Akanksha a directory to their available shops,

 Akanksha Ambavade1, Sagar Rathod 2,Prashant More3, Anuja Doke 4Prof. S.V.Athawale 5(Guide), Computer Department, A.


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

I.S.S.M.S. C.O.E.

  Abstract— Big shopping malls usually provide a directory to theiravailable shops, but these directories are most of the time static and do notprovide any interactivity features to the visitors. In this work, we present amobile shopping mall navigator. The main reason behind our conceptual idea ofour proposed project is because we feel that when visitors often change theirplan to go to other shops instead of the ones in their minds, it can be full ofeffort especially considering the crowded levels and location of the navigationmaterial. The application developed is practical and feasible; Smart phones havebecome very popular these days, so we have combined the idea.

Smart phoneapplication helping you in an alienated mall. The idea revolves around oursmart phones & the “Wi-Fi” provided by the mall. An application that needs real-time,fast, & reliable data processing.  Technical Keywords —  Indoor navigation, barcodescanner, Wi-Fi router I.     Introduction                Manual Shopping is thetraditional way of shopping where the customers choose their wished product andcarry the products along with them.

Traditional shopping is a tedious and timeconsuming job. In traditional shopping, the customer has to wait in long queuesat the cash counter. This consumes lot of time and energy of both the shopperas well as cashier.

To overcome this law, the customer himself can scan thebarcode using his mobile while making purchase, retrieve essential details ofall products from shops database and generate bill himself. This bill can besent to the customer’s mobile through online banking service thus the user canmake quick payment and leave the shop early. The Barcode of the product isscanned by the customer and move to the wish list if they are interested in choiceof item by using the proposed mobile application. In order to develop anAndroid Application that uses a barcode scanner for the purchasing andnavigation of items for store that will be self-checking and automatic paymenttransaction. Here comes the term indoor navigation and barcode scanning. Indoorpositioning is still a challenging problem because satellite-based approach donot work properly inside buildings.                 Barcodes are ubiquitously usedto 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-basedreaders, as a new kind of barcode reader, have recently gained much attention.The interest in camera-based barcode recognition is built on the fact thatnumerous mobile devices are already in use, which provide the capability totake images of a fair quality. This describes the hardware system architecture forimplementing the barcode reading system in mobile phones and its process. Thecamera device and application processors are necessary hardware components forthe system.

The application processors is needed to implement the camerainterface, LCD controllers , DSP for image processing, and application host inCPU for real-time computations. The application processor works for displayingthe menu and preview of the display and computing of code recognition anddecoding in real-time. With these systems, the user can control the position ofthe camera of smart-phone and decides the capture timing of barcode. II.  Related Work  Accurate and reliable real-time indoor positioning on commercial Smart-Phones Author: Gennady Berkovich 1 This paper outlinesthe software navigation engine that was developed by SPIRIT Navigation forindoor positioning on commercial smart-phones.

A distinctive feature of ourapproach is concurrent use of Wi-Fi and BLE modules, together with the floorpremises 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 determinedby GPS/GNSS (Global Navigation Satellite Systems) receiver. The automaticrecovery of tracking in this case allows continuing tracking and increasingavailability of indoor navigation. Positioning results given for differentindoor environments in a shopping mall with accuracy of about 1-2 m.

  Indoor positioning of wheeled devices for Ambient Assisted Living: A case study  Author: Payam Nazemzadeh, Daniele Fontanelli, David Macii,Luigi PalopoliIndoor navigation is awell-known research topic whose relevance has been steadily growing in the lastyears thrust by considerable commercial interests as well as by the need forsupporting and guiding users in large public environments, such as stations,airports or shopping malls. People with motion or cognitive impairments couldperceive large crowded environments as intimidating. In such situations, asmart wheeled walker able to estimate its own position autonomously could beused to guide users safely towards a wanted destination. Two strongrequirements for this kind of applications are: low deployment costs and thecapability to work in large and crowded environments. The position trackingtechnique presented in this paper is based on an Extended Kalman Filter (EKF)and is analysed through simulations in view of minimizing the amount of sensorsand devices in the environment.  Methods and Tools to Construct a Global Indoor Positioning System  Author: Suk-Hoon Jung, Gunwoo Lee, Dongsoo HanA GIPS is a system thatprovides positioning services in most buildings in villages and citiesglobally. An unsupervised learning-based method is adopted to construct radiomaps using fingerprints collected via crowd sourcing and a probabilistic indoorpositioning algorithm is developed.

An experimental GIPS, named KAILOS wasdeveloped integrating the methods and tools. The more volunteers who participate in developing indoor positioningsystems on KAILOS-like systems, the sooner GIPS will be realized.  Interactive android-based indoor parking lot vehicle locator using QR-code  Author: Siti Fatimah Abdul Razak, Choon Lin Liew, Chin Poo Lee, Kian MingLimIn this study, we reporton an android based application development aimed to provide navigationservices to locate parked vehicles in an indoor parking space of shoppingmalls. We utilize the motion sensor, bar code scanner function and camerafunction built in smart-phones. This application is able to show the route fromuser current location to his parked vehicle based on an indoor map of theparking area stored in a database.

  Mitigating the antenna orientation effect on indoor Wi-Fi positioning of mobile phones  Author: Da Su, Zhenhui Situ, Ivan Wang-Hei HoIn this paper, weimplement a practical and convenient indoor positioning system based on thefingerprint method and Kalman filter on Android mobile devices. This paper  discusses the positioning algorithms andaddresses various challenges in practical application, such as the effect ofantenna orientation and signal fluctuation. Specifically, an improved mappingalgorithm based on k-nearest neighbour (K-NN) is introduced to tackle theorientation effect, and an orientation-based fingerprint database isestablished through studying the received signal strength patterns in differentdirections to handle the large fluctuation caused by orientation change.Finally, our experimental result indicates that the proposed IPS can achieve upto 1.2 meters accuracy, is sufficient for various navigation services in indoor environments (e.g.

, shopping malls).  GROPING: Geomagnetism and Crowd sensing Powered Indoor Navigation  Author: Chi Zhang, Kalyan P. Subbu, Jun Luo, Jianxin WuThis paper propose GROPINGas a self-contained indoor navigation system independent of any infrastructuralsupport. It relies on geomagnetic fingerprints that are far more stable thanWi-Fi fingerprints, and it exploits crowd sensing to construct floor maps  than expecting individual venues to supplydigitized maps. Based on our experiments with 20 participants in various floorsof a big shopping mall, GROPING is able to deliver a sufficient accuracy forlocalization and thus provides smooth navigation experience.III.

Existing System People have to search exact product inthe mall with wide range of available brands. Sometimes they will ask for helpin searching product to assistant but may be they also don’t know the exactposition. Customers have to Wait in the billing line to scan the products. In foreign countries there are somemall which use indoor navigation.

To use this system user should go to theparticular LED/LCD screen and search for product location. But on the weekendsor holidays there is too much  rush, so therecan be number of  people waiting in queueto search  their product,   which is little bit time consuming.   Also at the billing section user needto scan for each  product and does thetotal.

There is not a technology for scanning all the product at the same timeso that user can do the shopping in minimum time as possible.    IV.PROPOSED METHODOLOGY  Methodologies to implement the system modules:1.       Pointout product2.

       Scanbarcode 3.       Payment  Point out product:      Now day’small getting bigger and bigger. It very difficult to find the expected productin mall. User search all over mall for expected product.

Propose system providethe better way to search the expected product. User just need to search productin mobile then it will point out the product where user could get the product.  Scan barcode:     When user want to add product in carthe/she scan the barcode of product and select the quantity. Then it willautomatically add the product into the cart.

After selecting required productuser can pay the bill. Payment:     Traditionally,payment is done by carry debit card, credit card or cash. But in propose systemuser can pay the bill from mobile by online. So customer not need to carry anykind of card or cash. V. ALGORITHM Let  X = {x1,x2,x3,……..

,xn}be the set of data points and V = {v1,v2,…….,vc}be the set of centres.1) Randomly select ‘c’ cluster centres.2) Calculate the distance between each datapoint and cluster centres.3) Assign the data point to the clustercentre whose distance from the cluster centre is minimum of all the clustercentres..

4) Recalculate the new cluster centreusing:Where, ‘ci’ represents the number of datapoints in ith cluster.5) Recalculate the distance between each datapoint and new obtained cluster centres.6) If no data point was reassigned thenstop, otherwise repeat from step 3). k-means clustering algorithm:      K-means simpleand easy way to classify a given data set through a certainnumber of clusters (assume k clusters). The main idea is todefine k centres, one for each cluster. These centres should beplaced in a cunning way because of different location causesdifferent result.

So, the better choice is to placethem as much as possible far away from each other. The next stepis to take each point belonging to a given data set and associate itto the nearest centre. When no point is pending, the first step is completedand an early group age is done. At this point we need to re-calculate k newcentroids as barycentre of the clusters resulting from the previous step. Afterwe have these k new centroids, a new binding has to be done between thesame data set points and the nearest new centre. A loop has beengenerated.

As a result of  this loop we  may  notice that the k centreschange their location step by step until no more changes  are doneor  in  other words centres do not move any more.·        User·        QR-Codescanner·        Payment User:User login intoapplication. Search the required product location.

Then scan the QR-Code to addthe product into cart. Then user will pay the bill. QR-Code scanner:QR-Code hold theall information about product like name, amount, etc.  users scan the product QR-Code to add intocart. Product will add to cart by scanning QR-Code.  Payment:As per the productcost, bill will generate by system.

User can pay the bill by credit/ debit cardor online payment. If user pay the bill by credit/ debit card then system willask card details like card no, expiry date, bank name, etc. if user pay thebill online then system will ask bank details.

 Component design :PerformanceRequirement:     Performanceof the functions and every module must be well.The overall performance of the softwarewill enable the users to work efficiently. SafetyRequirement:     Theapplication is designed in modules where errors can be detected and fixedeasily.This makes it easier to install and updatenew functionality if required. SecurityRequirement:    To access the system, person have toregister him/herself in database. Only authorized users can make paymentonline.

 TECHNIQUEUSED 1.       Data Migration. 2.       Interfaces with other systems.

3.       Set up and maintenance of securityrights and access permissions.  Scope:       Propose system effectively used in mallfor notify towards expected product. It also reduce affords of customer andshopper at the time of bill payment. Propose system could be used in shops forbilling purpose. Propose system could be used in canteen for selecting food andbill payment. FEATURESOF THE PROJECT Navigation:      Registration/Login:Customer register himself using his credentials and sets username to use the application for the first time. Then user will LOGIN intoour android app using his username & password.

Then user will input theproduct name and  location  automatically taken by Latitude values of receiver. After that system will show the path towards theproduct. Billing System:       By using navigationsystem user reach to the destination. Then customer has to scan QR-Code of theproduct and add it to cart. Customer have to repeat this process till he endsthe shopping. After that application will create the QR-Code of the totalproduct with the MRP and details.

So, that at the billing time, employee wouldscan the QR-Code and does fast billing process.iv.ConclusionsIn a step aimed at promoting shopping methods and makepeople life easier, we are going to build this mobile application that couldplay an important role in Indian society as a whole. The usage of Pocket PCmall navigator as a shopping mall navigator, in addition to helping the usersto find shops efficiently and effectively, were able to create awareness inusing smart mobile devices for flexibility in almost every task among theshopping mall. AcknowledgmentReferences1       Gennady Berkovich”Accurate and Reliable Real-Time IndoorPositioning on Commercial Smart-Phones”, IEEE           International Conference on Indoor Positioning and IndoorNavigation,  pp 670-677, Oct 2014. 2        Suk-Hoon Jung,Gunwoo Lee and Dongsoo Han “Methods and Tools to Construct a Global IndoorPositioning System”           IEEETransactions on System, man and Cybernetics system,  pp 2168-2216, Jun 2016. 3       Dasu,  ZhenhuiSitu, Ivan Wang-Hei Ho “Mitigating the Antenna Orientation Effect on IndoorWi-Fi positioning system of           MobilePhones” IEEE 26 th International Symposium On Personal, Indoorand Mobile Radio Communication(PIMRC)           Services,Applications and business, pp 2105-2109, Sep 2015.

4        Ultekin, OguzBayat “Smart Location-Based Mobile Shopping Android Application”,Journal of Computer and           Communications,pp  54-63, Feb 2014. 5        Prof. SeemaVanjire, Unmesh Kanchan, Ganesh Shitole, Pradnyesh Patil , “Location BasedServices on Smart-Phone    through theAndroid Application”, International Journal of Advanced Research inComputer and Communication        EngineeringVol.3, Issue 1, pp 417-421, Jan 2014. 6        P. E. Rybski,S.

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Papanikolopoulos,”Performanceof a distributed system using           sharedcommunications channels”, IEEE Trans. on communication and Automation,Volume 22(5), pp 713-727, Oct 2002. 7       M. Batalin and G.

S. Sukhatme  Coverage, “Exploration and deployment by aibeacons and communication network”,           TelecommunicationSystems Journal, Special Issue on Wireless Sensor Networks, Volume 26(2), pp181-196,  Jan 2004. 8       iBeacon (2014) Online. Available: https://developer.apple.com/ibeacon/Getting-Started-with-iBeacon.

pdf9       An indoor geo-location system for wireless lans, inParallel Processing Workshops, 2003. Proceedings. 2003 International           Conference on, pp 29-34, Oct 2003. 10    Location Fingerprint analyses toward efficient indoorpositioning, in Pervasive Computing and Communications, 2008,           PerCom 2008. Sixth Annual IEEE International Conference, pp 100-109, March2008. 11    Object recognition using a tag.

In 1997 InternationalConference on Image Processing (ICIP 97) 3-Volume Set-Volume 1,           IEEE, IEEE Computer Society Press, pp877-880, Oct 1997.   


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