Google Maps Research Articles

An Innovative Approach for Mission Sharing and Route Planning of Swarm Unmanned Aerial Vehicles in Disaster Management

Fast and effective response in disaster situations is critical for the success of rescue operations. In this context, swarm Unmanned Aerial Vehicles (UAVs) play an important role in disaster response by rapidly scanning large areas and performing situation assessments. In this paper, we propose an innovative method for task allocation and route planning for swarm UAVs. By combining Genetic Algorithm (GA) and Ant Colony Optimization (ACO) techniques, this method aims to ensure the most efficient movement of UAVs. First, clusters are created using GA to determine the regions of the disaster area that need to be scanned. At this stage, factors such as the capacities of the UAVs, their flight times, and the breadth of their mission areas are taken into account. Each UAV is optimized to scan a specific area assigned to it. Once the clusters are formed, the routes of the UAVs within each cluster are determined by the Ant Colony Algorithm (ACA). The route planning is tested both on Google Maps and in a simulation environment. Google Maps is used to evaluate the accuracy and feasibility of route planning based on real-world conditions, while the simulation environment provides the opportunity to test the behavior of the UAVs and the effectiveness of the routes in a virtual setting. With real-time data integration, the UAVs' route planning can be updated instantly and quickly adapted to emergency situations.

Trip Attraction Rate Estimation Using Open Data Sources for Smart Transportation Planning

Trip Attraction Rate (TAR) serves as a load factor utilized in aggregate transportation modeling. Conventional estimation consumes a lot of time and manpower for field surveys. Meanwhile, open data sources, such as Google Maps, offer an alternative approach to conducting a survey. The popular times feature from Google Maps can estimate coffee shop TAR in the city of Bandung. This study focuses on coffee shops in Bandung City. Data was collected using web scraping techniques on Google Maps and produced a sample size of 377 data points after the validity and reliability processes. Subsequently, multiple linear regression was employed to estimate TAR. The findings reveal that variables like building area and distance to public transportation hubs influence TAR simultaneously. Moreover, our approach could also distinguish TAR between weekdays (0.13 people/m2/hour) and weekends (0.14 people/m2/hour) in Bandung City. This result challenges the usage of Institute of Transportation Engineers (ITE) standards, which is often due to limitations of time and workforce in conducting surveys for TAR estimation. The difference in values indicates the need to estimate specific TAR for each city in Indonesia rather than relying on ITE values, and the proposed approach to using open data sources will shorten the estimation process.

Rancang Bangun Aplikasi Frontend Geographic Information System Menggunakan Metode Rad (Rapid Application Development)

North Sumatra Province has the fourth largest population in Indonesia after the Provinces of West Java, East Java, and Central Java. In 2022, the population of North Sumatra will reach 15,372,437 people. This means that North Sumatra Province has many vehicles, one of which is motorized vehicles. This makes the community do a lot of services related to motor vehicle tax at Samsat Outlets. Ease of information about the locations of Samsat Outlets is also a mandatory need for the community. The use of internet technology to develop geographic information systems is expected to provide convenience for the public in obtaining information on the location of Samsat Outlets. This system utilizes Google Maps to process and visualize the location of Samsat Outlets. The system is designed using the Rapid Application Development software development method. It is hoped that the public will more easily obtain information about the location of Samsat

Unveiling the daily rhythm of urban space: Exploring the influence of built environment on spatiotemporal mobility patterns

Urban mobility research is crucial due to the complex and dynamic nature of cities. Traditional zoning methods often overlook the temporal dynamics of urban space usage. This paper aims to investigate the daily rhythm of urban space usage and how built environmental features affect spatiotemporal mobility. The methodology integrates various urban data sources, including street and building vectors and points of interest (POI). In Ankara, Türkiye, temporal usage types were identified using principle component analysis and k-means algorithms via Google Maps location-based service data. Multinomial logistic regression model was used to examine the impact of built-environment factors on daily mobility patterns. Results reveal distinct daily usage rhythms, categorizing busy areas into morning, noon, early evening, late evening, diurnal, and nocturnal zones. The study finds: (1) temporal usage is closely associated with spatial characteristics and resident income; (2) work-related activities drive morning mobility, while nighttime mobility relates to residence, income, and accessibility; and (3) population density alone does not guarantee continuous activities; diverse POIs alongside high density are crucial. The identified relationship between mobility measures and urban built environment indicators provides a comprehensive understanding of spatiotemporal variations, offering insights for critical policy evaluations and proposals for the future of urban areas.

Tele-Assisted Home-Based Palliative Care Reduces Health Care Costs for Terminal Cancer Patients: Real-World Evidence From a Regional Hospital in Taiwan.

Background: Tele-assisted home-based palliative care (THPC) usually fulfills the desire of terminal patients to pass away at home. The overall costs of such a service deserve evaluation. Objectives: This study aims to determine health care utilization and costs for cancer patients at the end of life, stratified by THPC service. Design: Patients who received THPC were matched 1:1 based on age, gender, year of death, and propensity score with those who did not receive THPC. Setting/Subjects: A total of 773 cancer patients passed away in a regional hospital in Taiwan during the period of 2012-2020, of which 293 received THPC. Measurements: We measured the rates and costs of outpatient clinic visits, emergency department (ED) visits, hospitalizations, and intensive care unit (ICU) admissions during the last week, the last two weeks and the last month before death. In addition, we estimated the driving times and expenses required for transportation from each cancer patient's home to the hospital using Google Maps. National Health Insurance (NHI) reimbursements and out-of-pocket expenses were also calculated. Results: In comparison with patients without THPC, those who received THPC had a 50% lower likelihood of visiting the ED or being hospitalized, a more than 90% reduced chance of ICU admission, but were four times more likely to obtain their medicines from outpatient clinics. THPC patients had similar out-of-pocket expenditures, approximately half of the NHI costs, and lower rates and costs for ambulance transportation to the ED. Conclusions: THPC reduced health care costs for terminal cancer patients in the last week, the last two weeks, and the last month before death, while also increasing the likelihood of patients being able to rest and pass away at home.

Pemanfaatan Marketplace Shopee sebagai Media Promosi pada Pelaku UMKM di Desa Kaliwlingi, Kabupaten Brebes

The current development of MSMEs has an effect on increasing people's income. However, the lack of access to promotion in marketing causes MSMEs to experience problems in increasing income. This problem can be overcome by digitizing MSMEs which are expected to be able to promote their products online, one of which is by providing assistance by making a Google map. This community service aims to provide knowledge to MSME business actors about the importance of promotion in the world of digitalization. Thus, KKN students carry out community service to fully support MSMEs in the village of Kaliwlingi, Brebes Regency so that MSME Business Actors can compete broadly in the outside realm of their area. This service starts from the preparation stage by visiting MSMEs through door to door, and continues with training on making Shopee for each MSME business actor.

Exploratory Analysis on the Livability of a City with Digital Placemaking in Jakarta Timur, Indonesia

Abstract People who work in Jakarta to prefer suburban areas as their homes, such as Jakarta Timur. Urban livability directly influences the quality of life of the citizens. The purposes of this study on Jakarta Timur: 1) understanding the public space roles and values; 2) finding out the types of public spaces; 3) understanding the connection between livability and the value of public spaces; and 4) exploring new placemaking research method of using big data. The methodology included data collection (government documents, news articles from trusted sources, Google Reviews via Octoparse 8, and Google Map), data visualization (wordclouds and QGIS), and data analysis (word frequency, sentiment, and accessibility). The area’s socio-demographic study estimated that the reviews are dominantly written informatively and expressively by locals with certain characteristics (must be proven in future studies). It was also revealed that Jakarta Timur is comprised of more yellow zones (housing) with only a little green zone (already including the selected public spaces). The recurring motives for visitation included doing sport and playing with family/children and the sentiment analysis reflected overall positive values on the citizens. Regarding accessibility, it was found that despite preferring private transportation, the willingness to ride the public transportation still existed.

Optimizing Tourist Visits through Digital Tourism Socialization Campaign at Watubangga Beach Tourism Destination

Tourism is a crucial economic sector in regional development, including Watubangga Beach, Southeast Sulawesi. Despite its significant potential, efforts to market and promote this destination have yet to be optimal in attracting tourists. This project aims to leverage digital technology to enhance the appeal of Watubangga Beach, aiming to provide substantial benefits to both the local community and visitors. Methods employed include field observations, interviews with tourism managers, establishment of social media accounts, mapping the location on Google Maps, providing entrance tickets and tourism brochures, coastal area cleanup, and installation of directional signage. This article discusses digital-based tourism promotion strategies to increase visitor numbers to Watubangga Beach. By maintaining cleanliness, utilizing social media, and actively involving tourists, it is hoped to create satisfying tourist experiences. The digital marketing strategies are expected to directly benefit tourism managers by boosting visitor numbers and advancing tourism at Watubangga Beach.

Beach Clubs and Tourist Gaze: A Critical Inquiry into the Construction of Social Distinction

This study explores the growing concerns about socioeconomic accessibility, inclusivity, and exclusionary practices of beach clubs as ostensibly public spaces in the tourism destination of Çeşme. The thematic analysis of Google Maps online reviews has provided critical insights into beach clubs’ selective admission practices and has elucidated the factors influencing customer perspectives and driving high demand for these clubs. Also, the findings revealed a relationship between customer expenditure and favorable entrance experiences; guests with lesser spending reported dissatisfaction and reluctance to revisit. Eight beach clubs with ratings deviating from the weighted average were examined to ensure diverse representation. The findings strongly encourage us to take urgent policy action to address the call for the need to create more inclusive beaches that should not be solely open to certain people with privileges. In the case of beach clubs, the adherence to specific dress codes and the emphasis on Instagram followers as a measure of social status reflect the doxa of conspicuous consumption and social hierarchies. This perpetuates a system where the privileged and affluent are more likely to gain access, while others may feel excluded or marginalized. Drawing on the solid theoretical frameworks of Pierre Bourdieu’s social theory and John Urry’s “tourist gaze,” this paper outlines the socio-economic barriers that distort ideals of public space and leisure and invites a reassessment of inclusivity in tourist destinations and luxury tourism.

The Development of A Mobile-Based Area Recommendation System Using Grid-Based Area Skyline Query and Google Maps

The Development of A Mobile-Based Area Recommendation System Using Grid-Based Area Skyline Query and Google Maps

Eksplorasi Pemetaan Pelanggan dan Prioritas Pengembangan Jaringan Internet : Pendekatan Sistem Informasi Geografis Berbasis Web dan AHP

ArsyaNet, a local internet service provider, strives to deliver fast and reliable internet access to its customers. This study aims to implement a web-based Geographic Information System (GIS) for customer mapping and network development prioritization using the Analytic Hierarchy Process (AHP) method at ArsyaNet. Leaflet is employed to map the distribution of ArsyaNet customers within the RT/RW network in the Pringgasela District. The main objective of this research is to accurately and efficiently map the distribution of internet customers to support optimal network development. By integrating AHP into the GIS, customer preferences and other relevant factors such as access speed, service quality, and infrastructure needs in specific areas will be considered in determining the priority locations for network development. The AHP method allows for the grouping of customers based on their preferences and determining locations by considering weights on each relevant aspect. Integrating Leaflet into the GIS enables accurate and interactive mapping results using a lighter map compared to the Google Maps API. This research is conducted to enhance the quality of internet services provided by ArsyaNet by better understanding the needs and preferences of customers in selecting internet service providers and their customer distribution.

Spatial distribution of patients with pressure injuries treated at a teaching hospital

Introduction: Pressure injury (PI) is characterized by pressure exerted mainly on bony prominences, or even related to the use of medical devices. As epidemiological aspects are still scarce in the country, it is appropriate to produce studies that delimit the information for a better characterization of this public health problem, with extraterritorial dimensions. Geoprocessing is a revolutionary technology that encompasses the most diverse disciplines, data, equipment, analysis and interpretations from certain locations and geographic data, thus obtaining maps and/or spreadsheets with information relevant to that particular region that, when used in the health area, allows the identification and mapping of risks and injuries that affect the population. Objective: To demonstrate the technical experience of spatial demarcation and geoprocessing of patients with pressure injuries treated at a teaching hospital in the state of Sergipe. Method: A descriptive epidemiological study was carried out from a data sheet of patients with pressure injuries treated by the Skin Care Service team of a teaching hospital in Sergipe, between 2018 and 2022. Georeferencing and geoprocessing were developed in conjunction with Google Maps and Google Earth software. Results: The study sample consisted of 215 patients with pressure injuries (PI) in which the age group that stood out was the elderly (54.8%), followed by adults (40.0%). It is noted, in the spatial representation, that most of the patients with PL were residents of Greater Aracaju (n=130), followed by the East of Sergipe (n=23) and Central Agreste (n=18). Most of the LPs were acquired prior to admission to the institution studied (55.8%), while the others (44.2%) appeared during the hospital stay. Conclusion: In view of the analysis presented, it was possible to verify that most patients affected by PLs are men and elderly, and that the Greater Aracaju regional was the one that stood out the most because it concentrated most of the patients with PL, whether pre-existing or acquired at hospitalization.

Method of Forming and Algorithm of Saving a Photo Map of the Seafloor during its Photography by an Unmanned Underwater Vehicle

The paper proposes a new method and algorithm for creating a photo map of the seabed from photographs obtained from on-board photo and video systems of autonomous uninhabited underwater vehicles during fulfillment of their various missions. This photo map is formed from photographs of the seabed by sequentially overlapping them. At the same time, data on the position of the underwater vehicle received from the on-board navigation system at the time of receipt of each photograph is used to position each photo image on the generated photo map. And to rotate and scale these photographic images, data on the orientation of the underwater vehicle in the global coordinate system and its height above the bottom, also obtained from the on-board navigation system, are used. To provide quick access to the photo map, it is proposed to store it on an on-board data storage device in the form of a tile map, widely used when creating interactive geographical maps, for example, Google Maps. However, the formation of a tile map is usually carried out on the basis of all the already received photographic images, as is done with satellite images, which cannot be applied on board underwater vehicles when data from the photo-video system is received sequentially. Therefore, a special algorithm has been developed and implemented that generates a tile map during the movement of the underwater vehicle and updates only the area of the tile map in which the photo is currently being taken. This minimizes the computational load and ensures the formation of a photo map of the bottom using standard on-board computing devices. The conducted semi-natural experiments with data obtained as a result of performing real missions using the MMT-3000 underwater vehicle confirmed the high efficiency of using the developed method and algorithm.

An Empirical Case Study GeoAI Usage for Sustainability Scoring of University Campuses

UI GreenMetric (GM) ranking system is a methodology to score and rank the university campuses in several categories. The campuses are measured according to their various sustainability indicators in this methodology. The base of this research to study on how we can use geoAI to calculate GM Setting & Infrastructure (SI) score. By this empirical case study to have ideas connected with the relation of score point and geospatial metrics by recognized of google map geotiff images of university campuses. To develop a geoIA methodology with KooMap cloud service in the purpose of sustainability scoring would provide a practical, accurate and pretty objective algorithm for a smart campus evaluation. In the way of transforming to smart city these applications and utilizations of geoAI are the digital trends of new era.

Optimal Placement of Multiple Sources in a Mesh-Type DC Microgrid Using Dijkstra’s Algorithm

This research paper introduces an optimization methodology for the strategic electric sources’ placement at multiple positions in a DC islanded microgrid characterized by a mesh network, aiming to minimize line losses while considering minimal cable weight. The DC microgrid studied in this paper is composed of PV panels, batteries, a diesel generator, and 20 residential loads. Employing Dijkstra’s algorithm, a graph algorithm used in Google Maps, the study identifies the shortest path (resistance) between potential source nodes and various variable loads within a predefined electric distribution mesh network topology. This study focuses on active power considerations and offers valuable insights into the placement optimization of multiple sources’ positions in DC microgrid mesh networks. A key contribution of this paper lies in the ranking of source node positions based on minimal to maximal line losses, taking into consideration optimal cable weights, while using MATPOWER to validate sources’ ranking based on Dijkstra’s hypothesis. The research further includes a techno-economic study to assess the viability of sources’ placement at multiple positions within the mesh network, comparing it with the optimal placement scenario involving a single position for all sources. This methodology serves as a valuable resource for system designers and operators aiming to minimize line losses and optimize energy distribution in DC microgrids in a mesh topology.

Application of Naive Bayes Algorithm for Sentiment Analysis of Service and Facility Satisfaction (Case Study: PKU Muhammadiyah Sukoharjo General Hospital)

PKU Muhammadiyah Sukoharjo Hospital is a health facility located in Sukoharjo, Central Java. The role of the hospital in the Sukoharjo community is very important in terms of the level of community satisfaction with its services and facilities. Opinions and assessments from the community also affect the assessment of the quality of service provided by the hospital. A large assessment can be seen on Google Maps review, which will take time for the community. Public complaints on Google Maps review of PKU Muhammadiyah Sukoharjo Hospital became the basic object of this research. This research uses the Naive Bayes algorithm to categorize the assessment based on positive and negative sentiments. Two hundred nine review data from Google Maps were processed with text processing and classified using Naïve Bayes. Test results using 10% test data show a dominant positive sentiment, with 90% accuracy, 94% precision, and 83% recall.

Tourism Guide Application for Heritage Sites in Surabaya Based on Augmented Reality and GPS Gamification

One of the most important revenue streams for the nation's economy and development is tourism. The COVID-19 pandemic is, however, causing a reduction in tourism in Indonesia; Surabaya, the country's second-largest city, has seen a drop in visitors from 6.5 million to 500 thousand. To solve this problem, an innovation is required to boost the number of visitors to Indonesia's heritage sites who use contemporary technology, specifically smartphone with interactive media (with AR and GPS for instance). The author will develop an app that, depending on the user's location, will let them visit several Surabaya heritage sites and provide them with comprehensive details and instructions. Indonesia can stimulate its economy and return visitors to its heritage sites by employing this interactive gamification apps. However, on the examination to the user, we found a good implementation in detecting and measuring the nearest destination to the current user position, and how to parse into google map and guiding the destination to that heritage site. But we have some distraction when pointing the apps to the Augmented Reality (AR) marker on the site, since various historical places have various lighting, some devices are unable to take a clear picture of the marker due to its lack of lighting and abnormal size or form. Thus, it will be effective when the user points his smartphone camera to the AR marker, he/she supposed to use the smartphone lighting as well.

ROAD EXTRACTION FROM SATELLITE IMAGERY USING DEEP LEARNING VOL - I

Road extraction involves the intricate process of generating road maps automatically through deep learning algorithms. This task, particularly from satellite imagery, presents significant challenges due to various factors like occlusions, shadows, noise, and fluctuating illumination conditions. As a result, achieving complete and accurate road extraction is daunting without relying on manual annotations or imperfect road maps for guidance. One potential strategy to enhance road extraction accuracy is by incorporating partial road maps as supplementary data. These partial maps, sourced from platforms like OpenStreetMap or Google Maps, may not offer complete or pristine representations of roads but can still provide valuable additional information. By integrating these partial maps with satellite images, we can exploit their complementary nature to mitigate uncertainty in the extraction process. It's important to note that while road extraction may be relatively straightforward in some regions, such as rural areas, it becomes significantly more complex in urban or underdeveloped areas. These environments present unique challenges that require sophisticated algorithms and approaches to accurately extract roads from satellite imagery. Key Words: Road Extraction, Satellite Imagery, Google Maps, Open Street Map, Auxiliary information, Disaster management, Occlusions, Illumination, Annotation, Shadow.

Gun-free zones and active shootings in the United States: a matched case-control study

Most Americans believe that gun-free zones make locations more vulnerable to violent crimes, particularly active shootings. However, there is no empirical evidence regarding the impact of gun-free zones on protecting locations from violence. The objective of this study was to estimate the association between gun-free zones and active shootings. We used a pair-matched case-control study where cases were all US establishments where active shootings occurred between 2014 and 2020, and controls were randomly selected US establishments where active shootings could have but did not occur, pair-matched by establishment type, year, and county. Gun-free status of included establishments was determined via local laws, company policy, news reporting, Google Maps and posted signage, and calling establishments. Of 150 active shooting cases, 72 (48.0%) were determined to have occurred in a gun-free zone. Of 150 controls where no active shooting occurred, 92 (61.3%) were determined to be gun-free. After accounting for matched pairs, the conditional odds of an active shooting in gun-free establishments were 0.38 times those in non-gun-free establishments, with a 95% confidence interval of 0.19-0.73 (p-value=0.0038). Several robustness analyses affirmed these findings. It is unlikely that gun-free zones attract active shooters; gun-free zones may be protective against active shootings. This study challenges the proposition of repealing gun-free zones based on safety concerns. This work was funded in part by the National Collaborative on Gun Violence Research and the Arnold Foundation.

The association of travel burden with prenatal care utilization, what happens after provider-selection

BackgroundBirthing people in the United States face numerous challenges when accessing adequate prenatal care (PNC), with transportation being a significant obstacle. Nevertheless, previous studies that relied solely on the distance to the nearest provider cannot differentiate the effects of travel burden on provider selection and care utilization. These may exaggerate the degree of inequality in access and fail to capture perceived travel burden. This study investigated whether travel distances to the initially visited provider, to the predominant PNC provider, and perceived travel burden (measured by the travel disadvantage index (TDI)) are associated with PNC utilization.MethodsA retrospective cohort of people with live births were identified from South Carolina Medicaid claims files in 2015–2018. Travel distances were calculated using Google Maps. The estimated TDI was derived from local pilot survey data. PNC utilization was measured by PNC initiation and frequency. Repeated measure logistic regression test was utilized for categorical variables and one-way repeated measures ANOVA for continuous variables. Unadjusted and adjusted ordinal logistic regressions with repeated measure were utilized to examine the association of travel burdens with PNC usage.ResultsFor 25,801 pregnancies among those continuously enrolled in Medicaid, birthing people traveled an average of 24.9 and 24.2 miles to their initial and predominant provider, respectively, with an average TDI of -11.4 (SD, 8.5). Of these pregnancies, 60% initiated PNC in the first trimester, with an average of 8 total visits. Compared to the specialties of initial providers, predominant providers were more likely to be OBGYN-related specialists (81.6% vs. 87.9%, p < .001) and midwives (3.5% vs. 4.3%, p < .001). Multiple regression analysis revealed that every doubling of travel distance was associated with less likelihood to initiate timely PNC (OR: 0.95, p < .001) and a lower visit frequency (OR: 0.85, p < .001), and every doubling of TDI was associated with less likelihood to initiate timely PNC (OR: 0.94, p = .04).ConclusionsFindings suggest that the association between travel burden and PNC utilization was statistically significant but of limited practical significance.