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Publication Type : Journal Article
Source : International Journal of Research in Electronics & Communication Technology (IJRECT) ,ISSN Print:2348-0017 ISSN Online: 2347-6109,Vol2
Url : https://iaeme.com/MasterAdmin/Journal_uploads/IJRECT/VOLUME_2_ISSUE_2/IJRECT_02_02_006.pdf
Keywords : Location Based Services (LBS), GPRS, Crowdedness Monitoring Service, Estimated Mean Crowdedness
Campus : Chennai
School : School of Computing
Department : Computer Science and Engineering
Year : 2014
Abstract : This project paper proposes a new Location Based Service (LBS) which can be suitably implemented in required locations. For example, if many people Check-in in a particular location, it means that the location is crowded. Users find it difficult to manage their daily activities (e.g. paying a bill, shopping, and bank works etc.,), because unexpected crowdedness in a location will cause undue delay in their daily works. The described service here is the function of finding the less crowded location. Thus users can plan their daily works in a more efficient way. To implement these services, two types of Check-in may be used. They are Active Check-in and Passive Check-in. In our proposed model kit, we have employed Active Check-in using a finger print module. The embedded microcontroller ARM 11 is used as a database server. The regular customers in a particular location are registered using their finger prints. The registered users’ database is stored in the micro controller. A GPS module is used to provide location data information. A customer entering that location has to do active check-in i.e. he has to do thumb impression in the finger print module. If he is a registered customer, then the microcontroller will send information details of him to a web server through a GPRS module. The Name, Designation, Check-in time and Location details are displayed in the web server. If the customer is not a registered customer, then he is recognized as an unauthorized person. We can see this displayed information from the web server at any place. From these details, we can identify the number of customers in that location and also who the customers are at present in that location. We can decide whether to go to that location now or sometime later. This will also be helpful for higher authorities of that location to modify the services offered in that location based on the number of customers.