Authors :
Vedant Wagh; Ayush Vishwakarma
Volume/Issue :
Volume 9 - 2024, Issue 12 - December
Google Scholar :
https://tinyurl.com/adky8esb
Scribd :
https://tinyurl.com/2twxpf4w
DOI :
https://doi.org/10.5281/zenodo.14575910
Abstract :
Google Map has been giving us the best results
as promised since 2007 without ever failing. It also keeps
upgrading the data and eventually integrated my location
service. However, occasionally Google Map does not
function as intended when displaying the quickest routes.
It's because the geospatial data isn't updated frequently.
It takes a certain amount of time to update the data.
Here, we've spoken about how it occasionally
malfunctions and how it provides us with a route that
accurately forecasts the outcome. In order to tackle the
challenge of identifying a destination using
approximation parameters, we reviewed the Google
Maps technique in this study and suggested a system.
The issue is that if we want to locate a restaurant
from source S that is decent and has average costs, the
map should provide the path of the restaurant that is not
the closest but effective by taking into account factors
like the restaurant bill, distance, travel costs, service
time, etc.
References :
- H. Li and L. Zhijian, "The study and implementation of mobile GPS navigation system based on Google Maps," 2010 International Conference on Computer and Information Application, Tianjin, China
- Z. Xiaofang, Z. Xu and Hejiang, "Research on satellite selection and search strategy of constellation autonomous navigation," 2022 34th Chinese Control and Decision Conference (CCDC), Hefei, China.
- S. Nanda, M. Ranjan Mishra, A. Narayan Brahma, S. Chandra Swain, S. Shekhar Patra and R. Kumar Barik, "Performance Analysis of Geospatial Serverless Computing for Geospatial Big Data Analysis," 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC), Coimbatore, India
- M. Ouyang et al., "Network Coding-Based Multipath Transmission for LEO Satellite Networks With Domain Cluster," in IEEE Internet of Things Journal
- G. Yuxuan, L. Yue and S. Penghui, "Research Status of Typical Satellite Communication Systems," 2021 19th International Conference on Optical Communications and Networks (ICOCN), Qufu, China
- P. Martin, E. Marchand, P. Houlier and I. Marchal, "Mapping and re-localization for mobile augmented reality," 2014 IEEE International Conference on Image Processing (ICIP), Paris, France
- H. Zhang, M. Li, Z. Chen, Z. Bao, Q. Huang and D. Cai, "Land use information release system based on Google Maps API and XML," 2010 18th International Conference on Geoinformatics, Beijing, China
- R. Ding et al., "5G Integrated Satellite Communication Systems: Architectures, Air Interface, and Standardization," 2020 International Conference on Wireless Communications and Signal Processing (WCSP), Nanjing, China
- T. Geller, "Imaging the World: The State of Online Mapping," in IEEE Computer Graphics and Applications
- A.Dhoke and P. Shankar, "Exploring the Complexities of GPS Navigation: Addressing Challenges and Solutions in the Functionality of Google Maps," 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA), Pune, India.
- Y. Dian Harja and R. Sarno, "Determine the best option for nearest medical services using Google maps API, Haversine and TOPSIS algorithm," 2018 International Conference on Information and Communications Technology (ICOIACT), Yogyakarta, Indonesia
- O. Verenych, S. Bezshapkin, I. Vasyliev and D. Verenych, "GIS-Technologies Using for Spatial Data Analyse of the Road Traffic Accidences on the Example of Kyiv," 2019 IEEE International Conference on Advanced Trends in Information Theory (ATIT), Kyiv, Ukraine
- J. -R. Jiang, H. -W. Huang, J. -H. Liao and S. -Y. Chen, "Extending Dijkstra's shortest path algorithm for software defined networking," The 16th Asia-Pacific Network Operations and Management Symposium, Hsinchu, Taiwan
- T. Cieslewski, S. Lynen, M. Dymczyk, S. Magnenat and R. Siegwart, "Map API - scalable decentralized map building for robots," 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA
- Bozyiğit, G. Alankuş and E. Nasiboğlu, "Public transport route planning: Modified dijkstra's algorithm," 2017 International Conference on Computer Science and Engineering (UBMK), Antalya, Turkey
- K. Wei, Y. Gao, W. Zhang and S. Lin, "A Modified Dijkstra’s Algorithm for Solving the Problem of Finding the Maximum Load Path," 2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT), Kahului
Google Map has been giving us the best results
as promised since 2007 without ever failing. It also keeps
upgrading the data and eventually integrated my location
service. However, occasionally Google Map does not
function as intended when displaying the quickest routes.
It's because the geospatial data isn't updated frequently.
It takes a certain amount of time to update the data.
Here, we've spoken about how it occasionally
malfunctions and how it provides us with a route that
accurately forecasts the outcome. In order to tackle the
challenge of identifying a destination using
approximation parameters, we reviewed the Google
Maps technique in this study and suggested a system.
The issue is that if we want to locate a restaurant
from source S that is decent and has average costs, the
map should provide the path of the restaurant that is not
the closest but effective by taking into account factors
like the restaurant bill, distance, travel costs, service
time, etc.