Google Maps API Research Articles

The flying sidekick traveling salesman problem with stochastic travel time: A reinforcement learning approach

As a novel urban delivery approach, the coordinated operation of a truck–drone pair has gained increasing popularity, where the truck takes a traveling salesman route and the drone launches from the truck to deliver packages to nearby customers. Previous studies have referred to this problem as the flying sidekick traveling salesman problem (FSTSP) and have proposed numerous algorithms to solve it. However, few studies have considered the stochasticity of the travel time on the road network, mainly caused by traffic congestion, harsh weather conditions, etc, which heavily impacts the speed of the truck, thus affecting the drone’s operations and overall delivery routine. In this study, we extend the FSTSP with stochastic travel times and formulate the problem into a Markov decision process (MDP). The model is solved using reinforcement learning (RL) algorithms including the deep Q-network (DQN) and the Advantage Actor-Critic (A2C) algorithm to overcome the curse of dimensionality. Using an artificially generated dataset that was widely accepted as benchmarks in the literature, we show that the reinforcement learning algorithms also perform well as approximate optimization algorithms, outperforming a mixed integer programming (MIP) model and a local search heuristic algorithm on the original FSTSP without the stochastic travel time. On the FSTSP with stochastic travel time, the reinforcement learning algorithms obtain flexible policies that make dynamic decisions based on different traffic conditions on the roads, saving up to 28.65% on delivery time compared with the MIP model and a dynamic local search (DLS) algorithm. We also conduct a case study using real-time traffic data collected in a middle-sized city in the U.S. using Google Map API. Compared with a benchmark calculated by the DLS, the DRL approach saves 32.68% total delivery time in the case study, showing great potential for future practical adoption.

BUILDING FOOTPRINT EXTRACTION FROM SPACE-BORNE IMAGERY USING DEEP NEURAL NETWORKS

Abstract. One of the important and high-level detailing contained within basemaps is the ‘building feature’. Though pre-trained Deep Learning (DL) models are available for Building Feature Extraction (BFE), they are not efficient in predicting the buildings in other locations. This study explores the need and the major issue of implementing DL models for BFE from Very High Resolution Remote Sensing (VHRS) satellite data for any given area. Though advanced DL models are invented, in order to implement them, huge amount of potential training data is demanded for feed in. the building typologies are highly subjected to the context of study area including soil characteristics, culture/lifestyle/economy, architectural style and the building byelaws. The study believes that availability of enough training data of contextual buildings as one of the concern for effective model training. The study aims to extract the buildings present in the study area from Pleiades 1A (2019) RGB VHRS data using simple Mask R-CNN instance segmentation model which is training on the native contextual buildings. Here, an automated method of generating the location-specific training data for a given area is followed using Google Maps API (2021). The generated training data when trained on a deep learning architecture and predicted by the input data yielded promising results. The prediction accuracy of about 98.41% specificity, 96.20% predictive accuracy and 0.89 F1 score are achieved. The methods adopted assist the planning/governing bodies to accelerate the qualitative urban map preparation.

College Bus Tracking System

The modern world is driven by technological change day by day. Especially appropriate technological changes improve modern business strategies. Various technologies have been developed in the world to make people's lives easier and better day by day. Android is the latest and fastest technology available to all users or users in today's market. A significant increase in user acceptance has been seen in the last few years. The project is based on the latest GPS technology that allows the college management team the best way to monitor college bus activity and schedule and provide real-time bus location for students using the bus service. This paper proposes an Android mobile app that provides information about buses, bus numbers and bus routes / bus-stops online. The proposed system is fully integrated with online bus tracking systems using an android app. They can also view bus details as a bus schedule and arrive at the bus on time. It is a real-time system as the current bus location is constantly updated with latitude and longitude is obtained by the user at his request with the help of Google Map API.

Generation of Istanbul road data set using Google Map API for deep learning-based segmentation

ABSTRACT Deep learning architectures are widely used for road segmentation studies. Data sets reflect the characteristics of the study region in which they are generated. The models that are trained with the data sets are unable to accurately forecast the region outside the area covered by the data sets. That is why local data sets must be generated to meet the requirements of navigation, military activities, urban planning and health management applications where road data are indispensable. In this study, satellite images and corresponding mask images of Istanbul city at different zoom levels were generated via Google Map Platform. Trained models were produced using Deep Residual U-Net. This study consists of three parts. The first part includes training each zoom level, from 14 to 17, separately. The recall statistics of models were found as 95%, 94%, 92% and 86%, and corresponding F1-Score statistics were calculated as 95%, 95%, 92% and 86%, respectively. Next, consecutive training with priory weight and regularization on satellite images were tested to increase the prediction results. The consecutive model and regularization methods resulted in an increase in both recall and F1-Score by 2−3%. In the third part, a new model was generated by combining all images which were produced at different levels. The combined model was found successful for the prediction of roads in all zoom levels. Finally, the performance of these models trained with the Istanbul data set was compared with well-known DeepGlobe and Massachusetts road data sets. Hence, this study illustrated that generating all data sets specifically for the area of interest is crucial.

ANALISA PENCAPAIAN PROGRAM KAMPUNG KB DI KABUPATEN LAMPUNG SELATAN DENGAN SISTEM INFORMASI GEOGRAFIS

Efforts to realize quality family planning one of them by living in a healthy environment and also regulate natality, ideal age of childbirth and distance. Planning and Activities Programs are coordinated by representatives of the Provincial BKKBN by involving all elements in the Organizational Structure of Kampung KB (in accordance with the Decree of the Regent / Mayor) through the Forum of Deliberation or inserting in other appropriate forums. A form of realization of program planning is by the form of geographic information systems. Information about the location or place of an object located on the earth's surface and includes information on the location of geographical locations to be analyzed and made decisions. By using the Google Maps API, it is possible to use Google Maps from the geographic information system created. In its early development, the Google Maps API was limited to the Java Script API. Maps API expanded to include an infographic that makes it easy to store and interpret map-shaped data. The problem of the Department of Population Control and Family Planning related to the Kampung KB Program is that they cannot provide information anywhere where the distribution of KB Village is and what achievements have been achieved after the selection of the village into Kampung KB. The presentation of information with spatial data can be facilitated with Geographic Information System. So far, government only receives data in the form of reports of general nature, and government cannot see the distribution of Kampung KB visually. With this information can be presented Geographic Information System. In this study will be developed Geographic Information System distribution and achievement of kampung kb program. Web-based system to visualize the mapping of kb villages into the form of maps, as well as provide information about areas that have been registered as kb or non-kb villages in South Lampung Regency. The system is created using the programming languages PHP, HTML, Javascript and MySql as a system database.

Real-Time Accident Detection Using KNN Algorithm to Support IoT-based Smart City

Surabaya is a city with an area of 326.81 km2 and is the center of land transportation in the eastern part of Java Island. The construction of digital infrastructure in the Surabaya area will make it easier for the City Government to make efficient services. Traffic accidents that occurred in Surabaya until 2017 recorded 1,365 incidents. EVAN (Emergency Vehicle Automatic Notification) is a research topic that focuses on the field of transportation, especially in real-time traffic accidents which can be integrated with city information centers and hospitals for primary assistance in accidents. The purpose of this research is to make it easier for the Surabaya city government to provide first aid in the event of an accident. The design of the device on the user side is made using the Arduino, the accelerometer sensor and the gyroscope in the form of the MPU6050 sensor and the u-blox gps module. Crash detection on the system using the k-Nearest neighbors algorithm (KNN). On the operator side, the design is done on a web basis by utilizing the ReactJs framework which is integrated with the Google Maps APIs. The results of the accuracy of the accident detection system reached 97% and the detection of accident locations and the nearest hospital from the location reached 100%. Thus, real-time accident detection can be implemented in Surabaya city to support the smart city.

Hospital selection and patient transport model in the emergency medical system

We designed a model for hospital selection and patient transport in the emergency medical system. The model integrates the criterium of insurance coverage, seldom used in the literature and the usual criteria such as care capacities, congestion and proximity, typical of countries with mixed health systems (public-private). In addition, the model considered the travel and waiting times in emergency departments as performance measures in different time slots and days of the week. We developed and implemented a prototype in the Python programming language connecting to web services from Google Maps API (Directions, Maps JavaScript) to support the decision-making process in real-time and tested its performance. This research study validated the model with actual data from events managed by the emergency medical system in a Colombian city. We used Monte Carlo simulation to predict the current and proposed models’ travel and transfer time (travel time + waiting time). The simulation results indicate that the proposed model, which considers insurance coverage, emergency departments capacities, congestion and proximity, has a lower probability of putting at risk the lives of critically ill patients. In addition, non-critical patient satisfaction increases as wait times decrease.

PEMETAAN WISATA KULINER HALAL DI WILAYAH PESISIR PANTAI KALIMANTAN BARAT

West kalimantan are third largest province in Indonesia with the rich cultural make him one provincial culture. tourist destination. One of international culture festival that attracts tourists namely local and foreign Cap Go Meh in Singkawang City. Cap Go Meh is the festival legacy of the ethnic Chinese. ancestral culture. Not only the cultural festival, coastal areas the beach or areas downstream have tourist destinations in nature that is not less riveting. Visitors. Local and international visitors always present in the festival which, not only see cultural attractions any tourists will want to kind of food tasting / drinks. local local specialty. Food or drinks sold should be guaranteed halal, so that it can be enjoyed by everyone, especially Muslim consumers. Considering the number of Muslims in West Kalimantan as much as 60% of the total population. From the conditions and opportunities in the field, researchers created a website-based application using the Google Maps API database. The data source used is from LPPOM MUI Kalbar and the Youth, Sports and Tourism Office of West Kalimantan Province. The purpose of this research is to help search halal culinary tourism locations in west Kalimantan tourist areas, especially coastal areas to make it easier for tourists to find and find information about halal restaurants and help promote through digital media SMEs in West Kalimantan who have obtained halal certification and are able to present information for users to find information about halal certification on food based website applications.

Is COVID-19 Causing More Business Closures in Poor and Minority Neighborhoods?

We are starting to understand the magnitude of economic damage from the COVID-19 pandemic. Current estimates cover the national or state level, but tell us little about how massive business closures may be affecting urban vitality at the intrametropolitan level. A particular concern is whether urban areas with high poor or minority populations are more deeply affected. This paper combines InfoGroup Historic Business Data and Google Map API to analyze business closures at the neighborhood level in Franklin County, Ohio, encompassing the Columbus Metropolitan Area. As expected, retail and restaurant sectors had the highest number of closures, but closure rates were higher in other sectors. Descriptive and multivariate analyzes reveal that downtown Columbus has been severely affected, but no disadvantaging effect for communities of color or neighborhoods with concentrations of poor residents is found to be statistically significant.

Sistem Informasi Geografis Pencarian Rute Optimum Lokasi Obyek Wisata Kota Semarang Menggunakan Algoritma Dijkstra

The Semarang City Government is currently developing tourism potential in the Semarang City area. However, the number of tourist attractions in the city of Semarang makes tourists who come to the city of Semarang to be confused to visit the tourist attractions that will be visited. In this study the authors provide solutions for grouping based on the type of tour such as religious tourism, environmental tourism, water tourism, nature tourism and education tourism. The use of the Dijkstra algorithm will be used to help find solutions to visit these tourist attractions. In this system the Google Maps API will be used to display spatial data to indicate the route to be passed. System design to create a Geographic Information System using the Unified Modeling Language (UML). Tourists later use this application by entering the initial location information and the location you want to get to get the route. Based on testing that has been done the system is able to display information on the route it travels will be bypassed by tourists. The results of research and field studies that have been carried out, can be concluded from the user acceptance testing in terms of usefulness of 89.5%, in terms of use of 89.3%, in terms of appearance of 89.5%, and in terms of accuracy of 87.6%, that is strongly agree.

Interactive HGIS platform union of lublin (1569): A geomatic solution for discovering the Jagiellonian heritage of the city

• Lublin Historical GIS is the first www platform in Poland developed with object-oriented approach dedicated to present historical narrations. • The portal is based on four-pillar types of data: events, places, people and sources linked in multirelational matrix. • The developed CMS is integrating various multimedia so that the portal editors (journalists, historians - generally humanists) dont have to have technological skills to develop attractive, deep spatial narratives. • The case presented is so far the deepest and the most accurate historical reconstruction of Lublin in the 16th century. • The users visiting teatrnn.pl/unia-lubelska can explore the vast digital world of 16th-century Lublin at their own pace and with the individual intrests. Lublin in the period of the Lublin Union (1569) is an interdisciplinary research project conducted by the “Grodzka Gate – NN Theatre” Centre in Lublin as a part of the celebration of the 450th anniversary of signing the Union of Lublin Act - one of the most important historical events in 16th-century Europe, during which the Polish-Lithuanian Commonwealth was constituted. This paper aims to present the research process by which an innovative Historical GIS web platform, based on an object-orientated database design, was tested and refined. The portal uses four pillars of spatial-temporal databases (events, people, places, sources) to collect data and develop historical narratives presenting various events in the history of the city and the region. The idea behind the project was to develop an Internet portal that would acknowledge modern users with the historical event of the Union of Lublin from the perspective of the then resident of Lublin. What is known about the 16th-century Lublin? What did the city and its surroundings look like? Who lived in Lublin? Who used to visit it? What architectural elements and traces of cultural heritage have been saved to this day? The reconstruction of the 16th-century urban space was carried out using the retrogression method of 11 early plans and maps of Lublin, verified and supplemented with the latest archaeological findings, accurate architectural research (geo-radar, laser scanning) and an extensive archival query. Thanks to the Historical GIS technology, the research results have been published in the form of a universal platform ( www.teatrnn.pl/unia-lubelska ), with an interactive web-map of 16th-century Lublin (Google Maps API implementation) and modelling urban facilities with 3D technology (SketchUp & Unity). The designed technological solution is scalable, making it possible to search and combine individual records (e.g. person-event-address) as well as entire groups of records on higher hierarchical levels (social groups - sequences of events - multifaceted maps). The portal editing panel is dedicated to humanists (historians, journalists, sociologists, etc.) without specialist knowledge of GIS. The functions integrated with the CMS facilitate mapping the content collected in the database and embedding the narration in an adequate context of the historical space. As a result, editors preparing a thematic article have a searchable set of documents, facts, people and places at their disposal, and their task is to fill the narrative with descriptive content. This is a universal model for building deep maps and spatial narratives.

AUTOMATED CONTROL SYSTEM FOR THE OPERATION OF RENEWABLE ELECTRICITY SOURCES USING A DECISION TREE ALGORITHM

Effectively addressing the new challenges of renewable energy management requires innovations in power system modeling, operation and management. Through the efficient use of renewable energy sources, control systems are able to meet load demand and minimize energy costs. The aim of the study is to develop and create a distributed information system for analyzing, processing and storing meteorological data, improving the methodology for choosing the most efficient source of electricity, calculating and forecasting energy consumption indicators. The article describes the developed information system for the efficient use of renewable energy sources, which provides storage of meteorological information and decision-making on the appropriateness of using an energy source. Weather information is represented by the number of the station from which information is transmitted, the date and time of the research, the ultraviolet index, the wind power index, and the coordinate on the map. The operator has the ability to perform weather analysis for each station separately to plan the efficient operation of renewable electrical energy. The calculation of the power of the generated energy is performed, and its prediction is also performed based on the ARIMA model. The database is built on a relational data model, the PHP programming language and the phpMyAdmin DBMS were used to develop the application. Also, the Internet services Google Map API (to determine the coordinates of the location of the source of renewable energy of the settlement) and weatherbit.io (to determine the weather) were used.

Design and Implementation of a Vehicle Tracking Mechanism using Wireless Network Infrastructure

This study presents the design and implementation of a vehicle tracking system with the goal of assisting victims of road accidents in obtaining prompt assistance from the rescue team. This is accomplished by sending tracking data to the rescue team's mobile equipment. The system was developed utilising available electronics components, installed in a vehicle. Accident situations were recreated by dropping loads of different sizes from a height and loads linked to a rope to shatter the glass on the automobile in order to determine the minimal impart energy necessary to break the glass and the likelihood of a catastrophic accident. If an accident occurs, the GPS engine sends the coordinates of the crash site to the rescue team's mobile equipment through the SIM900 module's GSM engine over a GSM frequency for tracking. The system's tracking accuracy was determined using a standard GPS device, the GERMIN GPSMAP78s, to get the GPS coordinates of the scene and tracking them using the Google map API. When tracked using Google map, the tracking information obtained, when compared with the GARMIN GPSMAP78s, were exact, indicating that proposed device is capable of transmitting accurate tracking information in a short period of time, thereby saving lives.

Tour Guide Backpacker Application Designing Bengkulu City Based on Android

One of the trends in enjoying tourism that is currently developing is backpacking. Generally, backpackers are young tourists who want new experiences by doing tours at the least possible cost, they use conventional tourist transportation models and carry out their activities freely without hiring the services of a tour company. Backpacking has its own advantages but there are some issues especially for beginner backpackers. They will experience difficulties when traveling to an area that is rarely visited by other backpackers. For that we need an application that can be used as a reference for beginner backpackers who want to visit tourist areas, especially the city of Bengkulu. Applications that can accommodate data needs of a backpacker, especially regarding cheap hotel data, types of city transportation to take, recommended tourist attractions including the amount of costs required. The application will be integrated with firebase control so that the application becomes dynamic because the data is obtained from the database. To complete the application, the author will also use the google map API for more details about tourist locations, restaurants and inns that the user wants to visit. The frond end application can be run on the android operating system and is built using the java and xml programming languages, while the back end application is built using PHP and MySQL. To be able to display the map requires a separate API which is obtained from the google console. Applications use JSON data as a link between the front end and back end of the application. It is hoped that this application can help novice backpackers enjoy their travels in Bengkulu City which at the same time can be a guide for beginner backpackers who have never backpacked and do not understand the right and safe ways to travel to certain destinations with minimal costs.

Web Application based Image Geolocation Analysis to Detect Human Trafficking

Migrant smuggling is a dangerous phenomenon threatening international peace and security. This global concern for many countries is mainly due to the high use of multimedia devices and social media. There are great demands to specify an in depth gathering of information about a suspect’s mobile device while investigating cases of human trafficking and migrant smuggling. The primary purpose of this study is to help resolve the human trafficking problem that currently faces Sudan. In this paper we cover the steps used to geolocate images captured from suspects and victims’ mobile devices cameras. The obtained images are then analyzed using our specialized developed web application. This latter is built using open-source tools such as the Laravel framework and a Google Maps API which is considered as the main component of the web application. The results of the developed web application on a real case in Sudan has proven its usefulness in easing and speeding up the digital investigation process

Online Public Participation Geographic Information System (PPGIS) as a landscape and public use management tool: a case study from the Ebro Delta Natural Park (Spain)

This paper presents a Public Participation Geographic Information System (PPGIS) application conducted in the Ebro Delta Natural Park, Spain. It aims to support decision-making and management activities. The application is based on an online PPGIS questionnaire using Google Maps API. Participants were asked about the spatial and temporal usage while visiting the Natural Park, about their landscape preferences, and appreciations. A set of eight pairs of bipolar adjectives related to landscape characteristics and experience, four items related to public use, and nine to leisure activities were used. In total, 204 valid answers and 3,969 georeferenced opinions were mapped by this case study. The results of this mapping give insights in the use, perception and appreciation of landscape naturalness and aesthetic beauty, accessibility, facilities, services, and signposting. Furthermore, this study discuss the outcomes of mapping the results and how they support the park management with regard to the identification of conflicts, and the need for action. Finally, this study discuss potentials and limitations of PPGIS as a tool for public participation to capture visitors' experiential knowledge in order to optimize and enhance the management of protected areas.

Urban expansion and differential accessibility by car and public transport in the Greater Kumasi city-region, Ghana—A geospatial modelling approach

There is a growing recognition of the worsening problems of accessibility in Africa's major urban centres and city-regions. Yet, research assessing differential accessibility in these contexts is limited, partly because of the lack of population and land-use data at granular spatial resolutions. In this paper, we contribute to addressing the existing challenges by presenting a geospatial modelling approach that combines historical urban physical development data extracted from Landsat satellite images, travel time data from Openrouteservice and Google Maps API services, and relevant transport infrastructure data. We apply the approach to analyse place-based (100 m2) accessibility in the Greater Kumasi city-region of Ghana. The analysis reveals a strong co-evolutionary relationship between physical development and geographical accessibility, with an estimated 83% of the emergent physical development located within half-a-kilometre distance of a primary road. First-and-last-mile accessibility in terms of walking time to public transport stations and public transport service routes are quantified. We reveal huge first-and-last-mile accessibility deficits, with an estimated 14% and 33% of the city-region's built-up area having a 5-minute and 10-minute walking time reachability to a public transport station, as a critical node of accessibility. Differential accessibility by car and public transport is analysed, focusing on the city-region's most important functional centre (i.e. CBD). The results show that the CBD is within 15 min and nearly 30 min reach by car and public transport respectively, for only 1% of the city-region's built-up area. This implies that overall accessibility is poor regardless of mode choice, due to congestion. The findings underscore the need for integrative urban development and accessibility planning in the city-region for equitable transport and mobility outcomes.

Development of A Geographic Information System for The Distribution of Parks in Kediri City

The Department of Environment, Hygiene, and Parks is an agency that takes care of cleanliness and landscaping in Kediri. The distribution of parks in the Kediri City area is data and managed using a manual system using Microsoft Excel to get results in reports. For this reason, the Department of Environment, Cleanliness, and Parks requires an application that can be used to help manage data on the distribution of parks in the Kediri City area. The required system can manage park distribution data, display a park distribution map, and display the scale of conditions. The Geographic Information System for the Distribution of Parks in the City of Kediri was designed and built to meet the needs of the relevant agencies. Users of this system consist of visitors, admins, and heads of services. The system is designed and implemented using PHP, HTML, CSS, JavaScript, Mysql, and Laravel Framework, then integration with Google Maps API. The final result of this research is a Geographic Information System for the distribution of web-based parks in the City of Kediri using the Google map API as a provider of free maps that are integrated into the website. In addition, of course, it provides information about the distribution of the park and the scale of conditions.

Geographic Density of Linear Accelerators and Receipt of Radiation Therapy for Prostate Cancer

Radiation therapy (RT) is one among several definitive treatments for patients with prostate cancer. Recent analyses have suggested distance from a radiation oncologist influences the likelihood that a patient is to receive RT for their prostate cancer. We aimed to assess if linear accelerator density within healthcare referral regions (HRRs) impacts practice patterns regarding the treatment of prostate cancer patients.Along with the American Society for Radiation Oncology (ASTRO), we identified, and quality checked the location of linear accelerators in the United States as of July 2020, derived from the International Atomic Energy Agency Directory of Radiotherapy Centers (DIRAC) database. The address to each practice was geocoded using the Google Maps API within QGIS 3.12. The number of linear accelerators was determined in each HRR as defined by the Dartmouth Atlas; HRRs represent "regional healthcare markets for tertiary medical care." In 2014, the Dartmouth Atlas published data regarding the management of prostate cancer by HRR based on Medicare data from 2007 - 2011. Linear regression tested the association of linear accelerator density with receipt of prostate cancer radiation therapy.We identified 3,521 linear accelerators in the United States serving a population (as of the most recent US Census in 2010) of 309 million people; this represents approximately 88,000 people per linear accelerator, or 11.4 linear accelerators per million people. Among the 306 HRRs, the mean density of linear accelerators is 11.7 per million (standard deviation 5.2); 5 HRRs do not have a linear accelerator. For 227 HRRs, data regarding the proportion of Medicare beneficiaries over the age of 75 with prostate cancer who received RT was available. For every 1 additional linear accelerator per million, an additional 2.1 prostate cancer patients per 1,000 received RT (95% CI: 0.08 - 4.2; P = 0.04). For 234 HRRs reporting the number of prostatectomies per 1,000 Medicare beneficiaries under 75 with prostate cancer, there was no relationship between prostatectomy rate and number of linear accelerators (P = 0.42).Increasing HRR linear accelerator density is associated with increasing rate of receipt of radiotherapy for prostate cancer in elderly men. These findings need to be explored across other disease sites and age ranges to ascertain the magnitude of this effect and optimize the distribution of linear accelerators to best ensure access to care across the geographic spectrum.

RANCANGAN APLIKASI PENCARIAN JALUR TERPENDEK DENGAN PENDEKANAN GEOGRAPHIC INFORMATION SYSTEMS DAN DIJKSTRA'S ALGORITHM

Islamic boarding schools play a role in developing the independent character of students, however, in addition to the large role of boarding schools, there are still many obstacles, namely the difficulty of obtaining accurate information about the existence of boarding schools. Currently, to obtain information about Islamic boarding schools in Pandeglang Regency, they still use conventional methods, like coming directly to the location of the boarding school. There are even some boarding schools whose information cannot be found, so we need a solution to solve these problems by utilizing information technology and computers. Researchers offer a solution to overcome this problem by utilizing information system technology, namely Geographic Information Systems by utilizing Google Maps as a map provider and Dijkstra's Algorithm as a method to find the shortest path from one point to another on a graph. This research produces a digital map application on the web by utilizing the Google Maps API and Web Service using the Apache Web Server to retrieve data from the MySQL database.The goal to be achieved in this research is to build a Geographic Information System (GIS) for boarding schools that can be used to provide information about the map of the location of boarding schools in the Pandeglang Regency area along with other supporting information in the boarding schools.