Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12323/7668
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dc.contributor.authorMustafayev, Mustafa Azer-
dc.date.accessioned2024-09-30T06:26:26Z-
dc.date.available2024-09-30T06:26:26Z-
dc.date.issued2024-
dc.identifier.urihttp://hdl.handle.net/20.500.12323/7668-
dc.descriptionSchool: Graduate School of Science, Art and Technology Department: Computer Science Qualification: Software of Computer Systems and Networks Supervisor: Assoc. Prof. Dr. Leyla Muradkhanli Gazanfaren_US
dc.description.abstractThis thesis presents the development and implementation of an Android application designed to find the optimal meeting point for users based on their geographic locations. Leveraging Google APIs, the application gathers users' positional data and calculates a central, convenient location for all parties involved. The primary goal is to enhance social interactions and logistical coordination by simplifying the process of finding a mutually agreeable meeting point. The application integrates several Google APIs, including the Google Maps API for location visualization, the Places API for point-of-interest searches, and the Distance Matrix API for calculating travel distances and times. By utilizing these tools, the application can provide real-time, accurate suggestions for meeting locations that minimize travel time and distance for all users. The core algorithm considers various factors such as the geographic distribution of users, transportation modes, and real-time traffic conditions. Users can input their current locations or allow the application to detect their positions automatically. The system then computes potential meeting points and ranks them based on accessibility, travel time, and user preferences. This dynamic approach ensures that the suggested meeting points are practical and efficient. Usability and user experience are critical components of the application design. The interface is intuitive, with clear visual representations of suggested meeting points on a map, along with detailed information about each location, including distance, estimated travel time, and nearby amenities. Feedback mechanisms are incorporated to continually improve the accuracy and relevance of the meeting point suggestions. Through extensive testing and user feedback, the application has demonstrated its utility in various scenarios, from casual social gatherings to professional meetings. The results indicate a significant reduction in the time and effort required to coordinate meetups, thereby enhancing overall user satisfaction. In conclusion, this Android application exemplifies how leveraging advanced location-based services and algorithms can streamline the process of finding optimal meeting points, ultimately fostering more efficient and enjoyable social and professional interactions.en_US
dc.language.isoenen_US
dc.relation.ispartofseries;Master thesis-
dc.titleImplementation of shortest route algorithms in Smart Cityen_US
dc.title.alternativeAğıllı şəhərdə ən qısa marşurutun tapılması alqoritmien_US
dc.typeThesisen_US
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