Android Based Location Based Shopping Application

Specilization in Project    
Android Based Location Based Shopping Application


Project Title: Location Based Shopping Application


In the paper, a smart location-based mobile shopping application for Android devices is proposed. The Geo-position of the users mobile device is utilized to produce location information in shopping application (SAGO). The flow of the application is that user searches a product, and then SAGO identifies the location and searches the product on the closest electronic local stores. The idea is to get the prices from each local store with in stock information and smartly listed product list. With the proposed smart filtering algorithm, mobile shopping application achieves precise and minimum error based on searching and listing results.

Literature Review:

1)      Auther: Ahmad Jaradat* , Noor Azian Mohamad**, Ahmad Asadullah**, Seyed Ebrahim** *,** Information System Department, International Islamic University Malaysia

In general, marketing is the overall process which holds the value of product or service to customers. In todays environment, consumers are more fragmented than ever before and marketers are looking for alternative and innovative ways to capture people to earn peoples attention and connect with these fragments. As a smart phone user the possibilities of Location Based Marketing (LBM) on smartphones are being extended which make it easier for such services to be delivered. It is a critical for marketers to launch LBM services since it allow them to develop innovative applications and services to provide a better customer experience. According to Mobile Marketing Association [1], Location Based Marketing is defined as any application, service, or campaign that incorporates the use of geographic location to deliver or enhance a marketing message/service. Geographic location data may be obtained via a wide variety of methods and technologies. A consumer can directly provide a Postal Code, Zip Code, or City; or the precise location of the consumer and their device can be automatically determined using services provided by mobile operators or automatic detection of location as determined by the hardware, i.e., GPS-enabled or, Wi-Fi-enabled devices. Marketers can use this geographic location as a means to deliver a more relevant, targeted advertisement and/or a service, to the user. It can generally be observed that people these days tend to use new forms of services rather than the traditional ones. For instance, consumers tend to seek information inside the store from their smartphones not from the salesperson, as they want to have a new experience and enjoyment. Therefore, marketers should consider this when they use mobile marketing. A survey conducted by salesforce marketing found that 63% of consumers who dont use this feature simply dont want to share their location. An additional 35% say they dont want to participate because it decreases battery life. On the other hand, 76% of those who actually use location-sharing say it help them receive more meaningful content, and 73% rate this feature as useful [2]. Generally speaking, there are two types of location based services [3]. The first type sends location-based information to the device after a prior user request which is called Pull-based, whereas their counterpart and second type are Push-based services, which are not triggered by a direct user request. Although Location Based services are more social, more tangible, less disruptive, and more targeted, but there are some issues that need to be considered by both marketers and customers. Therefore, this paper is going to discuss some of these issues in Location based services in depth. I

2)      Auther: Günay Gültekin, Oguz Bayat

As more people have more smart phones, they are more willing to use them for purchasing, searching and other purposes, instead of using a computer. The survey proves that smart phones are used as a reference to get information [1]. In addition, the big companies get benefits from mobile devices and smart phones. PayPal is experiencing an exponential growth in mobile payments and growing from $750M in 2008 to over $4B in 2011, with $20B expected in 2013 [2]. More than 3 million people have paid using the Starbucks Card Mobile application, making Starbucks the nations largest mobile payment network. It presents in 6800 Starbucks and 1000 Target locations [3]. According to all this information, the mobile market becomes an important part of the world trade. Therefore, mobile applications are needed and produced by mobile developers. "Online shopping" is one type of mobile application on smart phones. Furthermore, we are able to see that the web market is losing the peoples focus, on the other side the focus is shifting towards the mobile market. Moreover, the people have a limited time nowadays because the technology has been improving and tons of work must be finished in a specific time; therefore the time becomes important for our daily work. In addition, the people want to decrease time consuming tasks on daily routine works by using the mobile devices.

According to it, market analyst says that the people use their phones more than that in the last two decades. In general, the people are willing to buy the cheapest products. Also, the location of shopping malls is an important factor, too. People prefer to choose closer shopping malls for buying a product even though the products price is high. Furthermore, they prefer to buy the cheapest product in the closest shopping mall. Therefore, the people have to search the location of shopping malls and products which are available at each shopping mall. Consequently, the location information is the key value for mobile applications. The location information is used as a standard feature which is used in the other applications and also, this mobile shopping Android applications coverage is not limited. The application is easily extendable according to the users requirements. The Android application is developed in Android 2.2 version, Application Programming Interface (API) level 8. Besides this information, the system architecture is designed by using Service-Oriented Modeling Framework (SOMF) based on Unified Modeling Language (UML) and object-oriented programming language is used in development process.

Designing with UML is simplifying complexity of the system and helps us to understand the architecture of this paper project. In the development process, the users input data which has been brought before searching products in the nearest electronic super-stores and also the names of local shopping stores are used in a "Smart Filtering algorithm". Moreover, simple filtering and cleaning technics such as Agglomerative Clustering Algorithm, Greedy Search Algorithm, and a Levenshtein distance are used in SAGO mobile shopping application. Although the mobile application is developed for android devices, it will be easily adopted and developed for iOS devices.


Smart Filtering Algorithm -

  • ·         Compute the distance/proximity matrix between the input data points, if necessary.
  • ·         Let each data point be a cluster
  • ·         Repeat Merge the closest two clusters
  • ·         Update the distance/proximity matrix until only one cluster remains.

Basic Agglomerative Hierarchical Clustering Algorithm

  • ·         Remove unrelated products
  • ·         Calculate the representative price of the product
  • ·         Normalize the output of the step 2
  • ·         Measure similarity score between search keyword and the product title (y)
  • ·         Use modified agglomerative clustering algorithm

Customer side Modules

  • ·         Registration
  • ü  Customer first register to the application in order to search the product available as per the location
  • ·         Search for the product
  • ü  Customer can search for the particular product which he/she wants to buy. Once he/she searches it then the shops near to his/her get displayed.
  • ·         Buying
  • ü  The customer can buy the product by going to the shop or he /she can order the product and then payment will be cash on delivery.
  • ·         Get Location
  • ü  It shows the direction of shop and the exact location of the shop on Google map.
  • ·         Product Offers
  • ü  Show the product offers in particular shop         

Software Specifications:

  • ·         Language: Android
  • ·         Database: MySQL / M S SQL 2008
  • ·         Web services: Ksoap / PHP


  • Ø  Pew Research Center (2011) How People Learn About Their Local Community.
  • Ø  PayPal (2013) Mobilising Sales Making Money in the Mobile Commerce Revolution.
  • Ø  Marker, F. and Chan, Y.H. (2009) A Survey on Android vs. Linux.
  • Ø  Bell, M. (2008) Introduction to Service-Oriented Modeling. In: Service-Oriented Modeling: Service Analysis, Design, and Architecture, Wiley & Sons, Hoboken.