly higher than that for the naïve goats, but not different from accustomed and moved. The total number of escapes in this condition was 7. For accustomed and moved, the success ratio was similar to the accustomed goats, but there was large variation across days, also in the number of audio cues. Escapes were only registered in one of the groups. We concluded that goats could adapt to and be confined by virtual fencing in commercial herds, but there were large individual variations as well as variation between groups regarding the number of audio cues and electric stimuli received.

A Data-Driven Method for Congestion Identification and Classification

Congestion detection is one of the key steps in reducing delays and associated costs in traffic management. With the increasing use of global positioning system (GPS)-based navigation, promising speed data are now available. This study used extensive historical probe data (year 2016) in Des Moines, Iowa. We used Bayesian change point detection to segment the speed signal and detect temporal congestion. The detected congestion events were then classified as recurrent congestion (RC) or nonrecurrent congestion (NRC). This paper thus presents a robust statistical, big-data-driven expert system and a big-data-mining methodology for identifying both recurrent and nonrecurrent congestion.

Energy Requirements and Nutritional Strategies for Male Soccer Players: A Review and Suggestions for Practice.

Soccer is a high intensity intermittent sport, featuring critical events completed at high/maximal intensity which is superimposed onto an aerobic base of lower intensity activities and rest. Due to these varying energic demands and the duration of competition the need for optimal nutritional strategies to offset and delay fatigue are paramount. Over the last 50 years, several investigations have been reported on aspects of soccer be they nutrition-focused or those concerning the demands of the sport. Emanating from these scientific papers, observations have been made on the likely factors which result in the fatigue during match-play. Factors such as muscle glycogen depletion and hypoglycaemia are discussed. Studies on the energy demands of soccer have employed a variety of methodologies which are briefly reviewed and vary between the use of heart rate telemetry to the use of global positioning systems (GPS). Moving on from observations of the energy demands of the sport leads to the major focus of this review which highlights key nutritional strategies to support the preparation and recovery of male soccer players to enhance performance, or at least to enable players to perform adequately. This review examines relevant methodologies in assessing training and competitive energy costs as well as the concomitant energy intakes demanded for successful performance outcomes. In order to bring an applied aspect to the overall findings from areas discussed, some practical ideas of feeding strategies are presented.

The analysis of Pangandaran fisherman’s actual usage level of GPS based on TAM model

A research domain that concentrates on looking at the interactions and phenomena between information technology and enterprise organizations. It is necessary to study the level of acceptance of the use of Global Positioning System (GPS) technology for fishermen. Therefore, this research was conducted on the use of GPS in the Pangandaran Regency using the Technology Acceptance Model (TAM). This study uses a quantitative approach. Meanwhile, the data collection technique used questionnaire survey techniques and interviews. Questionnaires were distributed to 4 sub-districts with a total of 50 respondents. Data analysis used a simple linear regression. The results showed that the 6 hypotheses tested positive. H6 has the strongest linear relationship than others with R2 is 0.780.

Fi-Vi: Large-Area Indoor Localization Scheme Combining ML/DL-Based Wireless Fingerprinting and Visual Positioning

Due to recent technological developments such as online navigation, augmented reality (AR), virtual reality (VR), and digital twins, and the high demand from users for various location-based services (LBS), research on location estimation techniques is being actively conducted. As a result, there is an increasing demand for effective localization technologies that can be used in places where the use of Global Positioning System (GPS) is limited, especially in indoor spaces with very large areas. In this paper, a new structure for an indoor localization system in which wireless fingerprinting and visual-based positioning are hierarchically combined—the so-called Fi-Vi system—is proposed. This scheme consists of two steps: fingerprint-based localization (FBL) followed by visual-based localization (VBL). In the first positioning step (i.e., the FBL stage), the entire area of a significantly broad range for localization is divided into multiple regions, the size and the number of which depend on the target accuracy of this step. Moreover, a machine-learning (ML) or deep-learning (DL) model trained on a Wi-Fi fingerprint radio map selects suitable candidate regions among these multiple regions. In the second positioning step (i.e., the VBL stage), the final location is precisely estimated through visual-based positioning based on the received information regarding the candidate regions. The FBL stage uses a sparse radio map (SRM) for fingerprinting, which can be constructed with relatively little effort and cost compared to radio maps used in conventional fingerprinting methods. As a result, it can be easily combined with existing visual-based positioning methods with almost negligible implementation complexity. Because of the hierarchical structure and SRM, the proposed scheme shows a significant performance improvement in terms of computational load and time required for indoor localization compared to the use of the existing visual-based indoor positioning method alone. In addition, it provides high accuracy and robustness even in a dynamically changing indoor wireless environment where conventional wireless fingerprinting methods show significant performance degradation. Finally, the performance analysis of the proposed scheme was performed using the UJIIndoorLoc dataset. Experiments and theoretical analysis have shown that when the estimation accuracy of the candidate region for the test dataset was achieved at about 99% through the FBL stage, the average computational amount of the VBL stage for the final position estimation was only about 16% of that in cases where the visual-based positioning method was used alone.

UKF-Based Inverted Ultra-Short Baseline SLAM With Current Compensation

This paper presents an inverted ultra-short baseline (iUSBL) simultaneous localization and mapping (SLAM) based on Unscented Kalman filter (UKF) with current compensation. The complexity of the underwater environment prevents the use of Global Positioning System (GPS) or visible-light cameras, thereby we rely on an acoustic positioning system to achieve autonomous underwater vehicle (AUV) navigation relative to the beacons. Our system considers using an AUV equipped with a time-synchronized iUSBL array to measure the range and angle between vehicle and acoustic beacons via one-way travel-time. Then, we propose UKF-based online SLAM to filter these acoustic measurements, meanwhile, add current compensation which is inherent underwater. In contrast, traditional SLAM applications usually contain a large number of landmarks, this iUSBL acoustic system only needs sparse beacons to estimate the vehicle pose. Consequently, it does not cause UKF to have an excessive computational burden. The validity of the proposed method is confirmed by numerical results. In particular, the proposed algorithm prevents cumulative errors from growing quickly quite well when using double beacons.

Decision rules for determining terrestrial movement and the consequences for filtering high-resolution global positioning system tracks: a case study using the African lion (Panthera leo).

The combined use of global positioning system (GPS) technology and motion sensors within the discipline of movement ecology has increased over recent years. This is particularly the case for instrumented wildlife, with many studies now opting to record parameters at high (infra-second) sampling frequencies. However, the detail with which GPS loggers can elucidate fine-scale movement depends on the precision and accuracy of fixes, with accuracy being affected by signal reception. We hypothesized that animal behaviour was the main factor affecting fix inaccuracy, with inherent GPS positional noise (jitter) being most apparent during GPS fixes for non-moving locations, thereby producing disproportionate error during rest periods. A movement-verified filtering (MVF) protocol was constructed to compare GPS-derived speed data with dynamic body acceleration, to provide a computationally quick method for identifying genuine travelling movement. This method was tested on 11 free-ranging lions (Panthera leo) fitted with collar-mounted GPS units and tri-axial motion sensors recording at 1 and 40 Hz, respectively. The findings support the hypothesis and show that distance moved estimates were, on average, overestimated by greater than 80% prior to GPS screening. We present the conceptual and mathematical protocols for screening fix inaccuracy within high-resolution GPS datasets and demonstrate the importance that MVF has for avoiding inaccurate and biased estimates of movement.

Water Resources and Management in Gori Ganga Watershed, Kumaun Himalaya by Using Remote Sensing and GIS

Uttarakhand Himalaya has been famous for its water resources (source for many rivers), forest diversity, unique wildlife, rich traditional culture, tribal culture and sacred Hindu’s shrine (i.e. Gangotri, Yamnotri, Kedarnath and Badrinath). The present study aims to assess the status of water resources in the Gori Ganga watershed. Water resources and their management were collected through field visit, use of Global Position System (GPS) and various methods (include questionnaire, personal interviews, direct interaction and group discussion with the villagers). Study explores the ability of Digital Elevation Model (DEM) in delineating watershed and drainage network of the Gori Ganga River basin. Gori Ganga watershed is laying in Eastern Kumaon Himalaya with great utility of water resources in socio-economic development for livelihood where the settlements are situated in valleys to high altitude. Gori Ganga drainage network i.e. Ralam, Mandakani and Bona gad is glacial fed river and these entire Rivers’s water received annually from glaciers which are very useful for development of villages, towns and hydro power stations in the watershed region. Study explores some traditional water resources (Glacier, streams, springs/Dhare/Naule, lakes/Kund/Taals and drainage network) and uses of water resources for traditional uses i.e. Gharat (watermill), drinking water, hydro power production, agriculture irrigation, fisheries and animal husbandry etc. in the study area. Keywords: Water Resource, Management, Socio and Economic Development, Remote Sensing and GIS.

Combining Global Positioning System (GPS) with saliva collection among sexual minority adults: A feasibility study.

BackgroundThis is the first study, of which we are aware, to evaluate the feasibility and accessibility of simultaneous use of Global Positioning System (GPS) and saliva collection for biomarker assessment as an objective measure of stress physiology among sexual minority (lesbian, gay, bisexual, queer, and other non-heterosexual identities) individuals. The principal motivation for pairing GPS and saliva collection was to investigate how characteristics of the built and social environments along with participants’ daily activity paths affect stress. This can contribute to a better understanding of health and health behaviors in the sexual minority community.MethodsA convenience sample of enrolled participants (N = 124) from Houston, Texas was asked to complete questionnaires, carry with them a GPS unit daily, and collect and store 6 samples of saliva at specific times across the span of a day prior to a second visit around one week later.ResultsOf 124 participants, 16 participants (12.90%) provided no useable GPS data and 98 (79.03%) provided at least 4 days of data. More than three-fourths (n = 98, 79.03%) also provided complete saliva samples.ConclusionsOur results show that the simultaneous use of GPS and saliva collection to assess sexual minority individuals’ activity paths and stress level is feasible.

Geospatial Assessment of the Impacts of Sand Mining Activities in Benin City, Edo State Nigeria

This study assessed the geospatial impacts of sand mining activities in Benin City, Edo State, Nigeria. There are thirty five (35) burrow pits in Benin and eleven (11) were used for the study. Similarly, three (3) distinct datasets and sources were used to determine the spatial extent of environmental degradation as a result of sand mining activities in Benin City. The first data set was the 19th January, 2019 satellite imagery of each of the mining sites. This high resolution remotely sensed data was used in the determination of areal extent of the sand mining sites. The second set of data was the Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) 30meters resolution digital elevation model (DEM). The ASTER-DEM was used as an input dataset in the determination of the volume of sand that have been mined in each site and compilation of three – dimensional model (3D Model) of each the sand mining site. The third set of data was the geographic coordinates of the mining sites. They were sourced from field survey with the use of global positioning system (GPS).The study concluded that sand mining and development cannot be entirely separated but mining should be done in a sustainable manner with less of environmental degradation. It is recommended that miners should be regularly sensitized by the government on environmental degradation and about the fragile nature of the environment. The government regulatory body should ensure that Environmental Impact Assessment (EIA) is carried before mining pits are approved for mining activities. Also illegal burrow pits should be short down to check environmental degradation.

High precision positioning system for autopilot based on multi-sensor fusion

For autonomous vehicles, autonomous positioning is a core technology in their development. A good positioning system not only helps them efficiently complete autonomous operations, but also improves safety performance. At present, the use of global positioning system (GPS) is a more mainstream positioning method, but in indoor, serious shelter and other environments, GPS signal loss will lead to positioning failure. In order to solve this problem, this paper proposes a method of mapping before positioning, and designs a set of high precision real-time positioning system by combining the technology of multi-sensor fusion. The designed system was carried on a Wuling sightseeing bus, and the mapping and positioning tests were carried out in the Nanhu Campus of Wuhan University of Technology, the East Campus of Mafangshan Campus and the underground garage where GPS signals were lost. The test results show that the system can realize the high precision real-time positioning function of the autonomous vehicle. Therefore, the in-depth study and implementation of this system is of great significance to the promotion and application of the automatic driving industry.