Akanksha the idea. Smart-Phone application helping you in

Akanksha Ambavade1, Sagar Rathod 2,Prashant More3, Anuja Doke 4Prof. S.V.

Athawale 5(Guide), Computer Department, A.I.S.S.M.S. C.

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

O.E.   Abstract- Bigshopping malls usually provide a directory to their available shops, but thesedirectories are most of the time static and do not provide any interactivityfeatures to the visitors. In this work, we present a mobile shopping mallnavigator. The main reason behind our conceptual idea of our proposed projectis because we feel that when visitors often change their plan to go to othershops instead of the ones in their minds, it can be full of effort especiallyconsidering the crowded levels and location of the navigation material. Theapplication developed is practical and feasible.

Smart-Phones have become very popular thesedays, so we have combined the idea. Smart-Phone application helping you in analienated mall. The idea revolves around our Smart-Phones & the “Wi-Fi” provided by themall. An application that needs real-time, fast, & reliable dataprocessing.

  Technical Keywords –  Indoor navigation, QR-Code  scanner, Wi-Fi router I.     Introduction                ManualShopping is the traditional way of shopping where the customers choose theirdesired product and carry the products along with them. Traditional shopping isa tedious and time consuming job. In traditional shopping, the customer has towait in long queues at the cash counter. This consumes lot of time and energyof both the customer as well as cashier. To overcome these flaws, the customer himselfcan scan the QR-Code using his mobile while making purchase, retrieve essentialdetails of all products from shops database and generate bill himself 11. Thisbill can be sent to the customer’s mobile through online banking service thusthe user can make quick payment and leave the shop early. The QR-Code of theproduct is scanned by the customer and move to the wish list if they areinterested in choice of item by using the proposed mobile application.

In orderto develop an Android Application that uses a QR-Code scanner for thepurchasing and navigation4 of items for store that will be self-checking andautomatic payment transaction1. Here comes the term indoor navigation5 and QR-Codescanning. Indoor positioning is still a challenging problem becausesatellite-based approach does not work properly inside buildings1.                 QR-Codesare ubiquitously used to identify products, goods or deliveries. Devices toread QR-Codes are all around, in the form of pen type readers, laser scanners orLED scanners. Camera-based readers, as a new kind of QR-Code reader, haverecently gained much attention. The interest in camera-based QR-Coderecognition is built on the fact that numerous mobile devices are already inuse, which provide the capability to take images of a fair quality11. Thisdescribes the hardware system architecture for implementing the QR-Code readingsystem in mobile phones and its process.

The camera device and applicationprocessors are necessary hardware components for the system. The applicationprocessors are needed to implement the camera interface, LCD controllers, DSPfor image processing, and application host in CPU for real-time computations.The application processor works for displaying the menu and preview of thedisplay and computing of code recognition and decoding in real-time. With thesesystems, the user can control the position of the camera of Smart-Phone anddecides the capture timing of QR-Code5. II.  Related Work  Accurate and reliable real-time indoor positioning on commercial Smart-Phones Author: Gennady Berkovich This paper outlines the software navigation engine that wasdeveloped by SPIRIT Navigation for indoor positioning on commercial Smart-Phones1.A distinctive feature of our approach is concurrent use of Wi-Fi and BLEmodules, together with the floor premises plan are used for hybrid indoorpositioning in the navigation engine. Indoor navigation software uses suchtechnologies as PDR and map matching.

There is no need to enter initialposition manually where it can be determined by GPS/GNSS (Global NavigationSatellite Systems) receiver. The automatic recovery of tracking in this caseallows continuing tracking and increasing availability of indoor navigation.Positioning results given for different indoor environments in a shopping mallwith 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 PalopoliIndoornavigation is a well-known research topic whose relevance has been steadilygrowing in the last years thrust by considerable commercial interests as wellas by the need for supporting and guiding users in large public environments,such as stations, airports or shopping malls. People with motion or cognitiveimpairments could perceive large crowded environments as intimidating. In suchsituations, a smart wheeled walker able to estimate its own position autonomouslycould be used 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 HanAGIPS is a system that provides positioning services in most buildings invillages and cities globally2. An unsupervised learning-based method isadopted to construct radio maps using fingerprints collected via crowd sourcingand a probabilistic indoor positioning algorithm is developed.

An experimentalGIPS, named KAILOS was developed integrating the methods and tools.  The more volunteers who participate indeveloping indoor positioning systems on KAILOS-like systems, the sooner GIPSwill 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 MingLimInthis study, we report on an android based application development aimed toprovide navigation services to locate parked vehicles in an indoor parkingspace of shopping malls. We utilize the motion sensor, bar code scannerfunction and camera function built in smart-phones. This application is able toshow the route from user current location to his parked vehicle based on anindoor map of the parking area stored in a database.

  Mitigating the antenna orientation effect on indoor Wi-Fi positioning of mobile phones  Author: Da Su, Zhenhui Situ, IvanWang-Hei HoInthis paper, we implement a practical and convenient indoor positioning systembased on the fingerprint method and Kalman filter on Android mobile devices3.This paper discusses the positioning algorithms and addresses variouschallenges in practical application, such as the effect of antenna orientationand signal fluctuation. Specifically, an improved mapping algorithm based onk-nearest neighbour (K-NN) is introduced to tackle the orientation effect, andan orientation-based fingerprint database is established through studying thereceived signal strength patterns in different directions to handle the largefluctuation caused by orientation change. Finally, their experimental resultindicates that the proposed IPS can achieve up to 1.

2 meters accuracy, is sufficientfor 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 WuThispaper proposes GROPING as a self-contained indoor navigation system independentof any infrastructural support. It relies on geomagnetic fingerprints that arefar more stable than Wi-Fi fingerprints, and it exploits crowd sensing toconstruct floor maps than expecting individual venues to supply digitized maps12.Based on their experiments with 20 participants in various floors of a bigshopping mall, GROPING is able to deliver a sufficient accuracy forlocalization and thus provides smooth navigation experience.

III.Existing System In traditional shopping, people have tosearch exact product in the mall with wide range of available brands. Sometimesthey will ask for help in searching product to assistant but may be they alsodon’t know the exact position. On other hand, customers have to wait in thebilling line to scan the products. In foreign countries there are some mallswhich use indoor navigation. To use this system user should go to theparticular LED/LCD screen and search for product location2.

But on theweekends or holidays there is too much rush, so there can be number of peoplewaiting in queue to search their product, which is little bit time consuming.                                         Fig.1. BillingSection                                                              Fig.2. Navigation System Also at the billing section user needto scan each product and does the total. There is no technology to scan theentire products at the same time so that user can do the shopping in minimumtime as possible11.

    IV.PROPOSED METHODOLOGY  Methodologies to implement the system modules:1.       Pointout product2.       ScanQR-Code 3.

       Payment  Point out product:     Now-a-day’s malls are getting bigger and bigger. It is very difficult tofind the expected product in mall. User search all over mall for neededproduct. Propose system provide the better way to search the desired product. Userjust needs to search product in mobile then it will point out the product whereuser will get the product.  Scan QR-Code:     When user wants to add product in carthe/she scan the QR-Code of product and select the quantity. Then it willautomatically add the products into the cart.

After selecting required productsuser can pay the bill. Payment:     Traditionally,payment is done by debit card, credit card or cash. But in propose system usercan pay the bill online. So customers don’t need to carry any kind of card orcash.

 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 thenumber of data points 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-meanssimple and easy way to classify a given data set through acertain number of clusters (assume k clusters).The main idea is to define k centres, one for each cluster.These centres should be placed in a cunning way because ofdifferent location causes different result8. So, the better choice is toplace them as much as possible far away from each other.The next step is to take each point belonging to a givendata set and associate it to the nearest centre. When no point ispending, the first step is completed and an early group age is done. Atthis point we need to re-calculate k new centroids as barycentre of theclusters resulting from the previous step.

After we have these k new centroids,a new binding has to be done between the same data setpoints and the nearest new centre. A loop has been generated8. As aresult of  this loop we  may  notice that the k centres changetheir location step by step until no more changes  are done or in  other words centres do not move any more.Fig.3.

FlowChart VI. MODULES ·        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 holds theall information about product like name, amount, etc.  Users scan the product QR-Code to add it intocart. Product will add to cart by scanning QR-Code.

 Payment:As per the productcost, bill will be generate by system. User can pay the bill by credit/debitcard or online payment. If user pay the bill by credit/debit card then systemwill ask card details like card no, expiry date, bank name, etc. if user paythe bill online then system will ask bank details. Component design:Fig.4. component design Performance Requirement:     Performanceof the functions and every module must be well.     Theoverall performance of the software will enable the users to work efficiently.

 Safety Requirement:     Theapplication is designed in modules where errors can be detected and fixedeasily.     Thismakes it easier to install and update new functionality if required. Security Requirement:    To access the system, person have toregister him/herself in database. Only authorized users can make paymentonline. VII.TECHNIQUE USED 1.       Data Migration.

2.       Interfaces with other systems. 3.

       Set up and maintenance of securityrights and access permissions.  Scope:       Propose system effectively used in mallto notify the expected product. It also reduces efforts of customer and shopperat the time of bill payment. Propose system can be used in shops for billing purpose.Propose system can be used in canteen for selecting food and bill payment. VIII.

FEATURES OF THE PROJECT Navigation:      Registration/Login:Customer register himself using his credentials and sets username &Password to use the application for the first time. Then user will LOGIN in ourandroid app using his username & password. Then user will input the productname and location automatically taken by Latitude & Longitude values ofreceiver.

After that system will show the path towards the product. 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 has to repeat this process till he endsthe shopping11. After that application will create the QR-Code of the totalproduct with the MRP and details. So, that at the billing time, employee willscan the QR-Code and does fast billing process.        Fig.5.

Manual billingsystem v/s self billing system  IX. ConclusionsIn a step aimed for promoting shopping methods andmake people life easier, we are going to build this mobile application thatwill play an important role in Indian society. The usage of Pocket PC mallnavigator as a shopping mall navigator, in addition to helping the users tofind shops efficiently and effectively, were able to create awareness in usingsmart mobile devices for flexibility in almost every task among the shoppingmall.  References1       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 Indoor PositioningSystem”           IEEE Transactions onSystem, man and Cybernetics system,  pp2168-2216, 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.

A. Stoeter, M. Gini, D. F. Hougen, and N. 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       https://en.wikipedia.org/wiki/K-means_algorithm9       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 1997.12    Chi Zhang, Kalyan P. Subbu, Jun Luo, and Jianxin Wu,Member IEEE, “GROPING: Geomagnetism andCrowd sensing         PoweredIndoor Navigation”, IEEE Transactionson mobile computing, Volume 14, No. 2, pp 387-400, Feb 2015.    

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