Maps API Research Articles

Android Based Disaster Management Application Using Machine Learning

A good saying” Precaution is better than cure” for emergency situations. Natural disasters in India, many of them related to the climate of India, cause massive losses of Indian life and property. Droughts, flash floods, cyclones, avalanches, landslides brought on by torrential rains and snowstorms pose the greatest threats. Landslides are common in the Lower Himalayas. Parts of the Western Ghats also suffer from low-intensity landslides. Floods are the most common natural disaster in India. Therefore, developing a system which can monitor as well as providing instructions on basis of current disaster using Supervised learning, reducing time for quick actions, Google map API for locating nearby locations, Disaster prediction using data analytics. The mobile application will have four tabs: Alert buzzer, weather forecast, the menu tab and the communication forum. Furthermore, the system notifies the users through SMS and even through the forum whenever there is the alert notification posted on the application Using system can help a great deal in the planning and implementation of disaster mitigation schemes. Keywords: ML-Machine Learning, SVM-Support Vector Machine, NDRF-National Disaster Response Force, SDRF-State Disaster Response Force

Bank agglomeration and corporate environmental responsibility performance: Evidence from Chinese bank branch data

While corporate environmental responsibility (CER) has attracted widespread attention in recent years, there is still very little understanding as regards whether bank agglomeration affects CER practices. This study has measured the agglomeration of bank branches around Chinese listed enterprises from 2011 to 2020 using Python and the Baidu Map API. For the first time, the study has revealed that, bank agglomeration can have a positive impact on CER practices by reducing financial constraints on enterprises and fostering green business practices. This impact is more significant for private enterprises, enterprises with high costs of equity, enterprises in non-pollution-intensive industries, and enterprises in highly marketized regions. CER performance can be better enhanced by the clustering of state-owned, local, and foreign bank branches around enterprises. In addition, the entry and exit of bank branches can improve CER performance as it can foster the effective allocation of financial resources, and this effect is more evident for private enterprises. To conclude, this study has evaluated the value of bank branch evolution for the environment and society of emerging countries.

Restricted but satisfied: Google Maps and agency in the mundane life

The study grasps the transformation of agency in the context of mundane production and use of mapping apps. It is asked theoretically and empirically, who produces and maintains Google Maps as cartographic infrastructure and how is this kind of agency being reflected and acted upon from a lifeworld perspective. Firstly, findings are compiled from various interdisciplinary studies on digital cartography, platform capitalism and digital infrastructures. Since these studies focus on agency almost exclusively from a structural perspective, a qualitative study is conducted to explore the use of Google Maps in everyday life. 20 interviews with German users show that digitalization and datafication profoundly change the dynamics of how agency is perceived and reflected. It can be understood as a form of extension of agency because it is deeply rooted in the entanglement of Google Maps’ infrastructure and city dwellers everyday practices.

RANCANG BANGUN SISTEM INFORMASI PENGELOLAAN WISATA PULAU RANOH BERBASIS WEBSITE

The purpose of making the Design and Development of a Website-Based Ranoh Island Tourism Management Information System is to promote and facilitate booking of tour packages on Ranoh Island. Web-based visual information system is a system consisting of text and graphic images. It is these factors that make these tours interesting and make bookings easy. In addition, the Website-Based Ranoh Island Tourism Management Information System is a system that contains complete information for tourists and can be found at any time. This support cannot be separated from the research process design and technology. This study aims to design a Website-Based Ranoh Island Tourism Management Information System as a source of information for viewing and ordering tourist attractions and other facilities on Ranoh Island. The Website-Based Ranoh Island Tourism Management Information System was developed using the PHP programming language and data stored in a database using MySQL to optimize system and database performance. The Google Maps API is one of the features of this information system that can be used to add maps to websites using JavaScript. The result of the design is a web tourism information system which should be a way to promote tourism in the city of Batam, so that through this web design it is hoped that there will be a similar system to create better services. and more complete than existing services.

RANCANG BANGUN SISTEM INFORMASI JASA SERVICE AC DI KOTA BATAM BERBASIS WEB

The goal of creating a web-based information system about air conditioning services in Batam City is to provide air conditioning services in Batam City. Web-based information systems come in the form of images, text, graphics, and sound. That's why it makes advertising or promotion more attractive. In addition, the web-based ac service information system becomes a comprehensive information system for users or visitors that can be found anywhere. This support is inseparable from the design and technology of the research process. For other media, the success of the media is determined by the success of the well conveyed message. This study aims to design a web-based information system for air conditioning services in Batam city as a source of information to find air conditioning services with other facilities in Batam. Batam City's service system is developed using PHP programming language and data is stored in a database using HeidiSQL to optimize system and database performance. The Google Maps API is one of the features of this information system that can be used to add maps. The result of the design is in the form of a web-based information system for ac services, which is expected to be the means of service delivery and other ac service facilities in Batam city, thus , through this web design, hope that there will be a similar system to create better services. and more comprehensive than existing services. .

Container Infrastructure on Laravel to Improve Online Shop

A laundry business is a business that operates laundry services or similar and is often used by the general public. The development of this business is quite fast, as many consider renting laundry to be more convenient. This rapid increase is inversely proportional to the evolution of companies in using technology as a means of digitizing their businesses. The digitization process can make it easier for business owners to manage, monitor, promote, and receive business reviews. One attempt to overcome this is to develop a web-based laundry management and publishing application using the Laravel framework and container infrastructure, with the aim of making business management and advertising easier for laundry entrepreneurs and customers to choose from to facilitate washing area. This study uses data collection techniques in the form of literature reviews, questionnaires and uses technologies to facilitate the development process such as the Laravel framework, MySQL, Google Maps API, and container and waterfall infrastructure as application development methods. The test technique used is black box. The result of the research is a web-based laundry application that conforms to the eight golden rules, has been tested by laundry owners and customers, and can achieve the research goals.

Surviving the pandemic: COVID-19 and restaurant closures in Suzhou

ABSTRACT The outbreak of COVID-19 disrupts the economy and presents challenges to small and medium enterprises in various sectors. Focused on the restaurant industry in Suzhou, China, this study draws upon secondary data from Meituan Dianping and Baidu Map API and considers how variables related to restaurants themselves and variables pertaining to restaurants’ built environment conditions contribute to their survival during the pandemic with the use of regression analysis. For restaurants, it is important to have certain core competencies, such as price or quality advantage, if they were to survive external shocks. In addition, high population density of a restaurant’s surrounding area, one of the most crucial factors in determining business success under normal circumstances, significantly reduces its survival likelihood during the pandemic. We conclude by outlining opportunities for future research. Highlights This study examines what determines restaurant survival in the pandemic. The survival is influenced by both restaurant and built environment factors. Restaurants need to have specific core competencies to survive market shocks. Density and accessibility have adverse impacts on restaurant survival. The analysis provides policy suggestions for similar circumstances in the future.

Exploring the spatial dynamics of cultural facilities based on multi-source data: A case study of Nanjing’s art institutions

Abstract Examining the spatial characteristics and accessibility of cultural facilities, such as art institutions, is crucial for understanding the lifestyles of citizens. With the increasing utilization of multi-source data in geographical studies, new opportunities have arisen for investigating the development of cultural facilities in urban areas. Consequently, this article investigates the spatial dynamics of art institutions in urban development, using Nanjing, a historic city, as a case study. The study obtained a total of 260,392 points of interest data for Nanjing in 2018 and 2022 from the GaoDe map API console. By employing network analysis and the two-step floating catchment area method, the geostatistical findings reveal that the distribution of art institutions in Nanjing has become more balanced over time. For instance, the research indicates that the proportion of residents able to reach art exchange institutions within a 30-min travel time increased from 75% in 2018 to 90% in 2022. However, the distribution of art training institutions remains more concentrated compared to art exchange institutions. Furthermore, the spatial arrangement of art institutions does not entirely align with the distribution of demand points, indicating the potential for further optimization. In conclusion, this study has significant implications for understanding the accessibility, social justice, and urban planning in Nanjing. The government should pay attention to the cultural demands of marginalized communities, promote social justice and cultural inclusiveness by increasing the accessibility of cultural facilities.

Estimation of the aggregation degree of public transport use among elderly people based on urban built environment

With the accelerated aging process, the increased willingness of elderly people to travel, and the concessionary bus travel policy implementation, public transport, especially buses, has become one of the important ways for China's elderly people to participate in social activities. Meanwhile, the increased use of public transport by elderly people results in serious conflicts with commuters. In order to understand details about when, where and why public transport trips of the elderly become large, this study investigates the aggregation degree of public transport use among the elderly as well as its determinants mainly from the viewpoint of spatial characteristics. Based on Smart card data and Baidu Map API, the aggregation degree of public transport use in elderly people is rated on a scale of 1 to 5. And then its correlation to the microscopic built environment is analyzed by using negative binomial regression. The results indicate that public transport use by elderly people is highly aggregative in both spatial and temporal dimensions. It is also found that the urban built environment has a significant effect on the aggregation degree of public transport use in the elderly and significant variables for four time periods on both weekdays and weekends are quite different. The proximity of housing estates, elderly activity centers, universities for the elderly, and medical and shopping facilities near bus stations increases the aggregation degree of public transport use by elderly people. This study will provide a reference basis for optimizing the public transport system in the aging society.

A-VRPD: Automating Drone-Based Last-Mile Delivery Using Self-Driving Cars

Drone-based last-mile delivery is an emerging technology that uses drones loaded onto a truck to deliver parcels to customers. In this paper, we introduce a fully automated system for drone-based last-mile delivery through incorporation of autonomous vehicles (AVs). A novel problem called the autonomous vehicle routing problem with drones (A-VRPD) is defined. A-VRPD is to select AVs from a pool of available AVs based on crowd sourcing, assign selected AVs to customer groups, and schedule routes for selected AVs to optimize the total operational cost. We formulate A-VRPD as a Mixed Integer Linear Program (MILP) and propose an optimization framework to solve the problem. A greedy algorithm is also developed to significantly improve the running time for large-scale delivery scenarios. Extensive simulations were conducted taking into account real-world operational costs for different types of AVs, traveled distances calculated considering the real-time traffic conditions using Google Map API, and varying load capacities of AVs. We evaluated the performance in comparison with two different state-of-the-art solutions: an algorithm designed to address the traditional vehicle routing problem with drones (VRP-D), which involves human-operated trucks working in tandem with drones to deliver parcels, and an algorithm for the two echelon vehicle routing problem (2E-VRP), wherein parcels are first transported to satellite locations and subsequently delivered from those satellites to the customers. The results indicate a substantial increase in profits for both the delivery company and vehicle owners compared with the state-of-the-art algorithms.

The Comparison of Distance Methods on The On-Demand Ambulance Application

The on-demand ambulance is an application service that can be used to connect hospital ambulances or NGOs with people who need ambulance services. In this application, there is a geolocation feature service that is implemented with the distance calculation method, so that the feature gets the optimal distance with high accuracy. There are 3 distance search methods used in testing the distance search method, namely the haversine method, the Euclidean method, and the spherical triangle law of the cosine method. This study was conducted by utilizing data collected from the Google Maps API and obtained an accuracy of 100% for the haversine and spherical triangle law of cosine methods, while the accuracy was 89.95% for the Euclidean method. 
 
 Keywords—Distance Method; Haversine; Euclidean, Spherical Triangle Law of Cosine

Map API-Based Evacuation Route Guidance System for Floods

Recently, human casualties and property damage caused by natural disasters have increased worldwide. Among these natural disasters, flood damage is affected by season. Depending on the concentration of precipitation in the summer, heavy rainfall can occur, thus resulting in typhoons, floods, and increased damage. To prevent such damages, the appropriate measures and research are being conducted in response to disasters. When a flash flood occurs, safe evacuation can be realized after detecting the situation and using announcements or laser indicators. However, these route guidance systems are typically used in fire or indoor environments, thus rendering them difficult to access outdoors. Therefore, we herein propose an evacuation route guidance system based on a map API that recognizes flood occurrences in forest areas, recreational forests, and parks. It calculates the route based on the map API and delivers the evacuation route to the nearest shelter to the user; and if there is a second problem on the moving evacuation route and it is difficult to proceed, the user’s current location is identified and the route to the next nearest shelter is provided. This will help you to evacuate safely.

Visualizing Google Sheets Data in Web Applications with Laravel

The study presents the design implementation of visualizing Google Sheets data in web applications using the Rapid Application Development (RAD) approach. It focuses on integrating Google Sheets data seamlessly into a web application using the Laravel PHP framework and employs effective data visualization techniques. Real-time data access is achieved through the integration of Google Sheets API, while the Google Maps API and High charts Library enabled interactive and informative data visualizations. The result is a user-friendly web application, empowering users to explore data insights and make well-informed decisions with ease

Genetic Algorithm Application in Route Optimization Using Google Maps API

Route planning from several locations is a common problem encountered. Google Maps provides a feature to plan routes from multiple location but does not provide a feature to find the optimal route from these locations. Based on the survey, 61.9% of respondents have a low level of confidence when planning the optimal route from several locations. So we need software that can help in planning the route. This research utilizes genetic algorithms to help plan routes from several locations. The genetic algorithm used includes components in the form of chromosomes, fitness values, selection, crossover, and mutations. In addition, Google Maps API used as the data source that provides maps, directions, and distance matrices. The design method used extreme programming. The software is made using HTML, CSS, PHP, and JavaScript programming languages with MySQL DBMS. In addition, Black-box and White-box testing method is used in this research. The results of this study are route optimization software that works by using genetic algorithm components to obtain optimal route from several locations with the advantages of using Google Maps API and selecting location points and starting points that are flexible. This study aims to highlight the benefits, limitations, and future prospects of route optimization. The findings of this research will contribute to assist decision-makers in adopting effective strategies related to route optimization.

Sistem Monitoring Deteksi Kebakaran Bangunan Berbasis IOT dan Android dengan Google Maps API

Fire is a natural disaster which is threateing and interfering life that was caused by nature, non-nature, so that the disaster will causing, casunlties, property loss also affecting psychologis. Designing structur whice expected could, defecting a fire base on the level of smoke concentration and flame which is happend in a building also sending a notice to the fire sighting unid. Designing system monitoring stucture using android with the use of Google map API as a location determination tool of the information of where the fire accured, so that owner of the building and the fire fight could geting a realtime effecture informetion using app base an android with internet of things and Google maps, utilized the use of internet of things also can be view of sends an information between cencor so in order that owner of the building can also monitoring online by the used of Google maps. Google maps is functioning to send position of the fool which was installed in the building the resuld foud that flame cencor could detecting the source of fire using wave length of light between 0 – 1032 nm and smoke cencor could detecting smoke concentration between 100 – 5000 ppm the with the use of MQTT protocol it will directly send to android. android can monitoring the fire information after that is determine the location of the fire by Google maps

Development, Calibration, and Validation of a Large-Scale Traffic Simulation Model: Belgium Road Network

Development of large-scale traffic simulation models have always been challenging for transportation researchers. One of the essential steps in developing traffic simulation models, which needs lots of resources, is travel demand modeling. Therefore, proposing travel demand models that require less data than classical travel demand models is highly important, especially in large-scale networks. This paper first presents a travel demand model named as probabilistic travel demand model, then it reports the process of development, calibration and validation of Belgium traffic simulation model. The probabilistic travel demand model takes cities' population, distances between the cities, yearly vehicle-kilometer traveled, and yearly truck trips as inputs. The extracted origin-destination matrices are imported into the SUMO traffic simulator. Mesoscopic traffic simulation and the dynamic user equilibrium traffic assignment are used to build the base case model. This base case model is calibrated using the traffic count data. Al-so, the validation of the model is performed by comparing the real (extracted from Google Map API) and simulated travel times between the cities. The validation results ensure that the model is a superior representation of reality with a high level of accuracy. The model will be helpful for road authorities, planners, and decision-makers to test different scenarios, such as the im-pact of abnormal conditions or the impact of connected and autonomous vehicles on the Belgium road network.

A COMPARATIVE STUDY OF METHODS FOR DRIVE TIME ESTIMATION ON GEOSPATIAL BIG DATA: A CASE STUDY IN USA

Abstract. Travel time estimation is crucial for several geospatial research studies, particularly healthcare accessibility studies. This paper presents a comparative study of six methods for drive time estimation on geospatial big data in the USA. The comparison is done with respect to the cost, accuracy, and scalability of these methods. The six methods examined are Google Maps API, Bing Maps API, Esri Routing Web Service, ArcGIS Pro Desktop, OpenStreetMap NetworkX (OSMnx), and Open Source Routing Machine (OSRM). Our case study involves calculating driving times of 10,000 origin-destination (OD) pairs between ZIP code population centroids and pediatric hospitals in the USA. We found that OSRM provides a low-cost, accurate, and efficient solution for calculating travel time on geospatial big data. Our study provides valuable insight into selecting the most appropriate drive time estimation method and is a benchmark for comparing the six different methods. Our open-source scripts are published on GitHub (https://github.com/wybert/Comparative-Study-of-Methods-for-Drive-Time-Estimation) to facilitate further usage and research by the wider academic community.

Development of an Android-Based Cultural Heritage Map App

This study aims to (1) develop an Android-based cultural heritage map app that can provide the location of cultural heritages in the Special Region in Yogyakarta along with its descriptions, images, and videos; and (2) understand the quality of the app based on standard software quality testing ISO / IEC 25010 on functional suitability, performance efficiency, and compatibility. The development method utilized a waterfall software development model that consists of communication, planning, modeling, construction, and deployment. The results of this study are 1) an Android-based cultural heritage map app that can provide the location of cultural heritages in the Special Region of Yogyakarta along with its descriptions, pictures, and videos. and 2) the test results indicate the app meets the standards of ISO / IEC 25010 on the aspect of (1) functional suitability, entire functions of the app running 100%, (2) the compatibility of the app, compatible 100% of the co-existence, various operating systems, device types, and screen dimensions, (3) performance efficiency, the app successfully executed in 312 of the 321 test devices without any memory leak with the average of time behavior, CPU utilization, and memory utilization for Dalvik Virtual Machine are 0.022 seconds/thread, 10.71%, and 33.11 MB and the average of time behavior, CPU utilization, and memory utilization for Android Run Time are 0.020 seconds/thread, 9.9918%, and 154.582 MB.

Aplikasi SIG Berbasis Web Pemetaan Lokasi Toko Oleh Oleh di Kota Batam

Abstract
 The development of technology today is very undoubted so that information is easy to access anytime and anywhere. The ease of accessing information gives new enthusiasm for humans in developing information technology or commonly referred to as Geographic Information System (GIS). The definition of GIS itself is a special information system that manages data that has special information, or it can also be interpreted as information about the place or location where the geographical location is located. Batam city is one of the cities in the Riau archipelego province. Batam is famous as a location visited by foreign and domestic tourists. Tourists that visit Batam city have a habit of bringing food as souvenirs from Batam. However, tourists and local people sometimes have difficulty in finding the location of stores that sell food souvenirs. This study aims to develop a Geographic Information System application that maps the location of gift shops in Batam. The result of this study is web-based GIS applications, which uses Google Maps API to display maps and retrieve store location coordinates. Through the application, the tourist can be helped in finding the location of souvenir shops in the city of Batam.
 Keywords: GSeographical Information System, Gift Shop, Google Maps API, Web based GIS.

Aplikasi Penentuan Rute Terpendek Pengambilan Sampah Berbasis Internet of Things Terintegrasi Dengan Google Maps API

Solid waste is a sensitive issue involving serious environmental problems in the world today. The situation of direct disposal of waste without proper inspection and segregation has left a serious impact on environmental pollution which has led to a tremendous growth in health problems. This study aims to monitor the level of fullness of waste in trash cans, send the results to a Google map using the Google Maps API and determine the shortest route for waste collection based on the level of fullness of waste. The android application was developed to make it easier for users to find out which trash cans are full and need to be taken immediately and to determine the shortest route using google maps.