Global Positioning System Coordinates Research Articles

Assessment of Noise Level and Distribution from Socotherm Nigeria Limited: Its Health Implications on the Workers

Exposure to noise for a long period of time has been an issue of concern to occupational health workers. This study investigated noise pollution level (NPL) and its spatial distribution in Socotherm Nigeria Limited coating plants and its effects on the health of the workers. Six sampling points were selected on the grounds of intensity of activities. A digital sound level Metre-Extech 407730 was used to measure noise level at the sampling points namely, application area, welding spot, aggregate separator, generator/powerhouse, impingement plant, bushing area. A global positioning system (GPS)-NAVA 300 was used to record the GPS coordinates of the sampling noise hotspots in the factory. The Arc GIS software was used to interpolate the spatial distribution of noise within the factory for the working periods which include morning, afternoon and evening. With a wellconstructed questionnaire, results of the health implication of workers exposure to noise from the factory were recorded. Results revealed that afternoon has the highest noise level of 99.20 dB(A) at welding point and application area conveyor of the factory while the lowest noise was observed at 85.20 dB(A) which was at cold spot of chemical feed area of the factory. The study observed that majority of the machines (noise hotspots) produce noise that was above Occupational Safety and Health Association (OSHA) permissible noise level. This study therefore recommends that workers be encouraged to use personal protective equipment and be educated regarding noise induced hearing loss and other non-auditory effects of noise exposure. The factories should adopt and implement hearing conservation programs under the direction of an occupational and environmental health professional.

Kinematic and Dynamic Vehicle Model-Assisted Global Positioning Method for Autonomous Vehicles with Low-Cost GPS/Camera/In-Vehicle Sensors.

Real-time, precise and low-cost vehicular positioning systems associated with global continuous coordinates are needed for path planning and motion control in autonomous vehicles. However, existing positioning systems do not perform well in urban canyons, tunnels and indoor parking lots. To address this issue, this paper proposes a multi-sensor positioning system that combines a global positioning system (GPS), a camera and in-vehicle sensors assisted by kinematic and dynamic vehicle models. First, the system eliminates image blurring and removes false feature correspondences to ensure the local accuracy and stability of the visual simultaneous localisation and mapping (SLAM) algorithm. Next, the global GPS coordinates are transferred to a local coordinate system that is consistent with the visual SLAM process, and the GPS and visual SLAM tracks are calibrated with the improved weighted iterative closest point and least absolute deviation methods. Finally, an inverse coordinate system conversion is conducted to obtain the position in the global coordinate system. To improve the positioning accuracy, information from the in-vehicle sensors is fused with the interacting multiple-model extended Kalman filter based on kinematic and dynamic vehicle models. The developed algorithm was verified via intensive simulations and evaluated through experiments using KITTI benchmarks (A project of Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago) and data captured using our autonomous vehicle platform. The results show that the proposed positioning system improves the accuracy and reliability of positioning in environments in which the Global Navigation Satellite System is not available. The developed system is suitable for the positioning and navigation of autonomous vehicles.

How Users of a Smartphone Weather Application Are Influenced by Animated Announcements Conveying Rainfall Intensity and Electronic Gifts Promoting Rain Evacuation

In this study, we assumed that animated announcements that conveyed rainfall intensity of localized heavy rain and the distribution of electronic gifts to encourage rain evacuation would promote evacuation actions. If evacuation actions could be promoted through these methods, then the transmission of weather information could be improved. Therefore, we modified the features of a weather information application for smartphones, which was already widely used, and conducted a demonstrative experiment with application users who agreed to participate in order to check the validity. We analyzed users’ behaviors by transmitting information regarding the predicted start time of rain and recording the Global Positioning System coordinates of the users’ smartphones. In addition, a questionnaire survey was administered to the users after the experiment to collect data on their conception of rainfall intensity. The participants were also interviewed. The results of the experiment showed a significant difference in user conception of rainfall intensity depending on whether they had viewed the animation. However, a behavior analysis based on location data showed no statistical bias in the relationship between the animation and rain evacuation behavior.

Intelligent Agent Technology for Cellular-Assisted GPS Positioning using Bayesian and Self-Organizing Map

This paper presents the use of intelligent agent technology, cellular-assisted Global Positioning System (GPS) and data mining for positioning purpose. Due to overlapping coverage areas of cell towers, conventional cell-based positioning techniques have been reported to be inaccurate. Current cell-assisted GPS positioning setup with high accuracy is costly as it requires huge investments on hardware deployments. A new solution of using intelligent agent technology was proposed by the authors for an economical and satisfactory cell-assisted GPS positioning system. Location information in the form of cell identity (ID) and GPS coordinates pairs can be acquired via devices such as smart phones and GPS trackers. The cell ID-GPS coordinates pairs are then grouped by each individual cell ID. An intelligent agent equipped with data mining capabilities is then deployed to computer the optimal GPS coordinates of the cell ID to provide more precise location information. The proposed solution was evaluated via a prototype system. The system was built to collect raw data of cell-ID and GPS coordinate pairs from trackers and mobile phone applications. Using the reference GPS coordinate that was calculated by taking the mean of longitude and mean of latitude for all the GPS coordinates clustered in the same group, the geographical distance between each GPS coordinate and the reference GPS coordinate in the same group was computed to evaluate the performance of the proposed solution.. Experimental results showed that the proposed solution based on intelligent agent equipped with data mining capability helped in improving the prediction of location with sub-kilometer accuracy, in contract to the conventional cell-assisted GPS positioning system which have low accuracy with distance rate various in kilometers.

A new 3D laser-scanning and GPS combined measurement system

Terrestrial laser scanning (TLS) is widely used because of its ability to quickly acquire high-density and high-precision 3D image and topographic data. However, it can only acquire independent coordinate system points, which restricts its application in large-scale deformation monitoring. In this study, we constructed a measurement system to acquire global coordinate point cloud data by combining TLS and GPS (Global Positioning System). The coordinate values of retro-reflective targets could be acquired in different coordinate systems, the GPS coordinate and the TLS station coordinate, synchronously. Our experiments showed that, after registration with the homonymy points acquired by 30-min short-baseline differential GPS using the ICP algorithm, the positional accuracy of the TLS retro-reflective target center in the global coordinate was better than 10 mm. This high precision meets, for instance, the requirements of coal mining subsidence monitoring. We used our new combined measurement system to acquire and process the point cloud data of a frame structure. The measurements demonstrated the practicability and robustness of the new measurement system.

Reliability of the 6-minute walking test smartphone application.

Objective functional measures such as the 6-minute walking test (6WT) are increasingly applied to evaluate patients with degenerative diseases of the lumbar spine before and after (surgical) treatment. However, the traditional 6WT is cumbersome to apply, as it requires specialized in-hospital infrastructure and personnel. The authors set out to compare 6-minute walking distance (6WD) measurements obtained with a newly developed smartphone application (app) and those obtained with the gold-standard distance wheel (DW). The authors developed a free iOS- and Android-based smartphone app that allows patients to measure the 6WD in their home environment using global positioning system (GPS) coordinates. In a laboratory setting, the authors obtained 6WD measurements over a range of smartphone models, testing environments, and walking patterns and speeds. The main outcome was the relative measurement error (rME; in percent of 6WD), with |rME| < 7.5% defined as reliable. The intraclass correlation coefficient (ICC) for agreement between app- and DW-based 6WD was calculated. Measurements (n = 406) were reliable with all smartphone types in neighborhood, nature, and city environments (without high buildings), as well as with unspecified, straight, continuous, and stop-and-go walking patterns (ICC = 0.97, 95% CI 0.97-0.98, p < 0.001). Measurements were unreliable indoors, in city areas with high buildings, and for predominantly rectangular walking courses. Walking speed had an influence on the ME, with worse accuracy (2% higher rME) for every kilometer per hour slower walking pace (95% CI 1.4%-2.5%, p < 0.001). Mathematical adjustment of the app-based 6WD for velocity-dependent error mitigated the rME (p < 0.011), attenuated velocity dependence (p = 0.362), and had a positive effect on accuracy (ICC = 0.98, 95% CI 0.98-0.99, p < 0.001). The new, free, spine-specific 6WT smartphone app measures the 6WD conveniently by using GPS coordinates, empowering patients to independently determine their functional status before and after (surgical) treatment. Measurements of 6WD obtained for the target population under the recommended circumstances are highly reliable.

A decade of sustained geographic spread of HIV infections among women in Durban, South Africa

BackgroundFine scale geospatial analysis of HIV infection patterns can be used to facilitate geographically targeted interventions. Our objective was to use the geospatial technology to map age and time standardized HIV incidence rates over a period of 10 years to identify communities at high risk of HIV in the greater Durban area.MethodsHIV incidence rates from 7557 South African women enrolled in five community-based HIV prevention trials (2002–2012) were mapped using participant household global positioning system (GPS) coordinates. Age and period standardized HIV incidence rates were calculated for 43 recruitment clusters across greater Durban. Bayesian conditional autoregressive areal spatial regression (CAR) was used to identify significant patterns and clustering of new HIV infections in recruitment communities.ResultsThe total person-time in the cohort was 9093.93 years and 613 seroconversions were observed. The overall crude HIV incidence rate across all communities was 6·74 per 100PY (95% CI: 6·22–7·30). 95% of the clusters had HIV incidence rates greater than 3 per 100PY. The CAR analysis identified six communities with significantly high HIV incidence. Estimated relative risks for these clusters ranged from 1.34 to 1.70. Consistent with these results, age standardized HIV incidence rates were also highest in these clusters and estimated to be 10 or more per 100 PY.Compared to women 35+ years old younger women were more likely to reside in the highest incidence areas (aOR: 1·51, 95% CI: 1·06–2·15; aOR: 1.59, 95% CI: 1·19–2·14 and aOR: 1·62, 95% CI: 1·2–2·18 for < 20, 20–24, 25–29 years old respectively). Partnership factors (2+ sex partners and being unmarried/not cohabiting) were also more common in the highest incidence clusters (aOR 1.48, 95% CI: 1.25–1.75 and aOR 1.54, 95% CI: 1.28–1.84 respectively).ConclusionFine geospatial analysis showed a continuous, unrelenting, hyper HIV epidemic in most of the greater Durban region with six communities characterised by particularly high levels of HIV incidence. The results motivate for comprehensive community-based HIV prevention approaches including expanded access to PrEP. In addition, a higher concentration of HIV related services is required in the highest risk communities to effectively reach the most vulnerable populations.

Stratigraphic architecture and hierarchy of fluvial overbank splay deposits

Splay deposits represent an important sand-prone component of the otherwise fine-grained stratigraphic record of fluvial overbank systems. This work presents a hierarchical approach to the classification and palaeoenvironmental interpretation of ancient preserved splay deposits supported by the analysis of the stratigraphic architecture of 11 exhumed examples from the Jurassic Morrison Formation and the Cretaceous Mesaverde Group (western USA) and analysis of the morphology of splays from nine modern fluvial systems. A hierarchical arrangement of splay deposits is proposed, categorized into lithofacies, beds, elements and complexes. Recognition criteria for each tier of the hierarchy include identification of bounding surfaces, thinning and fining trends of splay elements and complexes, and palaeocurrent variability. Progradational and compensational stacking trends control the stratal architecture of splay deposits, and these are influenced by the following factors: (1) the rate of local accommodation generation, which influences the erosive power of floodwaters and whether splay elements are laterally offset owing to compensational stacking; (2) the nature of the topographic confinement of the floodplain; (3) the preservation potential linked to migration direction of channel. Splay bodies can contribute volume to fluvial reservoirs and may form significant connectors that link otherwise isolated primary channel bodies, thereby enhancing reservoir connectivity. Supplementary material: Thickness and facies types with global positioning system (GPS) coordinates, length and width v. thickness, and modern data and coordinates are available at https://doi.org/10.6084/m9.figshare.c.4461026

Using paradata to collect better survey data: Evidence from a household survey in Tanzania

AbstractData are a key component in the design, implementation, and evaluation of economic and social policies. Monitoring data quality is an essential part of any serious, large‐scale data collection process. The purpose of this article is to show how paradata should be used before, during, and after data collection to monitor and improve data quality. To do this we use timestamps, global positioning system (GPS) coordinates, and other paradata collected from an 800‐household survey conducted in Tanzania in 2016. We demonstrate how key paradata can be used during each phase of a research project to identify and prevent issues in the data and the methods used to collect it. Our results corroborate the importance of collecting and analyzing paradata to monitor fieldwork and ensuring data quality for micro data collection in developing countries. Based on these findings we also make recommendations as to how researchers can make better use of paradata in the future to manage and improve data quality. We argue for an expansion in the understanding and use of varied paradata among researchers, and a greater focus on its use for improving data quality.

Delivering integrated care after sexual violence in the Democratic Republic of the Congo

In the eastern Democratic Republic of the Congo, ongoing armed conflict increases the incidence of gender-based violence (GBV) and presents a distinct and major barrier to care delivery for all...

Sensing System for Real-Time Measurement of Seed Spacing, Depth, and Geo-Location of Corn: A Proof-of-Concept Study

Abstract. Proper seed placement during planting is critical for achieving uniform emergence, which optimizes the crop for maximum yield potential. While uniform plant spacing and seeding depth are often used by corn growers to determine the performance of precision planters, these parameters can be influenced by factors other than machinery, such as seed germination, insects, diseases, and soil properties (e.g., temperature and moisture). Currently, the ideal way to determine planter performance is to manually measure plant spacing and seeding depth. However, this process is both cost- and labor-intensive and prone to human errors. Therefore, this study aimed to develop and test a proof-of-concept sensing and measurement (SAM) system to measure seed spacing and seeding depth and provide the geo-location of each planted seed. The system consisted of a high-speed camera, light section sensor, potentiometer, and survey-grade real-time kinematic (RTK) global positioning system (GPS) unit. Results demonstrated the potential of the proof-of-concept SAM system for measuring seed spacing, seeding depth, and geo-location of corn seeds. Results showed that seed spacing can be calculated using the generated stitched images, achieving a root mean squared error (RMSE) of 0.63 cm and a coefficient of determination (R2) of 0.87 when compared to actual seed spacing measurements. Likewise, 98% of the recorded seeding depths were within the acceptable tolerance of ±10% error. Finally, GPS coordinates were recorded for individual images, which can be used to locate individual seeds and provide detailed information on missing plants (no seeds).HighlightsCalculated seed spacing showed an RMSE of 0.63 cm and an R2 of 0.87.98% of the recorded seeding depth was within the acceptable error of ±10%.GPS coordinates were recorded for individual images. Keywords: High-speed camera, Image mosaic, Light section sensor, Proof of concept, Seeding depth, Seed spacing.

Design and Implementation of a Customable Automatic Vehicle Location System in Ambulances and Emergency Vehicle Systems.

Background:Automatic vehicle location (AVL) refers to a system that calculates the geographical location of any vehicle, i.e., latitude and longitude. Vehicle location information about one or more moving vehicles can be stored in the internal memory and accessed when vehicles are available (offline tracking). It is also possible to get location information on a real-time basis (online tracking). The real-time tracking systems designed to date may incorporate three devices: global positioning system (GPS), geographic information system, and cellular communication platforms that may be either a general packet radio service (GPRS) or any private and local radiofrequency network.Methods:The GPS-based navigation system has been designed so as to allow for user-friendly real-time tracking applications for any emergency vehicles like ambulances. First, GPS coordinates are obtained from the SIM908 module and sent via to a server transmission control protocol/internet protocol. Server codes, which are written in C#, load Google map to show real-time location.Results:We designed online tracking AVL hardware in the two simple and advanced versions. The latter enables both the ambulance driver and the data center to monitor path real-time besides enabling the vehicle driver to receive and make calls and send or receive messages. The former only sends latitude and longitude to the data server continuously, and the path travelled by vehicle is displayed.Conclusion:SIM908 integrates GSM, GPRS, and GPS in one package. It can be a proper choice for real-time economic tracking systems despite its low accuracy in finding geolocations.

Evaluation of diosgenin content in Costus speciosus germplasm collected from Eastern Ghats of India and identification of elite chemotypes

Background: Costus speciosus known as insulin plant for its anti-diabetic potential. It has commercial significance due to the presence of industrially viable metabolite diosgenin. Objective: The identification of elite chemotypes of C. speciosus (Rhizome) through high-performance thin-layer chromatography (HPTLC) from the Eastern Ghats (India). Materials and Methods:A validated HPTLC method for the quantification of diosgenin was developed in accordance with the International Conference on Harmonization Guidelines. Results: In total, 11 populations of species were collected from their natural habitat with all the Global Positioning System (GPS) coordinates. The method was developed on HPTLC pre-coated silica gel 60 F254plates under a binary solvent system of n-hexane and ethyl acetate (7:2 v/v). The linearity was established at concentration range of 0.1–0.9 μg/spot having regression equation, 0.010× + 0.002. The limit of detection and limit of quantification were 0.907 and 2.751 with a regression coefficient of 0.999. The diosgenin content varies significantly (P

A Wearable Electronic Guidance System for the Blind Person

The sense of vision is essential in life. Blind persons have difficulties navigating both indoors and outdoors. A cane is a very important tool for them. However, using conventional cane is quite hazardous and time-consuming. To navigate safely and successfully, they need a device that is more than just an ordinary cane. In this study, an electronic guidance system that is equipped with both Global Systems for Mobile (GSM) and Global Positioning System (GPS) features had been designed and evaluated. The system is capable of alerting the user of the presence of nearby obstacles along the navigation path. It can give audio signals containing the GPS coordinates and direction details of the user. Through the GSM module, the system can send a message containing the location details of the blind user to a dedicated receiver in cases of emergencies. Experiment results had shown that the designed system can effectively detect obstacles and can efficiently provide the location and direction details. With this system, the travel time of the blind user had been significantly reduced by 21.26 percent.

Anti-Theft Vehicle Tracking System Using GPS and Location Prediction

Currently the number of private vehicles is increasing day by day and hence the importance of tracking and theft prevention. Recently the vehicle tracking systems are getting wide popularity and can be used in tracking in case of stolen vehicles. Real-time applications like Vehicle Tracking System is developed using Arduino board with a microcontroller. We have developed a vehicle tracking system with a Smartphone which is less expensive and reliable when compared to the existing system as there is no need for extra hardware. The objective is to develop an application for tracking vehicles, which will help the cab owners to track their car all the time and to predict the location of the vehicle in the case of a failing GPS (Global Positioning System). Time series prediction algorithm is used to predict the location of the vehicle if GPS is in off mode. The vehicle tracking system installed will update the GPS coordinates of the vehicle continued to the cloud, and this data can be used for predicting the location of the vehicle in case of emergency. This system can also be used to generate the bills after finishing the freight in the form of an SMS based on the distance traveled, which can be calculated from the latitude and longitude data. The GPS data can be mapped to the Google maps to track the location in real time. Compared with the existing system, this system is having the advantage of location prediction from the historic location data, and the cost is reduced by almost half.

COMPARISON OF SUPERVISED CLASSIFICATION TECHNIQUES WITH ALOS PALSAR SENSOR FOR ROORKEE REGION OF UTTARAKHAND, INDIA

Abstract. The Advanced Land Observing Satellite (ALOS) is developed by the Japanese Aerospace Exploration Agency (JAXA) which was launched in the year 2006 for the Earth observation and exploration purpose. The ALOS was carrying PRISM, AVNIR-2 and PALSAR sensors for this purpose. PALSAR is L-Band synthetic aperture radar (SAR). The PALSAR sensor is designed in a way that it can work in all weather conditions with a resolution of 10 meters. In this research work we have made an investigation on the accuracy obtained from the various supervised classification techniques. We have compared the accuracy obtained by classifying the ALOS PALSAR data of the Roorkee region of Uttarakhand, India. The training ROI’S (Region of Interest) are created manually with the assistance of ArcGIS Earth and for the testing purpose, we have used the Global positioning system (GPS) coordinates of the region. Supervised classification techniques included in this comparison are Parallelepiped classification (PC), Minimum distance classification (MDC), Mahalanobis distance classification (MaDC), Maximum likelihood classification (MLC), Spectral angle mapper (SAM), Spectral information divergence (SID) and Support vector machine (SVM). Later, through the post classification confusion matrix accuracy assessment test is performed and the corresponding value of the kappa coefficient is obtained. In the result, we have concluded MDC as best in term of overall accuracy with 82.3634% and MLC with a kappa value of 0.7591. Finally, a peculiar relationship is developed in between classification accuracy and kappa coefficient.

The virtual small cells based on UE positioning: a network densification solution

Next wireless generation mobile networks will be composed of a large number of antennas at the base station (BS), which is known as massive multiple input multiple output (MIMO). Thanks to this technology, the BS can focus the energy on a user equipment (UE) or group of UEs to improve their throughput and the network capacity. We call these coverage areas virtual small cells (VSCs). Their main advantage is that they allow increasing the network capacity through a virtual densification, therefore, avoiding the deployment cost of new infrastructure. Identifying the dense traffic areas in real time and providing a good quality of service arises as a key challenge to be addressed. Our work focuses on the interaction between the VSCs and the identification of the dense traffic areas, where a feedback scheme is proposed. This feedback scheme is based on the location of these dense traffic areas provided by our proposed clustering methods. To conduct this research, we propose (i) a VSC architecture and system model with a specific codebook in order to avoid feedback overhead, and (ii) two positioning algorithms in order to determine the hotspots localization. The first positioning algorithm is based on K-means method and is centralized at the BS using Global Positioning System (GPS) coordinates, and the second one is based on cooperative communications using ultra-wideband (UWB) signals in order to avoid the network participation. Finally, simulations of these positioning methods intended for the use of the VSCs are presented. These results show significant improvement compared to already existing methods. Furthermore, these positioning methods highly reduce the feedback since, accordingly to our VSC model, the BS only requires angles information based on the localized hotspots.

Use of mobile technology-based participatory mapping approaches to geolocate health facility attendees for disease surveillance in low resource settings

Background Identifying fine-scale spatial patterns of disease is essential for effective disease control and elimination programmes. In low resource areas without formal addresses, novel strategies are needed to locate residences of individuals attending health facilities in order to efficiently map disease patterns. We aimed to assess the use of Android tablet-based applications containing high resolution maps to geolocate individual residences, whilst comparing the functionality, usability and cost of three software packages designed to collect spatial information.ResultsUsing Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116 m (IQR 42–368) in Rizal and 493 m (IQR 258–886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks.ConclusionsResults demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context.

Cluster-mapping procedure for tourism regions based on geostatistics and fuzzy clustering: example of Polish districts

ABSTRACTIn tourism, the phenomenon of spatial agglomeration (concentration of economic activity) spreads beyond the borders of the territorial units. It is referred to as geographic ‘spillovers’ that enhances spatial interdependence and functional relationship of neighbouring regions. Within the standard procedure of cluster-mapping, only concentration inside a territorial unit may be analysed which is a source of biased results in tourism studies. However, tourist agglomeration centres sometimes occur at the juncture of territorial units and the economic entities located in them form spatial clusters with a different degree of membership to several centres of agglomerations located in the neighbourhood. Therefore, we propose to measure ‘inter-regional’ agglomeration in tourism providing modification of spatial autocorrelation measures (regarding neighbourhood and distance). In order to measure neighbourhood more precisely, we use geostatistical information (global positioning system (GPS) coordinates of tourism entities) and geographically weighted fuzzy clustering approach (FGWC). We examine the method on the example of Polish districts (NUTS-4) using database of 131,338 firms registered in section I (accommodation and food services) of Polish Classification of Activity in 2015. The results proved that a novel method of cluster-mapping considering spatial dependency combined with geographic information system (GIS) and FGWC method increases the accuracy of the identification of tourism clusters (inter-regional agglomeration).

Radius of Care in Secondary Schools in the Midwest: Are Automated External Defibrillators Sufficiently Accessible to Enable Optimal Patient Care?

Sudden cardiac arrest is the leading cause of death among young athletes. According to the American Heart Association, an automated external defibrillator (AED) should be available within a 1- to 1.5-minute brisk walk from the patient for the highest chance of survival. Secondary school personnel have reported a lack of understanding about the proper number and placement of AEDs for optimal patient care. To determine whether fixed AEDs were located within a 1- to 1.5-minute timeframe from any location on secondary school property (ie, radius of care). Cross-sectional study. Public and private secondary schools in northwest Ohio and southeast Michigan. Thirty schools (24 public, 6 private) volunteered. Global positioning system coordinates were used to survey the entire school properties and determine AED locations. From each AED location, the radius of care was calculated for 3 retrieval speeds: walking, jogging, and driving a utility vehicle. Data were analyzed to expose any property area that fell outside the radius of care. Public schools (37.1% ± 11.0%) possessed more property outside the radius of care than did private schools (23.8% ± 8.0%; F1,28 = 8.35, P = .01). After accounting for retrieval speed, we still observed differences between school types when personnel would need to walk or jog to retrieve an AED ( F1.48,41.35 = 4.99, P = .02). The percentages of school property outside the radius of care for public and private schools were 72.6% and 56.3%, respectively, when walking and 34.4% and 12.2%, respectively, when jogging. Only 4.2% of the public and none of the private schools had property outside the radius of care when driving a utility vehicle. Schools should strategically place AEDs to decrease the percentage of property area outside the radius of care. In some cases, placement in a centralized location that is publicly accessible may be more important than the overall number of AEDs on site.