An operational design of indoor tracking system in the environment of GSM structure

Transcription

1 American Journal of Computer Science and Engineering 2014; 1(3): Published online October 10, 2014 ( An operational design of indoor tracking system in the environment of GSM structure Md. Ahsan Arif 1, Ariful Hossain Muhammad Amimul Ahsan 2, Md. Kamrul Hasan 3, Chandni Bhattacharya 4 1 Department of CSE, Asian University of Bangladesh, Dhaka, Bangladesh 2 IMS, Stuttgart University, Germany 3 Department of CCE, Patuakhali Science and Technology University, Dhaka, Bangladesh 4 Dept. of Computer Science and Engineering, Dhaka University of Engineering and Technology, Dhaka, Bangladesh address mdahsanarif@yahoo.com (M. A. Arif), aaa.ahsan.ete@aol.co.uk (A. H. M. A. Ahsan), kamrul@pstu.ac.bd (M. K. Hasan), chandniaub@yahoo.com (C. Bhattacharya) To cite this article Md. Ahsan Arif, Ariful Hossain Muhammad Amimul Ahsan, Md. Kamrul Hasan, Chandni Bhattacharya. An Operational Design of Indoor Tracking System in the Environment of GSM Structure. American Journal of Computer Science and Engineering. Vol. 1, No. 3, 2014, pp Abstract This paper presents an operational design of indoor tracking system in the environment of Global system for Mobile (GSM) structure with the method of Simple Point Matching (SPM) and Euclidean Distance Formula. The map of the structure involves of a regular grid of tiles that delivers the basis to identify the object through Finger Print Algorithm in Area Based Approach. The database lies of Radio Frequency Channel Number and its average receive signal strength (-dbm). The measurement of the wireless signal is accompanied from the concerned access point. The result gain from this tracking system can triumph high performance of current prediction on the location mobile unit. The maximum inclusive performance for the indoor positioning system about 88.09% of overall performance recorded. Keywords Simple Point Matching (SM), Euclidian Distance Formula, Finger Print Algorithm and Global system for Mobile (GSM) 1. Introduction Position tracking system as add-ons is becoming significant in the field of wireless technology arena now. Location aware services are established on some form of positioning technique [1]. Positioning systems enable context aware with location awareness. They are also necessary for emergency services such as E-911 for cellular system. In the last few decades, location tracking technology using existing tracking Global System for Mobile (GSM) infrastructure have been suggested for indoor area when the Global Positioning System (GPS) does not work well. The coverage of GSM signal in-building is good enough to make phone calls using the mobile phones. The information contains in the GSM signal which will be used by the mobile phone in order to establish the hand over process, can also be used for positioning purposes [2]. By extracting the important parameters contains through the mobile phones, a tracking program can be build and then can be applied on the indoor tracking applications. In addition to deployment of detecting technologies, increased hardware and software part is available for location-aware applications [3]. The mobile phones have emerged as ubiquitously deployed computing platform capable of downloading and running location-aware applications [3]. For example, if a user of a mobile phone entered large shopping complexes or museum, this indoor positioning application can be helpful in guiding the user so that he or she can locate recent position in the building and also finds the path to the nearest place which they want to go. It is very important for the authority to locate the positioning of the emergency calls been made from so they can lend help as fast as they can to save the people s life [4]. Positioning applications using the GSM signals are also offered by some of the mobile operators. In United Kingdom, Orange, a mobile operator offered a tracking application based on GSM signal to the mobile phones users [5]. The countries which have the root

2 19 Md. Ahsan Arif et al.: An Operational Design of Indoor Tracking System in the Environment of GSM Structure of the mobile networks are originated from the GSM standards. Therefore, it is more economical and universal using the GSM signal in order to cultivate the positioning application. 2. System Design 2.1. Localization Using Different Modules Localization systems for WSNs can be based on the Global Positioning System (GPS), which is a satellite-based localization infrastructure. At any location on earth, a GPS-receiver can be localized using information of at least four GPS satellites. The receiver computes the time-of-flight of the different satellite signals as the difference between its local time and the time the signals were sent and converts the times into distance estimates. Localization information in a WSN can also be acquired by equipping the sensor nodes with infrared sensors. Throughout the environment, anchor nodes equipped with infrared receivers are installed. Any unknown node sends an infrared signal at regular intervals. Depending on the sender's location, a limited number of (different) anchors detect the signal. Based on this knowledge, the sender's position can be roughly estimated. Room-level granularity is the best accuracy currently obtained with this method. Sound signals can also be used for localization purposes in wireless sensor networks. For that, sensor nodes need to be equipped with sound transceivers. In general, ultrasound is used: it is less intrusive since it is not audible for human beings. Localization in sensor networks can be achieved using knowledge about the radio signal behavior and the reception characteristics between two different sensor nodes. The radio signal strength indicator (RSSI) expresses the quality of a radio signal, i.e. its strength at reception time, the higher the RSSI-value, the better the signal reception. The main advantage of using radio-based localization techniques is that no additional hardware for the sensor nodes is required Algorithm The localization systems presented in this report are based on the radio signal strength indicator. Basically two types of algorithm are used for localization: Fingerprint This technique is based on the specific behavior of radio signals in a given environment including reflections, fading and so on. The fingerprinting technique is an anchor-based technique that consists of two separate phases. During the first phase, called the offline phase, a fingerprint database of the environment is constructed. The combination of the RSSI-values measured by the different anchors when the node is at a certain location forms the fingerprint of this location: a series of RSSI-values that are representative for that particular location. During the next phase, called the online phase, real-time localization is performed. An unknown node has to be localized in the deployment area. The unknown node broadcasts a message at regular intervals and the anchors measure the signal strength upon reception of a message. The measured RSSI-values are combined into a RSSI-sample. Afterwards, the best matches between the values in the RSSI-sample and the values stored in the database are searched for. The resulting matches determine the _null position of the unknown node. Its location could either be the value of the closest match or an average of a few best matches. Fig 1. An example grid and corresponding Fingerprint database Proximity Solution Proximity-based localization systems are an anchor-based solution to the localization problem. These systems derive their location data from connectivity information of the network. Knowledge about whether two devices, i.e. an unknown node and an anchor, in the network are within communication range is transformed into an assumption about their mutual distance and location Radio Signal Strength Behavior over Time Performing an analysis of the radio signal strength behavior during a longer period of time, i.e. a few seconds, can provide additional information about the mobility status of a sensor node. Research performed in points out that the variance of the signal strength is much larger when a node is moving than when it is static. Knowledge about a person's mobility pattern does not provide any real location information, but it is useful in combination with other localization algorithms. The technique is combined with fingerprinting. The inference of mobility information as well as location information from the radio signal is done using a Hidden Markov Model (HMM). The algorithm in leads to a median localization error of 1.5 meters and tells whether a node is in motion or not with an accuracy of 87% System Requirements The main function of this part is to establish the connection with the mobile phone and then extract the important parameter, which are the signal strengths and the carrier numbers into computer. The connection between the mobile phone and a notebook is initialized using a FBUS cable for higher data transferring process. Therefore, FBUS protocol is applied for the bidirectional serial communication bus which can achieve bps, 8 data bits with no parity bit and 1 stop bit [6].

3 American Journal of Computer Science and Engineering 2014; 1(3): offline phases. There is another software named NetMonitor used for mobile phone. It will show the parameters of the hidden value on the screen of the phone. The software used in developing the indoor positioning system engaged with own made and others. Network Monitor for Nokia phones and Gnokii is free and can be downloaded from the Internet. Both software support the Nokia 3315 which has been used in this project. The software using Visual Basic was developed personally from the nothing to a set of usable source code for the online and offline phase. Fig 2. The red circle shows the point where the RS232 cable is connected to the Nokia We have used Mobile phone, RS232 to USB converter cable, FBUS cable and personal computer as the component of hardware section Network Monitor for Nokia setup There is a method activating the Network Monitor on the mobile phone Nokia When this procedure is established successfully, the parameters of the hidden value can be shown on the screen of the phone. This Network Monitor menu is hidden menu in most of the Nokia phones where almost all of the network parameters from specific base station are shown. After the activation of Network Monitor on the phone, the screen will changed and display the parameters of the network such as signal receive level values in dbm, cell id, Frequency channel numbers and many more. The Network Monitor menu consists of 241 frames screens. Fig 3. Integration of both hardware and software part. The FBUS cable used in this part has a 4 pin with the battery holder at the one end side to connect to the Nokia The other end side is a serial connection, which is a RS232 port (male) but the connection port (female) is not available in the notebook. Therefore, the RS232 to USB converter is used to connect with the notebook. The note is operating on a window XP professional operating system. Fig 4. Hardware parts for the indoor position system Software Requirements Our experiment has software part as well. In this section, we decided to use Genokii is an open source code program of Nokia phone and it is chosen as an intermediate medium to communicate. Microsoft Visual Basic 6.0 was considered for design front end which is implemented in here as online and Fig 5. Display numbers 3 in Network Monitor The data can be seen through the screen frame of the phone is the carrier number or known as ARFCN Absolute Radio Frequency Channel Numbers [6], [7] Gnokii Software The Gnokii latest version is an open source code of Nokia phone software is chosen as an intermediate medium to communicate between mobile phone and notebook through the Visual Basic 6.0 user interface. Gnokii.exe is developed in Linux environment where it can only be executed in the command prompt. This program is a free software and can redistribute it or modify it under the terms of the GNU General Public License as published by the Free Software Foundation [9] Offline Course Every time the access to the data in the mobile phone Nokia 3315, the command line needs to be executed using the Gnokii application through the Visual Basic Netmonitor. The Netmonitor form will run the Gnokii.exe by prompting the command line C:\gnokii netmonitor 3 in txtcommand1 textbox and C:\gnokii --netmonitor 4 in the txtcommand2 textbox. After the command line has been executed, the data

4 21 Md. Ahsan Arif et al.: An Operational Design of Indoor Tracking System in the Environment of GSM Structure from the mobile phone displayed in Dos application where this Netmonitor form read the data from there and loaded it into the txtoutputs textbox. Every time the Execute button is pressed, the Netmonitor will start to take 40 samples of data. The netmonitor display 3 and 4 will be uploaded in the one txtoutputs textbox. After a successful reading of 40 data, the connection establish through RS232 and USB to RS232 converter Online course The hardware and software setup for this phase is same as for the offline course. The Simple Matching Point and Euclidean distance had been used for the online course for the prediction of the coordinate and rooms where the phone is. Same map and grid system used before this is also applied here. After the Online Measurement is clicked, the Netmonitor will show up. In this Form, the measurement of 20 samples consists of 6 strongest radio frequency channel number and its received signal strength recorded. After the recording process completed, the average of 6 strongest received signal strengths is computed. A vector of 6 radio frequency channel number and it averaged received signal strength would be used for the matching process with the points in the database.txt using a simple method, Simple Matching Points [8] Simple Matching Point This technique is used for area based algorithms. The Wireless Communication Center (WCC) map consists of a regular grid of tiles that described the expected fingerprint for area based approach. The particular tiles then grouped into sets of array which can represent the visual aid of the highlighted each room. Simple point matching is conducted using the Euclidean distance [8] [9]. During the online phase, the recent average 6 measured signal assumed as s j = [s 1, s 2, s 3, s 4, s 5 and s 6 ] at the points where the measurements were conducted is computed. The samples of vectors in the database consists 4 sample receive signal strength of S i = [S 1, S 2, S 3 and S 4 ] and its relevant coordinates x k, y k at the points were the extensive measurement conducted. Each tile in the map represents a small area at WCC building. The recent radio frequency channel number assumed as n j = [n 1, n 2, n 3, n 4, n 5 and n 6 ] and the radio frequency channel number from database assumed as N j = [N 1, N 2, N 3 and N 4 ]. The Simple Matching Points conducted according to some flow of steps. After verify the maximum matching of radio frequency channel number with the database, the Euclidean distance between the matched radio frequency channel number s signal strengths only is carried out. The distance here is not as same as the physical distance, its means the different between the signal strength of the same radio frequency channel [10]. Fig 6. The indoorpositioningonline.frm for online course Euclidean Distance The signal distance between the recent average signal strength, s j and the average signal strength from the database, S i is used to determine which of the points at the database corresponds to the position of mobile station. Euclidean distance used as the common metric to calculate the signal strength between two vectors [10]. Z k = [ (Si - si) 2 ] 1 k 9 (1) Equation 1 shows the common Euclidean distance formula been used extensively in the entire matching process. Z is the Euclidean distance of the differences in the signal strength of both the S i and s i. Due to big attenuation caused by the propagation mechanisms lost and wall, the average receive signal may varies according to the rooms [9]. With using this simple matching points and Euclidean distance, a successful matching process near to its actual coordinate can established. 3. Measurement Setup The measurement setups are followed every time the measurement took place. This setup also applied for both the offline and online course. The Table 3.1 shows the measurement setups parameters. All the measurements are conducted with using the Nokia 3315, which is connected to a

5 American Journal of Computer Science and Engineering 2014; 1(3): notebook running on window XP Home edition, Pentium 4, 1.8GHz processor s speed and 512Mb ram. The connection is prepared using a RS232 cable and RS232 to USB converter cable. The measurements were collected by way of the notebook is placed on an office chair and moved around the building. This will ensure the measurements taken on a constants height. Parameter Orientation Height Number of points Weather Time People activities Line Location of measurements Table 1. The measurement setup Statements Fix in one direction at the points where the measurements are taken Constant height from the floor which is about 1m as illustrated in the figure 3.1 At least 2 points in a room is selected randomly to conduct the measurements Reliable data for this project only considered on a clear weather Time for the measurement is at morning and afternoon People activities on normal working hours on WCC, which is less people and movement CELLCOM mobile operator The points where the measurements is taken is fix for both offline and online course throughout this project To identify an appropriate number of nodes and location inside the WCC, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, building to perform extensive indoor localization measurement. The locations are Simulation lab, Z-lane lab and meeting room of WCC. The samples are taken data from various heights from floor level. Both online and offline course for GUI software is developed using the Visual Basic 6.0. The grid system used in this application is based on tiles. The tiles represent a small area of the building and have the coordinate assigned for that particular tile. This approach is chosen because the system performs for area-based indoor position, not for point-based positioning. The online course uses the database to find the matching with the recent average readings using the Simple Point Matching with Euclidean distance. The indoor positioning developed in this paper is area-based. The area-based position for the room level displayed on the GUI for locating the room where the mobile phone is located in the WCC building. Table 2. Analysis of signal at 52, 43 Actual coordinate Percentage of correct prediction of rooms 52,43 BT) 83.33% 52,38 BT) 66.67% 48,43 BT) 100% 27,14 LP) 100% 22,18 LP) 100% 44,18 BS) 100% 52,14 BS) 16.67% Overall % This is an import element in this paper where the design of a well-analyzed database consists of the signal pattern at the points where the measurement is taken. The measurements took long time and laborious work to come out with optimism analysis for monitoring the radio signal strength received. The determination of average radio signal strength is crucial because in the online course because the prediction of the coordinate based on the matching process conducted with the database. About one week of measurements were taken in the WCC building for the offline course. All the measurements were recorded in the array.txt file. Form the line graph shown in Figure 8 and Figure 9, we can see that there is a typical signal patterns on the following two days. As for the radio frequency channel number 109, roughly the averaged signal can be estimated from the two line graphs about -65 dbm dbm time*8 sec Fig 8. Signal pattern at 52, 43 26/3/2007 1:18:46 PM

6 23 Md. Ahsan Arif et al.: An Operational Design of Indoor Tracking System in the Environment of GSM Structure Fig 9. Signal pattern at 52,43 The result dated 26/3/2007 from Table 3 recorded the highest overall performance for the indoor positioning system about 85.71%. The following day, on 27/3/2007 about 88.09% of overall performance recorded. The results are based on the preliminary measurement conducted for testing the system in online phase. 4. Conclusion This paper presents the indoor localization technique using the GSM signal coverage. Mostly indoor positioning technique use for location based service. It may also valid for vehicle tracking, location tracking etc. Area based positioning method used for locating the mobile unit at the WCC. In this system, total costs are more less than using GPS device. The performance of indoor positioning using GSM signal achieved up to % of correct location prediction with fixed measurement setup. References [1] Hazas, M. Scott, J. and Krumm, J. Location-aware computing comes of age. Computer (2) : [2] Otsason, V et al. Accurate GSM indoor localization. Ubicomp Heidelberg, Berlin. Springer-Verlag Fig 7. Mobile approximately 3 ft high from ground level, simulation lab, WCC. Table 3. Overall performances Frequency channel Average(dBm) Standard deviation All the measurements for the online phase according to earlier measurement setup as for the offline course. The online phase is conducted on the clear day only but the long time period taken to obtain results, the weather changes. Each point, about 6 readings was gathered and the predicted coordinates were recorded. The results above are taken on these following days, which the online course was carried out for almost all the points at the WCC building at the normal working office hour. [3] Hightower, J. and Borriello, G. Location systems for ubiquitous computing. Computer (8) : [4] Kabalan, K.Y. and Mounsef, J.L. Mobile location in GSM using signal strength technique. Electronics, Circuits and Systems, ICECS Proceedings of the th IEEE International Conference : [5] Stuckmann, P. The GSM Evolution : Mobile Packet Data Services. John Wiley & Sons. Chichester [6] Hasliza A Samsuddin. System for Automatic Measurement of Signal Level in GSM 900/1800 Channel with GPS Localization. Master of Electrical Engineering. Universiti Teknologi Malaysia [7] Rappaport, T. S. Wireless Communication Principle and Practice. 2nd edition. Upper Saddle River, NJ. Prentice Hall [8] Elnahrawy, E., Li, X. and Martin R. P. The limits of Localization Using Signal Strength: A Comparative Study. International Conference on Wireless Networks, communications and mobile computing

7 American Journal of Computer Science and Engineering 2014; 1(3): [9] Li, B. Wang, Y. Lee, H.K. Dempster, A. and Rizos, C. Method for yielding a database of location fingerprints in WLAN. Communications, IEE Proceedings (5) : Biography A. H. M. Amimul Ahsan has served as a Lecturer in the Department of Computer Science and Engineering, Asian University of Bangladesh (AUB). In addition, he was an adjunct Lecturer of EEE Department at Atish Dipankar University of Science and Technology (ADUST). Presently he is under study leave. He has completed post-graduation of Master of Engineering in Electrical, Electronics & Telecommunication from the UNIVERSITI TEKNOLOGI MALAYSIA (UTM), Malaysia. His research works in different international journals/conference like IJRRCS, CSJ, IJEST, ICCIT 2010 and University Journals in the field of Computer Science & Engineering, Image Processing and Computer Network has been published. Md. Kamrul Hasan has completed his post graduation from the University of Trento, Italy in Computer Science. Now Mr. Kamrul is an Assistant Professor in Computer and Communication Engineering (CCE) Department, Patuakhali Science and Technology University, Bangladesh. Currently, he is the Chairman (acting) of CCE Department of the Same University. A couple of research papers have been published in the national and international Journal. He has a few conference papers. [10] Kaemarungsi. K. and Krishnamurthy. P. Modeling of indoor positioning systems based on location fingerprinting. INFOCOM Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies : Md. Ahsan Arif has been serving as an Assistant Professor in the Dept. of Computer Science and Engineering (CSE), Asian University of Bangladesh since May He completed his B.Sc. in CSE and M. Sc. in CSE from the University of Madras, India. He also completed Master in Computer Application from Bangladesh. Now he is pursuing his Ph. D. He published more than 15 research article in different reputed journals. Chandni Bhattacharya received her B.Sc. (Engg) degree from Asian University of Bangladesh, Dhaka, Bangladesh in December She is a student of M.Sc. (Engg) in the Dhaka University of Engineering and Technology, Dhaka, Bangladesh and simultaneously working as a Software Developer in Systech Digital Ltd, Uttara, Dhaka, Bangladesh.