A Take on Geo-informatics Systems with Pin-Codes as Atomic Unit
Siddharth Gupta1, Abhinav Rana2, M.Lakhsmi3
1Siddharth Gupta*, Department of Computer Science and Engineering, SRM Institute of Science and Technology,Chennai (Tamil Nadu), India.
2Abhinav Rana, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3Dr. M. Lakhsmi, Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on March 12, 2021. | Revised Manuscript received on March 20, 2021. | Manuscript published on March 30, 2021. | PP: 13-16 | Volume-10 Issue-4, March 2021. | Retrieval Number: 100.1/ijsce.D34840310421 | DOI: 10.35940/ijsce.D3484.0310421
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Rural areas in India may not necessarily have internet connection and what if they need to know about nearest hospitals, fire stations or if a message has to be broadcasted over a large section of this area. This paper tries to solve all of these problems by implementing a pin-code based approach to map these important locations. Now a days, more advanced technologies such as GPS are more useful in solving these problems in real-time but what this paper tries to do is solve them statically where technology can’t take precedence over daily lives. It discusses a smart, fast algorithm with minimum memory overhead to solve these specific issues. Lack of data sets are a concern in this approach but to automate this we have used Image Processing to automatically detect boundaries of pin-codes on various sub-regions to form a universal Graph which can then be subjected to various algorithms like A*, DFS, BFS, Dijkstra which are local to each type of problem. This leaves scope for further research on developing models that can read images of maps more efficiently to create more accurate data sets which are accurate enough and void of longitudinal and latitudinal details.
Keywords: DFS, BFS, Dijkstra Which Are Local to Each Type of Problem.