Akanksha choose their wished product and carry the products

Akanksha Ambavade1, Sagar Rathod 2,
Prashant More3, Anuja Doke 4

Prof. S.V.Athawale 5
(Guide), Computer Department, A.I.S.S.M.S. C.O.E,

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1, 2, 3, 4Computer Department, A.I.S.S.M.S. C.O.E.



Abstract— Big
shopping malls usually provide a directory to their available shops, but these
directories are most of the time static and do not provide any interactivity
features to the visitors. In this work, we present a mobile shopping mall
navigator. The main reason behind our conceptual idea of our proposed project
is because we feel that when visitors often change their plan to go to other
shops instead of the ones in their minds, it can be full of effort especially
considering the crowded levels and location of the navigation material. The
application developed is practical and feasible; Smart phones have become very popular these
days, so we have combined the idea. Smart phone application helping you in an
alienated mall. The idea revolves around our smart phones & the

“Wi-Fi” provided by the
mall. An application that needs real-time, fast, & reliable data



Technical Keywords —  Indoor navigation, barcode
scanner, Wi-Fi router



Shopping is the traditional way of shopping where the customers choose their
wished product and carry the products along with them. Traditional shopping is
a tedious and time consuming job. In traditional shopping, the customer has to
wait in long queues at the cash counter. This consumes lot of time and energy
of both the shopper as well as cashier. To overcome this law, the customer himself
can scan the barcode using his mobile while making purchase, retrieve essential
details of all products from shops database and generate bill himself. This
bill can be sent to the customer’s mobile through online banking service thus
the user can make quick payment and leave the shop early. The Barcode of the
product is scanned by the customer and move to the wish list if they are interested
in choice of item by using the proposed mobile application. In order to develop
an Android Application that uses a barcode scanner for the purchasing and
navigation of items for store that will be self-checking and automatic payment
transaction. Here comes the term indoor navigation and barcode scanning. Indoor
positioning is still a challenging problem because satellite-based approach do
not work properly inside buildings.


are ubiquitously used to identify products, goods or deliveries. Devices to
read barcodes are all around, in the form of pen type readers, laser scanners or
LED scanners. Camera-based readers, as a new kind of barcode reader, have
recently gained much attention. The interest in camera-based barcode
recognition is built on the fact that numerous mobile devices are already in
use, which provide the capability to take images of a fair quality. This
describes the hardware system architecture for implementing the barcode reading
system in mobile phones and its process. The camera device and application
processors are necessary hardware components for the system. The application
processors is needed to implement the camera interface, LCD controllers , DSP
for image processing, and application host in CPU for real-time computations.
The application processor works for displaying the menu and preview of the
display and computing of code recognition and decoding in real-time. With these
systems, the user can control the position of the camera of smart-phone and
decides the capture timing of barcode.


Related Work


and reliable real-time indoor positioning on commercial Smart-Phones


Author: Gennady Berkovich

This paper outlines the software navigation engine that was developed by SPIRIT
Navigation for indoor positioning on commercial smart-phones. A distinctive
feature of our approach is concurrent use of Wi-Fi and BLE modules, together
with the floor premises plan are used for hybrid indoor positioning in the
navigation engine. Indoor navigation software uses such technologies as PDR and
map matching. There is no need to enter initial position manually where it can
be determined by GPS/GNSS (Global Navigation Satellite Systems) receiver. The
automatic recovery of tracking in this case allows continuing tracking and
increasing availability of indoor navigation. Positioning results given for
different indoor environments in a shopping mall with accuracy of about 1-2 m.


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