Location Based ATM Locator System Using OpenStreetMap Rajib Chandra Das∗, Parijat Prashun Purohit∗, Tauhidul Alam∗ and Mahfuzulhoq Chowdhury∗ ∗Department of Computer Science and Engineering Chittagong University of Engineeering and Technology (CUET) E-mail:
[email protected],
[email protected],
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Abstract—Money
transaction through ATM machine wherever we go has become phenomenon in our day-to-days activities as it is safe to keep a ATM card rather than keeping cash. When we need cash in any unknown area or during any emergency situation, we need to know about nearest ATM booth from where we can avail this opportunity. In addition, a tourist or new comer may face difficulty in having ATM help without this information. Hence, we have proposed a location based ATM locator system (LBALS) using OpenStreetMap, a growing open source digital map where ATM booths and fast tracks are mapped. Database contains detail information about all available ATM booths and fast tracks of different banks. It requires GPS supported android device with application installed on it for the user. Textual information are provided of nearest ATM booths or fast tracks from user’s current position when he requires the information. Some Markers indicate ATM booths or fast tracks on the map. Dijkstra’s algorithm has been applied to show the possible shortest path between user and an ATM booth. Haversine formula is also used to calculate perpendicular distance. Implemented LBALS is tested for some random locations in a specific region of our country. Keywords- Location Based ATM Locator System (LBALS), OpenStreetMap, Location Based Services (LBS), Android, ATM booth
I.
INTRODUCTION
Money transaction wherever we are is a daily need in our life. Now-a-days, with advance of technology, automated teller machine is a nice alternative to cash money to many people. An automated teller machine (ATM) [1] is an electronic telecommunications device that enables the customers of a financial institution to perform financial transactions without the need for a human cashier, clerk or bank teller. In ATM booth a customer is identified by inserting an ATM card containing a chip that contains a unique card number and security information. Customer has to enter a personal identification number (PIN) to authenticate him. An ATM card lets the customer to access bank accounts for making various transactions such as cash withdrawal, checking the balance, and even depositing the money. Moreover, each ATM booth provides 24/7 facility that enables anyone to access it anytime anywhere.
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Our intention is not to define ATM booth but to focus its necessity in our daily life. Banks are nowadays establishing a good number of booths for their customer’s welfare. Even many people have one or more ATM cards which they use when money is needed. With these ATM cards, customer can also deposit money in fast tracks of the bank. However, in the context of Bangladesh, these ATM booths and fast tracks of different banks have not been mapped in our country. So, customer will not be able to know the locations of ATM booths or fast tracks at any unknown place here in this country if customer needs to withdraw cash or deposit money. Sometimes someone may need money in any emergency situation and he has to know the location of ATM booth for money transaction. But ignorance of these booth’s locations may result not having the access of ATM booths or fast tracks for money transaction during any urgent situation. Tourist and new comers of any area in our country may also face the same difficulty for not knowing the locations of ATM booths or fast tracks since they do not know the surroundings of that area. So, sufficient booth establishment is not good enough if there is no way to find out its location when it is required. On the other hand, digital map plays an important role in providing location based services e.g. location, navigation help. As such, it is necessary to have digit map of ATM booths and fast tracks of different banks across the country. Using this digital map information, it is also needed to have today’s location based services provided by smartphones for accessing ATM booths or fast tracks wherever we are or wherever we go in this country. As such, it is necessary to have digit map of ATM booths and fast tracks of different banks across the country. Using this digital map information, it is also needed to have today’s location based services provided by smartphones for accessing ATM booths or fast tracks wherever we are or wherever we go in this country. Considering the above reservations, we have proposed a location based ATM locator system (LBALS). It is an android platform based smartphone application that locates nearest ATM booth with all detailed information using OpenStreetMap (OSM) [2]. Reason of our choice to use OSM is because it is a free and editable map. Anyone can update any location or amenity voluntarily. There is no legal or technical restriction on it whereas Google map has some
restrictions. So, anyone can use OSM in creative and expected way. Hence, we have used OSM to map ATM booths and fast tracks of Chittagong region of Bangladesh. Dijkstra’s algorithm [3] has been used here to show path between user’s current location and desired ATM booth location as it is an efficient algorithm for our purpose and we are considering the non negative distance. The straight line distance from user’s current location and selected ATM booth or fast track is calculated in our system using Haversine formula [4]. Moreover, all the geodata and other information of ATM booths and fast tracks are stored into a central database. The rest of the paper is organized as follows. In Section II, we discuss about previous related work and their limitations in short. Section III includes methodologies of our work. We discuss the system suitable platform, all technical features and performance analysis of our system in Section IV. Then in Section V we focused on the associated challenges that we have faced to implement location based ATM locator system and also the challenges of developing an OpenStreetMap based project in our region. We describe some future implementation at section VI. Finally, in Section VII our conclusion is stated. II.
RELATED WORK
A good number of works have been conducted in location based services domain for addressing various problems. Healthcare location based services has become possible with the development of telecommunication technology. In [5], S. H. Chew et al. described a location based patient tracking system which is based on global positioning technique. However, authors described it is at initial stage of the development. I. Maglogiannis et al. [6] proposed EmerLoc, which is also implemented on GPS technology. Their background describes that this system requires some sensors, a monitoring unit micro computing unit as well as a micro computing unit As it needs sensors and some hardware elements for proper coordination so it is not affordable everywhere. However, our system requires only a smartphone with our application installed on it which is affordable in our country. P. Keikhosrokiani et al. [7] proposed location based mobile cardiac telemedicine system (LMCES). Dijkstra’s algorithm is applied for selecting the shortest path between the nearest healthcare unit and the patient location in order to facilitate the ambulance’s path under critical conditions. But it must be ensured that medical amenities are mapped before it’s implementation. Limitation of the work is that this system will work only for cardiac patients. Recently, a work has been done to map healthcare centers in our country and an android application based system has been proposed to provide the emergency medical assistance [8] which has also used OSM for mapping. Also in [9], [10] two wireless telemedicine systems are described. Here it is focused on addressing different problem instead of healthcare location based services. Oehlman et al. [11] focused on location based services and
different mobile mapping APIs. They also looked at methods about how to render map on mobile using these APIs. They delved deeper into APIs of Google map which has some restrictions for public use. However, they did not describe on any API for open source map e.g. OSM which we have used in our system. Rifat et al. [12] proposed location information system for helping both normal and visually impaired people to search a specific location with text message. Nevertheless, this system can not give audio direction to get to the destination if the user takes wrong path. They also proposed that user gets an advertisement list based on current location via GPS with the assistance of location based advertisement (LBA) [13] using OSM. Rahman et al. [14] proposed an early disaster warning and evacuation system using OSM. It provides automatic visual and audio disaster warning to the user of the system if he is in probable disaster zone. Still it cannot give the complete solution for post disaster recovery and relief distribution help. In the country like Bangladesh, the demand of location based services is increasing with the growth of smartphone technology. However the digital map of the country to support location based applications on smartphones is not rich. So the challenges and opportunities of OSM in various sectors are discussed in [15] though they did not give solution for any problem. In our proposed system, we have addressed the problem of finding ATM booth or fast track locations in our country which was ignored before. We have used OSM in our work motivated by some of previous work. Moreover, we are also part of OSM community of this country. III.
METHODOLOGY
LBALS is an android application as the present age is the age of android in the domain of mobile operating system. Reason of choosing this mobile OS is the burgeoning growth of it. Open Handset Alliance launched Android as a mobile phone operating system [16]. Developers found the platform very flexible and application development for android is quite high. If we look at OS market share, in July 2014 Android OS secured around 84.60% global market share [17]. Figure 1 shows the global market share of android compared to other OS. So, Android platform is very supportive for implementing location based applications.
Fig. 1: Mobile OS market share strategy analytics, July 2014
LBALS is developed on OpenStreetMap as it is user friendly and freely editable compared to other maps. We can describe the OpenStreetMap Foundation (OSMF) as an international organization that supports the OpenStreetMap Projects [2]. It has the motivation to encourage the development as well as expansion of geo-data. There is an agreement between OSM and Bing since 2010. Bing map provides the aerial imagery that can be used for OSM drawing [18]. We can provide a good number of example of OSM projects. Young kiberans created the first digital map of their community [19] using OSM. Before that, Kibera which is a region inside Kenya was a blank spot in the map. Projects of OSM community was also continued in the WikiProject Haiti. Using OSM Haiti earthquake response mapping project created earthquake map resources [20]. In the year 2010, development of OSM was introduced in Bangladesh. Some GPS trackers were given by the OSM Foundation for update task. In Dhaka first OSM project was launched [12]. Later digital mapping project was introduced at Chittagong University of Engineering and Technology (CUET) campus of Chittagong, Bangladesh. A group of students are still involved voluntarily in mapping amenities of different regions of Chittagong since 2011. In [8] the updated medical amenities were mapped in OSM. For our proposed LBALS, the geo-coordinates (longitudes and latitudes) of different ATM booths and fast tracks around Chittagong city were taken via GPS tracker. Then collected geo-coordinates from GPS were imported them into JOSM software. Finally, we have uploaded our GPS traces of ATM booths and tracks on OSM which is shown in Figure 2. This map demonstrates a portion of updated ATM booths at Chittagong city. Inside circular indicator updated amenities are seen.
name of ATM booths, location etc. To calculate the distance between user’s current location and desired nearest ATM booth or fast track, we have used Haversine formula [4]. We assume a spherical Earth with radius R (earth radius = 6,371km), and the locations of the two points in spherical coordinates (longitude and latitude) are long1, lat1 and long2, lat2. The Haversine formula is as follows: Δlat = lat2− lat1 Δlong = long2− long1 a = sin² (Δlat/2) + cos (lat1).cos (lat2).sin² (Δlong/2) c = 2.atan2 (√ a, √ (1−a)) d = R.c
(1) (2) (3) (4) (5)
The above equations provides exact results for calculating the distance between user’s current location and selected ATM booth or fast track. The intermediate Δlat in eqn.1 calculates the difference between latitude of two points and Δlong in eqn2 also calculates the difference in two points longitude. The result found in a is the square of half of the straight-line distance (chord length) between the two points written in eqn3. The result in eqn4. c is the great circle distance expressed in radians. In eqn.5 the great circle distance d will be in the same units as R which is the distance between two places considering as two points e.g. (long1, lat1) and (long2, lat2). For calculating the shortest path from user’s current location and selected ATM booth or fast track, we have employed the Dijkstra’s algorithm [3]. The algorithm considers the nonnegative distances from one place to another. To get these distances, it also takes the advantage of Haversine formula. IV.
DESCRIPTION OF LOCATION BASED ATM LOCATOR SYSTEM
LBALS, an android application which utilizes the OSM, has been tested in various random areas of Chittagong city for finding ATM booths or fast tracks of different banks of the country. The system supported platform, features of ATM locator system, and performance analysis of our system have been discussed below: A. System Supported Platform •
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Fig. 2: A portion of updated OSM of ATM booths at Chittagong city, Bangladesh (the sign inside circles indicate mapped ATM booths on OSM of Chittagong city)
From the system perspective of our ATM locator system, we have also taken the advantage of a central server which contains the details of ATM booths e.g. bank information,
The application is implemented for android platform and it will require minimum Gingerbread version (2.3.3). This application will also run on higher version of android. Initially, internet connection must be available for loading OSM in our application. However, offline map can be used for viewing map in the application later on. To trace the current location of user, cellphone must have GPS.
B. Features of ATM Locator System •
Whenever our ATM locator system is installed on an android mobile, user will be asked to choose an option between fast track and ATM booth which is
illustrated in Figure 3a. For both options, our system will provide a list of all available names of ATM booths or fast tracks of different banks retrieved from database and this is shown in Figure 3b.
(a) Option for ATM locator
the name of the new ATM booth or fast track that user gets and latitude and longitude fields will automatically filled up according to the user’s current location. Then the new ATM booth or fast track will be dynamically updated on the map. Although there is no API for this features for adding the marker of ATM booth or fast track on OSM, but we have incorporated this feature in our application using our written API which will update OSM dynamically.
(b) List of nearby ATM booths
Fig. 3: Options and list of nearby ATM booths or fast tracks in the application •
•
•
•
By selecting any name of the bank from the list of Figure 3b, our user will get two options to choose. One option is to see details information about the bank services e.g. category of the bank, helpline number and web address. Other option is to view the ATM booths or fast tracks on the map. There are also available options to show the shortest path as well to see the calculated straight line distance. In map option, the user will be provided the markers of ATM booths or fast tracks. Markers are responsive. If a marker is touched for a while the system will give the name of the bank along with straight line distance which is calculated using Haversine formula as shown in Figure 4a. We have also employed Dijkstra’s algorithm to provide the shortest path using existing roads between user current location and desired location of ATM as shown in Figure 4b where the green marker represents the user current location and red marker for desired ATM location. The user just select the marker in which ATM booths or fast track he wants to go then an automatic shortest path will be shown. User will have to press the marker until shortest path appears. Since we have mapped ATM booths or fast tracks in a particular region of the country but there are many unmapped ATM booths or fast tracks across the country. So our application has additional feature stating “update ATM option” in main menu with a view to update them dynamically. If user gets new ATM booth or fast track and he wants to contribute voluntarily to update the mapping of it then our application will ask the user to put only
a) Calculated distance
(b) Calculated shortest path
Fig. 4: Distance and shortest path calculation between user’s current location and desired ATM booth C. Performance Analysis We have also analyzed the accurateness of our system in Chittagong city where all types of ATM booths and fast tracks are available. To check the system accuracy, we have taken the experimental value in random locations of Chittagong metropolitan area. In every experimental data collection process, we have selected a desired ATM booth or fast track then we determine the distance and path using existing road. As mentioned before, we have used Haversine formula to calculate the perpendicular distance and Dijkstra’s algorithm for shortest path calculation. Then we calculate the accuracy of both methods and finally we determine the least accuracy of the system. Performance of our experimental result analysis is shown in Table I that shows accuracy of our ATM locator system that has been taken for 345 random cases. For obvious reason we have found that the system accuracy is inversely proportional to the distance of ATM booth or fast track. So, this is the limitation of our work that the system accuracy decreases with the increase of the distance of ATM booth or fast track from user’s current location.
TABLE 1: ATM LOCATOR’S ACCURACY No of cases
100 80 60 40 25 20 10 10
Distance Between User and ATM (km) 0.3 0.5 1.0 1.5 2.0 5.0 6.0 10.0 V.
Haversine Formulas Accuracy
Dijkstra’s Algorithm Accuracy
Least Accuracy
97 76 57 37 21 16 8 7
96 73 54 33 19 15 7 5
96.00% 91.30% 90.00% 82.50% 76.00% 75.00% 70.00% 50.00%
CHALLENGES
Location based ATM locator system (LBALS) is an effective android application during any emergency money withdrawal and deposit. User of the application can choose the closest ATM booth or fast track from his current location. During the mapping and our application development, we have faced several challenges to overcome. These challenges are described below: • Developers are implementing various location based services using different platform and online map. But the fact is that these services are not well advertised. Telecom operators of our country are not still interested to provide these services to their customer. • There are very few GPS devices available in Bangladesh to update the OSM. And it is a great challenge we have faced in collecting the waypoints via GPS device. • As OSM is a free editable map there may have some repetition of update for the same amenity. Moreover if is not done in an efficient way, actual location and updated location in map may differ. Update task must be done in a structured way. • Although 3G service in Bangladesh is available right now but still it is pretty slow and hence high speed internet is one of the requirement in any development of OSM even today in our country. Many users have low speed connection that is not enough to edit OSM or view it quickly. The application of the system also lacks the required internet bandwidth for smooth viewing of the map on the application. • Undoubtedly, ATM booths are lot in number now a days in our country. Sometimes a user finds his desired booth but gets the teller machine out of money. Sometimes technical problem in teller machine is also seen. • People are not familiar with OSM still now. Whenever they hear about any online map they are confined to think about other maps e.g. Google
•
VI.
Map. Moreover they have no idea about the merits of OSM over other. So, familiarization of OSM is a big challenge as well. Number of motivated and skilled volunteers to develop OSM are not still adequate in Bangladesh since we are actually apprentice mapper to update the map. This is also responsible for the shortcomings of OSM development in our country. POSSIBLE FUTURE IMPLEMENTATION DIRECTIONS
In future, the development of OSM can be applied in different purposes with a view to address different problems of our country. The successful implementation of this location based service oriented system can boost the progress of OSM up and make the people of our country habituated to use location based application to have emergency ATM help. Furthermore, the possible future implementation directions of OSM are listed in the following: A.
Help in Public Heath Sector: OSM can be utilized to develop a map showing hospitals, diagnostic centers, and pharmacies in an area. This map will help the people to get easy access of existing health care system. Apart from this, OSM can play an important role to locate the arsenic affected areas and tube-wells on the map. Governmental vaccination campaign can coordinated through OSM by distributing different teams in different areas which will be shown on the map.
B. Intregrated location based services: The police office and fire station are two important amenities in our country. They can be considered in future for mapping and all the locations based services can be integrated in one application using OSM. C. Transportation Help and Traffic Jam Locator: Rickshaw is a major transport for average people in Bangladesh but it has been banned in some major streets in Dhaka. This type of traffic information may change rapidly under the direction of the traffic control authority. A road OSM showing restrictions on rickshaw as well as other information like which streets are one way would help the city dwellers. Traffic jam is a common phenomena in our country and OSM hereby can be used to develop such an integrated system to avoid the path as well as showing alternative one. Big data concept can be used here to determine the area of traffic jam. VII. CONCLUSION Our proposed LBALS is an android based smart phone application developed on OpenStreetMap (OSM) and specifically in a specific region of Bangladesh. The mapping of other regions can be carried on and it will become more effective then to use our application. Our proposed ATM locator provides the visualization of locations on the map of the application to users, gives the distance of nearest ATM
booth or fast track and user’s current location using Haversine formula and the shortest path between them using Dijsktra’s algorithm. This application will be very helpful to have ATM booths or fast tracks information during any emergency situations. But the details information of ATM booths and fast tracks of all the banks is not available around Bangladesh on OSM which is the main constraint of our work. Moreover our accuracy decreases when the distance increases. The limitation will be removed hopefully in future. Moreover it must be a cross platform application where any operating system can be suitable.
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