Large Scale Indoor Location System based on Wireless Sensor Networks for Ubiquitous Computing

Transcription

1 Large Scale Indoor Location System based on Wireless Sensor Networks for Ubiquitous Computing Taeyoung Kim, Sora Jin, Wooyong Lee, Wonhee Yee, PyeongSoo Mah 2, Seung-Min Park 2 and Doo-seop Eom Department of Electronics and Computer Engineering, Korea University, 5-ga, Anam-dong, Sungbuk-gu, Seoul, Korea tykim@final.korea.ac.kr 2 Embedded Software Division Electronics and Telecommunications Research Institute 6 Gajeong, Yuseong, Daejeon, Korea Abstract The task of formulating an efficient system for determining the location of an object, results in the creation of a wide number of applications and services. For this reason, most wireless sensor network applications assume the availability of sensor location information. In this paper, an indoor localization scheme, which is based on synchronized sensor nodes, is proposed. It is extremely efficient in terms of power consumption and location update rate. Furthermore, it resolves the scalability problem usually found in most conventional indoor location systems in large scale indoor environments. The performance of the proposed scheme is evaluated through experimental implementation. The results demonstrate that the proposed scheme is a feasible location system for a large scale indoor environment. Keywords: Indoor Location, Ubiquitous Computing, Wireless Sensor Networks, Power Efficiency, Synchronization, Context-aware Computing, Introduction Wireless sensor networks consist of distributed nodes with restricted computation, communications and power resources. The applications of wireless sensor networks include military surveillance, environmental observation, surgical operations, tracking patients and doctors in a hospital. A large number of wireless sensor network applications assume the availability of sensor location information. This is especially true in wireless sensor networks, it is essential to be able to identify the location of various objects. The most well-known location system is the Global Positioning System (GPS) []. This system uses 24 satellites to enable three-dimensional positioning services. However, the GPS is insufficient for indoor location systems, because it is difficult

2 for satellite signals to penetrate buildings and provide high precision location information. Furthermore, nodes equipped with GPS are not generally accepted in wireless sensor networks, due to unattractive scale, cost and power consumption attributes. Recently, there has been growing research efforts focused on indoor location systems. Cricket [2] is a system that can provide location-dependent applications using both RF and ultrasonic signals. The RADAR [] system attempts to take advantage of the existing RF data networks formed using IEEE 802. access points. The Active Bat [4] system is a cell-based location system in which objects are each attached with tags. The Active Bat consists of a collection of wireless transmitters, a matrix of receiver elements, and a central RF base station. The Bat refers to wireless transmitters that can be carried by tagged objects. This system measures the time of flight of the ultrasonic pulses emitted from a bat, to receivers installed in known and fixed positions. It uses the time difference of the arrival signal from each bat for localization. The RF base station controls the bats by means of broadcast messages. When receiving the messages, a bat transmits an ultrasonic pulse. A receiver that receives the RF signal from the base stations determines the time interval of the RF signal and ultrasonic pulse. However, the Active Bat suffers from the privacy problem because the location of objects cannot be determined by the Bat, and is carried by the user. That is, an infrastructure consisting of receivers and central RF base station monitors the location of user. In addition, receivers should always be activated in determining the location of a user, and thus the Active Bat consumes excess energy. In the case of the Cricket, in order to resolve the privacy problem, it does not rely on centralized management or control, and does not have explicit coordination. In order to obtain location information, a listener is attached to every object. Similar to the Active Bat, the Cricket uses a combination of RF and ultrasonic signals for measuring distance. Cricket uses the time difference of arrival (TDoA) using both RF and ultrasonic signals. A beacon transmits an RF signal and an ultrasonic pulse simultaneously. When the listener receives the RF signal, the ultrasonic sensor of the listener is turned on and waits for the ultrasonic signal. When receiving the ultrasonic pulse from a beacon, the listener measures the time interval between RF and ultrasonic signals. Cricket consumes excess energy in determining the location of the object. This is because the RF signal transmission always accompanies the ultrasonic signal during transmission, and all beacons consume energy when attempting to transmit RF and ultrasonic signals, although few are necessary in determining the location of the receiver. In these indoor location systems interest is focused on using both RF and ultrasonic signals. These systems provide various advantages. Firstly, they can be easily implemented at low cost using wireless sensor networks. Secondly, their location measurement error is relatively low, compared to indoor location systems only using the RF signal. However, in order to deploy such location systems in large indoor environments, many more beacons (the associated functionality is very similar to that of GPS satellites) are required, compared to indoor location systems only using RF signals. It is expected that this major disadvantage of indoor location systems using both RF and ultrasonic signal can be overcome, since wireless sensor networks will be deployed in most intelligent buildings in the near future and the cost of sensor

3 nodes consisting of wireless sensor networks is much lower than that of IEEE 802. wireless LAN or UWB nodes. Therefore, an indoor localization scheme, which is based on synchronized sensor nodes, is proposed. In this scheme, in order to activate a minimum number of beacons for determining the location of user, synchronization of sensor nodes is performed in a distributed manner, this is in contrast to the Active Bat. Therefore, as explained in subsequent sections, the proposed scheme can resolve the privacy problem inherent in the Active Bat and the excess power consumption problem of inherent in both Cricket and the Active Bat. The proposed scheme consists of two algorithms, an Auto-Beaconing algorithm for distributed time synchronization, and a Zone management algorithm for efficient power management. In general, it is assumed that receiver or beacon nodes operate with a battery in a large scale indoor location system, and thus indoor location systems must be reengineered with regard to power efficiency and scalability. The subsequent sections of this paper are structured as follows. In Section 2, a brief description of the proposed scheme is provided and the algorithms for time synchronization, zone management and power efficient measurement are described. The implementation of the location system is discussed and the evaluation results are presented in Section. Section 4 presents the conclusions. 2 Proposed Scheme In this section, the system architecture and algorithms of the proposed large scale indoor location system are presented. The architecture of the system is first described, then the Auto-Beaconing algorithm and the Zone management algorithm, are presented, for distributed time synchronization between beacons and receiver, and efficient power management, respectively. 2. System Architecture The proposed system is composed of four components; beacons mounted on the ceiling, a receiver attached to an object, a location sink for collecting location data and a context-aware application server, for monitoring the location of an object. The system architecture is presented in Fig.. Fig.. System Architecture

4 Receiver: The node attached to an object consists of essential functions for measuring the location and transmitting the data to the location sink. After achieving time synchronization, the receiver schedules the signal transmissions for distance measurements by using the Auto-Beaconing algorithm. Beacons: The nodes mounted on fixed sites of the ceilings with a known location containing functions which transmit the ultrasonic pulse following the Auto- Beaconing process controlled by the receiver, and transmit measurement data received from the receiver to the location sink when it is permitted for the contextaware server to monitor the location of an object. It is important to note that the receiver can retrieve its location independently using the signals from the beacons, similar to the method used in Cricket. That is, the proposed system supports both the Active Bat and Cricket mode operation. Location Sink and Context-Aware Application Server: The location sink connected to the context-aware application server with a RS22C or USB interface collects measurement data through the beacons, using ad hoc routing. The context-aware application server analyzes measurement data and determines the location of object using triangulation, displaying this result on the monitor. Figure 2 depicts the state transition diagram of the system. Beacons maintain minimal power consumption in power saving mode. For working in a large scale indoor environment, a zone is defined as a spatial division with a regular square shape. There are four beacons mounted on the corner of zone. When a receiver, which is attached to an object, moves into the zone, it forces the beacons to enter the zone management state. In the zone management algorithm, the receiver retrieves its zone, the beacons of the zone wait for time synchronization. Time synchronization is performed by sharing clock information of the receiver and the selected beacons. Fig. 2. System State Transition Diagram Using both ultrasonic and RF signals, distance measurements between the receiver and the selected beacons are performed using the proposed Auto-Beaconing algorithm

5 in the auto-beaconing measurement state. In the proposed scheme, only four selective beacons in the vicinity of the current location of the receiver are enabled, this significantly reduces system power consumption. Each Beacon node has two IDs, a Unique ID (uid) and Numbered ID (nid). An uid is assigned to each beacon for identifying beacons. A nid is also assigned to each beacon for calculation of the 4-modular decomposition numbers (from 0 to ). (See Fig..) The system requires a nid for Auto-Beaconing and collision avoidance in a large scale wireless sensor network. Fig.. Generation of nid and scheduling for measuring distance in a zone The receiver measures the arrival time difference of RF and ultrasonic signals for each beacon-to-receiver pair to calculate the distance between them. As presented in Fig., measuring order is determined by the nid of beacon. In this way, once the system determines the zone of receiver, no beacon signal collision problem exists, unlike Cricket. The receiver can transmits the measured data to the location sink or determines its location by itself using the measured data. The location sink relays the measured data to the context-aware application server. 2.2 Auto-Beaconing (A-B) Algorithm In this paper, the Auto-Beaconing algorithm is proposed, in order to achieve time synchronization, time slot assignment, beacon signal scheduling and zone selection for power efficient and rapid location update in indoor environments. Time synchronization is performed by adjusting the internal clock offset of the receiver and beacons. The receiver periodically transmits the time synchronization message. The beacons in the vicinity of the receivers receive the message. The zone of the receiver can be determined by exchanging information between the receiver and the beacons receiving the message. The zone selection process is described in more detail in Section 2.. The time synchronization message contains time slot size information. A time slot is defined as follows: Tslot-n = Tus-detect + Tredundancy () n : nid, n = {, 2,,0}

6 As presented in Eq., a time slot is further divided into two time periods: During T us-detect period, the ultrasonic signal transmitted by one of the selected beacons in the zone arrive at the receiver. The selected beacon transmits an ultrasonic signal at the beginning of its assigned time slot, and time slot assignment is automatically performed using the nid of the beacon. In the Zone management algorithm, the zone of the receiver is determined in a way that only four beacons having different nids are selected. Therefore the four beacons in the zone have a unique nid and transmit ultrasonic signals without collision. The T redundancy period is the guard time for avoiding interference with other slots. Figure 4 illustrates the Auto-Beaconing process of the system. When receiving the time synchronization message, four beacons in the zone reset their timer for achieving time synchronization and determine their time slot start time using the time slot size information in the time synchronization message and their nid. Since the ultrasonic signals are transmitted at the start time of each time slot must arrive until the corresponding time slot ends, the maximum distance between the receiver and beacon pair determines the time slot size. 4 RT slot = T slot n n= Fig. 4. Auto-Beaconing Process The beacons can orderly transmit ultrasonic signals to the receiver without RF signal transmission and collision of ultrasonic signal, because time synchronization is already achieved between the receiver and the four beacons in the zone. In order to determine the location of the object using the standard technique of trilaterlation, at a minimum, three beacon-to-receiver distances are required. Thus three time slots and a fault tolerance time slots are assigned in this system. The ultrasonic sensor timer of the receiver is initialized each time the time slots begin and is stopped as soon as the receiver receives the ultrasonic signal from the corresponding beacon. After the receiver iterates this measuring process four times, its location can be determined. That A-B algorithm is presented in Fig. 5.

7 Receiver Beacons Time Synchronization Ultrasound Flying Time SLOT- SLOT-2 START Ultrasonic Sensor Timer Ultrasonic Signal Transmission STOP Ultrasonic Sensor Timer START Ultrasonic Sensor Timer Ultrasonic Signal Transmission SLOT- ~ SLOT-4 in a cycle STOP Ultrasonic Sensor Timer Complete of Auto-Beaconing Fig. 5. Auto-Beaconing Algorithm The location update cycle of the proposed system, follows; 4 T A B = Tslot n + T n= sync TA B, can be determined as where T denotes the period where the time synchronization message is sync transmitted by the receiver. This period consists of four time slots for ultrasonic signal transmission and a synchronization time slot for time synchronization message transmission. Next the location update performance of the proposed system is roughly compared to that of Cricket. Two location algorithms are illustrated in Fig. 6. In Cricket, beacons contend each other to transmit an ultrasonic signal. In order to acquire the right to transmit ultrasonic signals, beacons first transmit a RF message, which is denoted as RF. Then the beacon successfully transmitting a head RF message can head transmit an ultrasonic signal. Other beacons receiving RF message wait until head ultrasonic signal transmission is completed. After completion of ultrasonic signal transmission, the beacon transmits a RF message to indicate completion of tail ultrasonic signal transmission. This beacon scheduling algorithm of Cricket is similar to RTS-CTS mechanism of IEEE 802. wireless LAN. The location update cycle of Cricket, T Cricket, can be expressed as follows; (2) 4 T Cricket = ( Trf _ head + Tus + Trf _ tail ) () n= where T rf _, head T and us T rf _ denote RF message transmission time, ultrasonic tail head signal transmission time and RF message transmission time, respectively. It is tail important to note that the difference between T and T us can be ignored because slot n

8 the distance between a receiver and beacon pair may be less than meters in normal indoor environments. In addition, the difference between T sync and T rf_tail can be ignored because the time synchronization and RF messages can be transmitted tail without contention. However, T rf _ can be much larger than others because head beacons of Cricket transmit a RF message using the CSMA protocol. head From Eqs. 2 and, the location update cycle difference of two systems can be determined as follows; T A B TCricket 4 Trf _ head + T rf _ tail (4) This demonstrated that the proposed Auto-Beaconing location algorithm is considerably faster than the Cricket location algorithm. The main reason of this result arises from the fact that the Auto-Beaconing location algorithm permits beacons to transmit ultrasonic signals successfully without random access. This feature of the system guarantees a constant location update rate, / TA. However, Cricket cannot B guarantee a constant location update rate due to usage of random access beacon scheduling, which also results in location error, particularly when tracking fast moving objects. This is because in order to obtain the accurate location of an object, the distances between the receiver and four beacons should be measured prior to the object moving to another point. In Cricket, due to its random access for beaconing, the majority of the time, this requirement is not satisfied when tracking fast moving objects. 4 T A B = Tn slot + T n= sync T Cricket = 4 n= ( T rf _ head + Tus + Trf _ tail ) Fig. 6. Comparison of Location Algorithms 2. Zone Management Algorithm In a large scale indoor environment, the service area of the proposed location system should be divided into zones, due to the limitations of ultrasonic transmission range, as presented in Fig. 7. The zone is defined as a sector having a beacon on every corner of the square. These beacons are usually attached to the ceiling. It is important to note

9 that beacons of zones are deployed in a manner where four beacons of a zone have one of four nids but the nids do not overlap. In determining zones in such a manner, ultrasonic signal transmission can not only be scheduled without collision, but also transmits RF messages for selecting the zone of the receiver with low collision probability, using the nid of the beacon. Although the zones in Fig. 7 have a square shape, all zone shapes are allowed, as long as beacons of zones obey the nid assignment rule. In order to determine the location of the receiver in a large scale indoor environment, it is necessary to extend the Auto-Beaconing algorithm for selecting four beacons in the vicinity of the receiver before distance measurement. The zone management algorithm is therefore proposed for this purpose. 2 4 Beacon Unique ID : 2 0 Numbered ID : Zone Beacon Unique ID : 2 0 Numbered ID : Zone-0 2 Receiver Receiver Activation Node Deactivation Node Fig. 7. Concept of Zone Management Algorithm Figure 7 illustrates a situation where the receiver attached to an object moves from zone-0 to zone-. Four beacons in the zone corresponding to the current location of the receiver take part in measuring the distance. The other beacons maintain a sleep state for power saving. Therefore, the zone management algorithm permits great power saving, unlike the traditional location system. The zone management algorithm is presented in Fig. 8. Fig. 8. Zone Management Algorithm In the zone management algorithm, the receiver first broadcasts the time synchronization message periodically, similar to the Auto-Beaconing algorithm. As

10 soon as beacons receive the message, they wake up and synchronize with the receiver to receive ultrasonic signals from the receiver. The beacons receiving the ultrasonic signal calculate the distance to the receiver. If the distance is less than the threshold value FZV(Fixed Zone Value), the beacon transmits a joining request message containing its uid and nid to the receiver for joining the zone. However, if the distance is greater than FZV, the beacon assumes that it is out of the zone and thus abandons the zone selection process. The scheduling of joining request message is performed using the nid of the beacon. In Fig. 7 it demonstrated that if the receiver is located in the middle of a zone, only four beacons having different nid can transmit the joining request message so that there is no collision of joining messages. However, if the receiver is located near the boundary of zones, greater than four beacons can transmit the joining request message since FZV is set to a value somewhat larger value than the maximum distance between the receiver and beacons in a zone, as explained in subsequent sections. Even in this case, only two beacons can have same nid and thus their joining request messages collide. However, it is easy to avoid collision in a situation where only two beacons compete for accessing the transmission medium. In this way, the receiver receives several joining request messages from the beacons receiving the ultrasonic signal. In using the IDs in the joining request messages, using the majority voting rule and zone mapping table, the receiver can determine its zone. The acknowledge message which contains the list of beacons consisting of the zone, is then broadcast. After the zone joining process is completed, in each time slot assigned according to nid, the distance between the receiver and corresponding beacon is measured, like the Auto-Beaconing algorithm. Fig. 9. Seamless Handoff by the Superposition Area As mentioned prior, FZV is defined for determining the specific zone in a large scale indoor environment. FZV is somewhat larger than the maximum distance between the receiver and a beacon in a zone, as presented in Fig. 9. Due to FZV definition, the superposition zone can be created for providing seamless handoff between two zones. Figure 9 illustrates the creation of superposition zone in a multizone environment. When an object is moving into another zone, it can transmit the time synchronization message in the superposition zone, and thus the receiver receives more than four joining request messages. In assuming the receiver crosses the center of the superposition zone from zone-0 to zone-, it can receive 6 joining

11 request messages from 6 beacons consisting of two zones. Then, the receiver can select one of two zones, using a majority voting rule. It is important to note that if the ultrasonic transmission range is roughly equal to FZV, two zones can determine the location of receiver successively, so that seamless handoff of the receiver can be achieved. Performance Evaluation. Experimental Environment Figure 0 presents the test-bed used to perform location measurement experiments for performance evaluation. The test-bed, consists of 6 zones having 2 beacons. The area of a zone is 50 cm by 50 cm and all zones have same area size. A zone is further divided into 25 grids, having area of 0 cm by 0 cm. At corners of zones, beacons are attached to the top of plastic bars having m height (black boxes in Fig. 0). In addition, there is a receiver attached to a radio control car in the test-bed. Fig. 0. Test-bed for Location Measurement Figure presents the hardware components of the system such as main module, ultrasonic sensor node and I/O interface module. The receivers and beacons are composed of a main module and an ultrasonic sensor module, and a location sink is composed of a main module and interface module. An Atmel ATMEGA28L MCU with 28 KB Program Memory and Chipcon CC2420 RF transceiver for the main module is used. Two.5 Volts AA batteries are used to supply power to the main module and the ultrasonic sensor module. The location sink is connected to computer or PDA using the USB or RS22C interface.

12 (a) (b) (c) Fig.. Sensor Nodes : (a) Main Module (b) Ultrasonic Sensor Module mounted on Main Module (c) Location Sink: I/O Interface Module attached to Main Module.2 Experimental Results In this section, the system performance is evaluated through the experiments. Firstly, iterative distance measurement tests have been performed. Next, the method of distance error providing impact on the location accuracy of the proposed system is investigated..2. Distance Error Table presents the results of measuring distance between a beacon and receiver facing each other. The real distances between two nodes are set to 50 cm and 00 cm. For each case, the distance between two nodes has been measured 000 times. Table. Accuracy of Distance Measurement actual distance measurement(cm) mean (cm) variance standard Although the proposed system uses relatively a low speed 8 MHz system clock and low precision oscillator, a very reliable distance measurement result by the Auto- Beaconing algorithm based on time synchronization can be obtained. The experiments are performed in a normal indoor environment. It is well known that the velocity of the sound wave is changed depending on temperature and humidity. In order to compensate the effect of temperate on the velocity of ultrasonic signal, Eq. 5 was used. V[ m / s] t = (5)

13 where t is the room temperature. From Eq. 5, it can be deduced that temperature greatly changes velocity of ultrasonic signal, so an on-board temperature sensor was used in Eq Location Error Location error measurement experiments were performed using the test-bed presented in Fig. 0. In the experiments, the location of receiver has been measured, while placing the receiver at various positions in a zone. The measurement results demonstrate that the average location error is approximately.005cm, as presented in Table 2. Table 2. Experimental Location Error location of receiver average location center of zone border of zone.595 average.005 The tendency that location error was found to become larger in the boundary of the zone, however, depending on the location of receiver, the distance error is not changed. It is assumed that the cause of this problem comes from the trilaterlation technique using the Newton-Raphson method since the distance error does not depend on the location of the receiver. The distance error is intentionally introduced when using the trilaterlation technique, and the location error for the receiver is compared on the center of the zone and on the border of the zone, as presented in Fig.. Beacon-2 Beacon- Beacon-2 Beacon- Beacon- Beacon- Auto-Beaconing Receiver Receiver (a) (b) Fig.. Location Error: (a) on the Center of Zone (b) on the Border of Zone In order to conduct the stable performance test of the context-aware application, the iterative tests with error measurement were conducted. Table and Table 4 present the location error when ±0.6 and ±.0 distance error is intentionally introduced for the two cases.

14 distance Table. The location error on the center of zone beacons with distance error beacons with distance error location Distance +0.6,2, 0-0.6,2, 0, 0.52,.7,2 0.52,2.7 2, 0.7 2, ,2, 0 -.0,2, 0, 0.86,.7,2 0.86,2.7 2, 0.7 2, distance beacons with distance error Table 4. The location error on the border of zone beacons with distance error location location distance +0.6,2, ,2, 0., 0.88,.9,2 0.87,2.46 2,.2 2, ,2, ,2, 0.52,.47,.,2 2, , 2 2, location As presented in the tables, although same distance measurement error is introduced in the two cases, the trilaterlation technique using numerical analysis fails to provide the same location error. The location error can be.96 cm on the zone when the distance error is -.0 cm. The reason location error becomes larger in the boundary of the zone is not discussed, because this topic is beyond the scope of this paper. It is important to note that location error of the system is less than 2.44 cm, regardless of

15 the location of the receiver in the zone, since the maximum distance error of the Auto- Beaconing algorithm is less than 0.4 cm (See Section.2.)..2. Location Update Rate If only the Auto-Beaconing algorithm is used, the location update rate of the system can be determined from Eq. 2. Tslot is set to 20 msec, considering the maximum n distance between the receiver and beacons. The proposed system can achieve time synchronization between the receiver and beacons ( T sync ) within.5 msec, and thus the location update rate of the proposed system is approximately / TA B = Hz. The experimental result corresponds with this theoretical value. However, if the Zone management algorithm is used for zone selection, location update rate becomes 4.2 Hz, because the additional time to select a zone is necessary. 4. Conclusions In this paper, a novel indoor location system for a large indoor environment is proposed. The location system is based on synchronized sensor nodes consisting of a wireless sensor network, and location measurement results can be transmitted to the context-aware server through the wireless sensor network. The system architecture is described and system performance is evaluated through experiments, with regard location error and location update rate. The evaluation results demonstrate the feasibility of the proposed system in a large indoor environment. It is anticipated that wireless sensor networks will be deployed in most intelligent buildings in the near future, and many services in such buildings will be based on the location of objects. In this scenario, the system is very useful because it can be built by simply adding an ultrasonic sensor to sensor nodes consisting of wireless sensor networks. Acknowledgement This work has been supported by electronics and telecommunications research institute (ETRI) under Korean Ministry of Information and Communication. References. P. Enge and P. Misra, "Special Issue on GPS: The Global Positioning System," Proc. of the IEEE, vol. 87, no., pp. -72, Jan N. Priyantha, A. Chakraborty, and H. Balakrishnan, "The Cricket Location Support System," Proc. ACM Int'l Conf. Mobile Computing and Networking (MobiCom '00), pp. 2-4, Aug

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