Development of Zone-base and Time-based Localisation Techniques ...

Development of Zone-base and Time-based Localisation Techniques for the RFID Technology K Khedo* Dept. of Computer Science and Engineering Faculty of Engineering University of Mauritius Email: [email protected] D Sathan Dept. of Computer Science and Engineering Faculty of Engineering University of Mauritius Email: [email protected] R Elaheebocus Dept. of Computer Science and Engineering Faculty of Engineering University of Mauritius Email: [email protected] R K Subramanian Dept. of Computer Science and Engineering Faculty of Engineering University of Mauritius Email: [email protected] S D D V Rughooputh Dept. of Physics Faculty of Science University of Mauritius Email: [email protected]

Abstract Initially proposed as a replacement for barcode, RFID technology has evolved considerably in the past few years to such an extent that its development and deployment cost has incurred significant reduction. This has enabled the exploration of further application areas. RFID tags are now being used in anti-theft system, in the medical field as well as in supply chain management among others. One area of current research using RFID is Real Time Location Tracking (RTLT). The main reason behind this interest lies in the fact that RFID can be used in environments where other technologies have failed or are known to perform poorly. However, there exist various challenges related to RFID which has stalled research work in the area of RTLT. RFID suffers from drawbacks such as a limited reading range especially in cases where obstacles are present, and limitation of most commercial RFID readers in terms of capability for measuring signal strength and time of arrival. In this paper we have given a broad outline of RFID and reviewed some research works that have been done using RFID for localisation. Two localisation techniques aimed at overcoming some of the challenges have then been proposed. One is a time-based localisation technique suitable for outdoor environment which makes use of the Time of Arrival but requires specialised RFID readers and has a high implementation cost. The other employs an overlapping-zone-based deployment of readers and is appropriate for indoor since it is less susceptible to obstacles. Its cost is also significantly lower. We have thus recommended the latter for localisation of assets inside buildings.

Keywords: localisation algorithms, zone partitioning, distance estimation, time of arrival, trilateration *For correspondences and reprints

1. Introduction Research work related to Radio Frequency IDentification (RFID) has been gaining momentum over its main counter-part, barcode, which has been almost exhaustively researched. RFID technology makes it possible to identify an object, to track it and to know its characteristics remotely through a tag attached to the object, emitting radio waves, commonly referred to as a transponder which is then ‘read’ by an RFID reader. RFID technology enables the reading of tags without the need for line-of-sight, passing through a wide range of material with ease except metals. A wide range of innovative applications are being developed in areas such as supply chain management, health care and security. Some of the most popular are: Luggage tracking and identification systems at airports (Anon, 2002) resulting in unaccompanied or lost luggage being significantly reduced. Tracking of RFID tagged medical equipments and monitoring patients by implanting into them RFID tags equipped with sensors have successfully been tested (Wang, S. et al, 2006; Irnich W., 2002). The U.S. Department of Defence and WalMart have been requiring their suppliers to implement RFID in their supply chain management system (RFID Gazette, 2004; Rutner S. et al, 2004) providing them with higher security and more efficient management of inventories. Anti-theft systems using RFID technology are also becoming more popular (Roberts C.M., 2006). Products are tagged and the tags are removed or ‘killed’ at the counters during check-out. In case someone tries to sneak out with some unpaid product, readers positioned at exits will detect the RFID tags and sound alarms. Real time location tracking (RTLT) is one of the latest types of applications to join the long list enabled by RFID (Sanpechuda, T. & Kovavisaruch, L., 2008). Using different metrics such as signal strength, time of arrival or range of detection, objects’ positions can be estimated. This paper will focus mainly on this application area.

While GPS has been the main area of research when it comes to outdoor localization, signals from satellites are not that useful for the purpose of tracking objects inside buildings or in covered areas due to their penetration limitation (Sanpechuda, T. & Kovavisaruch, L., 2008). On the other hand, indoor localisation systems have made use of short to medium range signals (Hightower, J. & Borriello, G. 2001) from technologies like ultra-sound (Priyantha, N.B. et al, 2000), infrared (Ward, A. et al, 1997) , WiFi (Ladd, A. et al, 2002) , Bluetooth (Aalto, L. et al, 2004) or GSM (Otsason, V. et al, 2005). Initially employed as an alternative to barcode which had the drawbacks of requiring line-of-sight to be read, limited message payload and being read-only, RFID tags overcomes all these with ease when it comes to the tracking of RFID tagged objects in both indoor and outdoor environments (Yamano, K. et al, 2004). Some of the challenges that researchers face when considering RFID as a technology for localisation are its range limitation and susceptibility to interferences such as obstacles in its path or other radio signals emitted from electronic devices. Furthermore, the cost of RFID readers are still quite high, thus using a large number of such readers in a localisation system will significantly raise its cost. Most researches for RFID-based localisation make use of active RFID tags (having their own power-source) because of their longer reading range and are less sensitive to environmental settings. However, their much higher cost when compared to passive tags does warrant more research for localisation techniques using the latter. The two main categories of localisation using RFID are reader-based and tag-based (Sanpechuda, T. & Kovavisaruch, L., 2008). In the former, a reader is attached to the object being tracked as it navigates through paths fitted with RFID tags as proposed in (Yamano, K. et al, 2004; Lee, H.J. & Lee, M.C., 2006) where mobile robots are fitted with RFID readers.

However, this technique is suitable in cases where there is a single or only a few objects to be tracked since cost of readers are still very expensive when compared to RFID tags. The other category is the tag-based one which is usually the ‘way to go’ whenever there are a significant number of entities to be tracked each of which are fitted with an RFID tag which can either be active or passive. Tracking can be performed for both fixed and mobile objects but, in case of moving objects, localisation speed is lower than when using the reader-based method (Sanpechuda, T. & Kovavisaruch L., 2008). The outline of this paper is as follows: We have introduced RFID as an emerging technology in this section, a critical appraisal of existing localisation techniques is made in section 2. Section 3 presents our proposal for two localisation techniques, a ‘Time-Based distance estimation’ (TBDE) and an ‘Overlapping Zone Partitioning’ (OZP) technique. An evaluation of the two techniques is performed in section 4 from which we have derived our observation and recommendation in section 5. Finally, we conclude with our findings and proposal in section 6.

2. Related Works Existing research works on wireless localisation have made use of metrics such as time, angle and signal strength to come up with algorithms that yield an estimated location for a tracked object. Below, a brief overview of some common metrics has been given with a focus on ‘time’ which can be employed in a larger range of localisation settings. The different techniques used by some existing localisation algorithms have also been reviewed.

2.1 Localisation Metrics To perform localisation through signals, in this case, radio signals, three main metrics can be used namely, Angle of Arrival, Time, and Signal Strength. Angle of Arrival is normally appropriate in cases where there is line of sight between the reader and the object being

tracked. Similarly signal strength is vulnerable to obstacles located between the two entities. Moreover, measuring signal strength requires RFID readers having these capabilities (Assad, M.A., 2007; Kanaan, M. et al, 2006). While line of sight can be possible in outdoor environment especially by placing readers at higher altitudes, this is usually not the case inside buildings. In our case, rooms are separated by concrete walls. This constraint means that angle of arrival will not be appropriate. Similarly, signal strength will be affected due to the walls. The readers that have been acquired for the prototype of this system are also not capable of measuring signal strength. Another method which is related to signal strength is the zone-based approach. But instead of measuring the signal’s strength, we determine the reader’s reading range. This can be adjusted to some extent by varying the power supplied to the reader to either boost or reduce its range. Time will also be affected to some extent with the presence of obstacles; we are assuming that by performing proper calibration for the different zones, this problem may be mitigated. However this will have to be verified through experimentations. Two sub-categories of Timebased metrics were presented in the background. These are: Time of Arrival (TOA), also known as Time of Flight (ToF) and Time Difference of Arrival (TDOA). While TOA uses the absolute time at which the signal is received by the reader, TDOA computes the time difference when the signal reaches different readers placed at distinct locations.

2.2 Localisation algorithms A few of the most popular localisation algorithms have been reviewed and it has been found that they can be classified into two groups (Zhou, J. & Shi, J., 2008); the first is comprised of algorithms requiring that RF signal distribution be first calibrated before estimating an object’s location. These include the Multilateration and the Bayesian inference algorithms.

While the second has no need for prior calibration, examples of which are: the Nearestneighbour, Proximity, the Kernel-based learning algorithms.

2.2.1 Multilateration Multilateration derives coordinates estimation of the tracked object by calculating the distances between the reference points and the object. It is suitable for both 2D and 3D localisation. To enhance accuracy, more reference points can be used. Implementing multilateration algorithms is simple and does not involve much processing thus making it one of the most popular localisation algorithms (Medidi, M. et al, 2006; Moore, D. et al 2004; Payne, K. et al 2006; Savarese, C. et al, 2002; Smaliagic, A. & Kogan, D., 2002) . Another system making use of ad hoc lateration is SpotON (Hightower, J. et al, 2000) that make use of clustering of tags and is capable of 3D localisation. However, it requires special tags modified to be able to estimate inter-tag distance using radio attenuation. The long time (1020 seconds) required to get a location estimate means it cannot be used to track fast moving objects.

2.2.2 Bayesian inference A probability based algorithm, the Bayesian inference uses statistics to infer the probability that a hypothesis being correct. By using a recursive equation, the coordinates of the tracked object is obtained given the signal strength. The algorithm is suitable for localisation of mobile objects and has been employed using different approaches depending on the application. Some approaches are Kalman filters (Klee, U. et al, 2006; Chen, W. et al, 2007), multi-hypothesis tracking (Jensfelt, P., & Kristensen, S. ,1999), grid-based approaches (Burgard, W. et al, 1996), topological approaches (Blaer, P. & Allen, P., 2002; Kwon, T et al, 2006) and particle filters (Howard, A., 2006; Xu, S. et al, 2007). A rare usage of passive RFID tags for localisation has been made in (Alippi, C. et al, 2006) which employed both

Bayesian and detection power calculating position estimates. Its algorithm is also based on polar localisation which can be classified under the Angle of Arrival (AOA) metric.

2.2.3 Nearest-neighbour In the Nearest-neighbour algorithm, the coverage area has reference points. The signal strength of the reference points are compared with that of the tracked object. The reference point of the comparison pair resulting in the smallest difference is the location estimate of the object. The nearest-neighbour algorithm is said to be not sensitive to variations in the application environment and has been used in LANDMARC (Ni, L.M. et al, 2003) whereby two types of readers, one with longer range than the other are used to divide the area to be covered into sub-regions. Whenever a tag enters one of them, its distance with respect to the reader is computed. Reference tags are also placed in the coverage area and assigned different weightings. A major drawback with LANDMARC is that all reference tags are considered resulting in unnecessary computing. Another system making use of the nearestneighbour method is the Closest Neighbour with TOA grid (CN-TOAG) (Kanaan, M. & Pahlavan, K. 2004) where a number of reference points (RP) are in place and for each one of them, the value of the TOA at any point in the area being covered is known but, being a centralised algorithm, it is suitable mostly for covering small areas. One of the improvements that can be brought to both LANDMARC (Ni, L.M. et al, 2003) and CN-TOAG (Kanaan, M. & Pahlavan, K., 2004) is the reduction of comparisons that have to be made: instead of comparing with all the grid points, a few selected ones can be used and, based on the results, a smaller number of points are subsequently compared till the estimated location is zeroed in. Other systems using nearest neighbours are described by various authors.(Adult, A. et al, 2005; Lorincz, K & Welsh, M., 2007; Thiesse, F. et al, 2006).

2.2.4 Proximity The approximate communication area is used to determine whether the tracked object is in a region. More than one reader is required and the intersection of their coverage areas and whether the object is in that intersection provide the approximate location. A mobile reader with a smaller reading range can greatly enhance localisation using this method. For instance, He, T. et al (2005) used it for localisation in a wireless sensor network while Song, J. et al (2007) used it to locate materials on construction sites (Zhou, J. & Shi, J., 2008).

2.2.5 Kernel-based learning A bit similar to the proximity-based algorithm, the Kernel-based learning method is a more generalised one due to the fact that coverage areas overlap in arbitrary shapes. A sample of training data, consisting of radio signal readings transmitted from a number of access points and received at a training point along with that of their physical distances in the form of a vector, is fed into the algorithm which learns its parameters based on it (Brunato,M.,&Battiti, R., 2005; Nguyen, X et al, 2005). The three main phases of the Kernel-based learning algorithms are: (i) defining the kernel matrix, (ii) learning the discriminant function, (iii) online localisation (Zhou, J. & J. Shi, J., 2008).

3. Proposal We are proposing two localisation techniques that can address the challenges paused by wireless localisation in existing techniques in terms of cost, simplicity and scalability. One, we have referred to as a ‘Time-based distance estimation’ (TBDE) technique uses ‘time’ as a metric while the second, dubbed the ‘Overlapping Zone Partitioning’ (OZP) technique makes use of the reading range and prior reader location awareness. While the algorithms described earlier provide very good accuracy, they do not consider cost as a factor and therefore do not attempt to minimise the number of readers and tags employed. Another important issue is

simplicity of the localisation architecture both for development and deployment so as to facilitate its adoption by larger groups of users in a wider variety of settings. Localisation over a wide area has often not been tested thus algorithms that yield high accuracy in smaller regions may not necessarily do so for larger spaces. With these challenges in mind, we have proposed TBDE and OZPE which are described below.

3.1 Time-based distance estimation (TBDE) The time of arrival of the first detected peak (FDP) of the received signal is used to calculate the time of flight between the sensor and reference point or tracked object along the direct path. The distance from the sensor can then be calculated. Two main sources of error in TOA is from multipath effects resulting in reflected and transmitted paths being received along with the direct path and Undetected Direct Path conditions that results when the direct path is lower than the receiver’s threshold which can occur at the edges of the areas being covered by the transmitter or due to large metallic obstacles. The first condition can be reduced by increasing the transmission bandwidth. However, the increase will not reduce the UDP condition (M. Kanaan et al, 2006). Time Difference Of Arrival (TDOA) uses almost the same method as TOA except that at least three receiver locations are required. Since the radio signal transmission is always the same, the difference in the arrival times at pairs of receiver locations are used in the calculation of hyperbolas. The region where they intersect is the estimated location. Speed of radio signal It is assumed that since radio signal travels at a known velocity, by timing the reception, the distance of the emitter can be deducted though the formula d= s * t (where d is the distance, s is the speed and t is the time).

However, this holds only in vacuum since the signal’s speed will vary according to the medium it travels through. In our case, concrete walls and other obstacles will have to be taken into consideration. While most of the materials will be fixed, and thus can be taken into consideration beforehand, there will be students and staff members whose presence will vary. Trilateration To be able to pinpoint a location based on TOA or TDOA, the trilateration method is used. This requires that the coverage area is within the reading range of at least three RFID readers. While triangulation can be applied the angle of arrival (AOA) is available as metric which is obtainable mostly in system where there is line of sight, when using time of arrival (TOA), or time difference of arrival (TDOA), lateration is used. Trilateration is performed by measuring the distances between a signal emitter and several receivers. These distances are used as radius from their respective receivers. By intersecting the arcs, the position of the emitter can be estimated. Multilateration involves the intersection of arcs from more than three receivers intended to enhance accuracy of the location estimate.

Distances of object from Readers as radius

Estimated location of Tracked object

RFID Reader

Figure 1: Localization using trilateration: Perfect distance information

Figure 2: Localization using trilateration: Imperfect distance information

Due to interferences with the radio signals and multipath reflection effects, it is very likely that the time measurement will not have high accuracy. This will eventually translate into an

approximate distance estimate which will yield imperfect distance information as shown in figure 1. Notice that the region encircled in figure 1 covers a larger region compared to the point encircled in figure 2. Measuring time Measuring the time for a radio signal to reach a receiver from an emitter should be performed in the nano-scale since the signal’s speed is comparable to that of light. Furthermore depending on the methodology used (TOA or TDOA), proper time synchronisation between the measuring equipments are crucial in the estimation of the tracked object’s location. The hardware being used can also affect time measurement. Thus, in case more than one computer is involved, necessary precaution should be made to ensure that the different systems are configured in the same way and properly synchronised to mitigate discrepancies. Readers’ placements Three RFID readers and three RFID locaters are available. The readers have a range of up to 100 meters with line of sight while the locators are used for directional short range detection such as at exits and entrances. Due to the requirement when using triangulation that at least three measurements at different reference points are needed, the three readers’ reading range will need to overlap over the coverage area. This means that the three readers will not be sufficient to cover the whole floor. The reading ranges will be further reduced due to the presence of brick walls separating the different rooms. Thus, only part of the floor will have to be considered in this experiment. This portion will be determined during the equipments setup phase before system development and implementation.

Steps involved 

controller sends command to readers to perform detection of tags



readers send signal and listen for answers from tags within their range



time taken between a signal being sent and the time an answer is received is recorded



the time of flight is then calculated using ((Ts-Ta)/2) where Ts is the time at which signal was sent and Ta is the time at which an answer is received.



the time of flight when detecting the tracked object is sent to the controller



controller uses the formula D= S * T * X where D is the distance, S the speed of the signal, T is the time of flight and X is a constant value to cater for variations in signal speed due to obstacles. X will have to be determined through experimentation.



Since the position of the RFID readers are known and the distances between each reader and the tracked object, such that {(x1, y1), r1} {(x2, y2), r2} {(x3, y3), r3}



Where x and y represent the coordinates for the readers’ position and r represents the distance.



Finally to determine the coordinates of the estimated location, the following equations are used. They basically compute the point at which the different arcs intersect.

S = ((xc*xc) - (xb*xb) + (yc*yc) (yb*yb) + (rb*rb) -(rc*rc) ) / 2.0 T = ((xa*xa) - (xb*xb) + (ya*ya) (yb*yb) + (rb*rb) - (ra*ra)

) / 2.0

EX = ((T*(xb-xc)) - (S*(xb-xa))) / (((ya-yb)*(xb-xc)) - ((yc-yb)*(xb-xa))) EY = ((y*(ya-yb)) - T) / (xb-xa)



EX and EY forms the estimated coordinates of the tracked objects such that (EX,EY) can be plotted on our map.

3.2 Overlapping Zone partitioning (OZP) One of the simplest forms of localisation, zone-based localisation simply uses readers’ own location and reading range to provide an estimate of the location of a tracked object. This can be further enhanced by partly overlapping coverage areas by the readers to reduce the approximated location area. This is shown in the diagram below whereby 3 readers have been placed (A, B & C). Through overlapping, we have obtained 5 zones instead of 3 if there was no overlap. Furthermore, without overlapping, blind zones would have existed, that is, zones where tags cannot be read because they are outside the ranges of all the readers although they are inside the coverage area.

A

Z1

B

Z2

Z3

C

Z4

Z5

Figure 3. Overlapping Zone partitioning In Figure 3, three readers (A, B & C) are placed at equal intervals. Five zones (Z1-Z5) can be derived by using the readers’ reading range and the areas at which a reader’s reader range

overlaps that of another. In case a tracked object can be read by only reader A, we can assume that its location is within zone Z1 whereas if it can be read by both reader A and B, it is located in zone Z2. Figure 4 shows the reader placement within the building’s floor.

A X

B

C

Y

Figure 4. System deployment for second floor The system deployment for second floor is shown in Figure 4. A, B, C are the RFID readers placed at equal intervals throughout the corridor. Their reading omni-directional antennas will ensure maximum coverage. X & Y are two RFID locaters equipped with plate-antennas that can read tags at a restricted angle and direction. They are placed at the two legitimate exit points (stairways) from the floor. The RFID Locaters X & Y perform in/out logic determining whether an asset is leaving or entering the area. All the entrances and exits are recorded for auditing and helping in asset tracking. In case an unauthorised exit occurs, an alarm is triggered which can also involve sending of mobile text messages to security staff with details about the asset that has left, the point of exit and the time. In cases where an asset has to be moved from one location to another, outside their normal pre-assigned zone(s), member of the staff will have to carry his/her administrative tag with him/her. In that case, no

alarm will be triggered but a record linking the staff with the asset exiting the zone will be stored in the database.

4. Evaluation We have evaluated both the TBDE and OZP techniques based on the scenario that objects to be tracked are university assets such as laptops and RGB projectors that are located on one floor of a building consisting of brick-wall separated rooms. The table below summarises our findings based on different characteristics for the two techniques. Characteristic / Technique

TBDE

OZP

Accuracy

High accuracy can be obtained provided equipments used can record time at nano-level. Accuracy will be hampered with the presence of obstacles though. A precision of about 0.1 meters can be expected.

Accuracy is approximately half the reading range area of a reader. The reading range will depend on whether there is line of sight or not; the less obstacles in the path, the greater the reading range. In the current scenario, the precision is about 5 meters.

Cost

The initial cost of deployment is relatively high since TBDE requires that the object to be tracked is within the range of at least three readers. However cost will go down in cases that line of sight is present and thus readers will have greater ranges.

A low cost solution for small areas with zones demarked by walls or other materials preventing RF signals from travelling over long distances. At a larger scale, the cost proportionally increases.

Covering an area of 100 x 50 Covering an area of 100 x 50 meters with line of sight will meters with line of sight will require at least 3 RFID readers require at least 6 specialised costing about $850 USD each RFID readers costing about 1500 USD each Scalability

At a larger scale, the system will become more complex to manage, especially in cases where there is no line of sight and obstacles from a range of materials are present.

Using OZP, scalability is not a matter of matter of concern since deployment will be uniformly performed.

Heterogeneity

TBDE requires specialised OZP can be implemented using RFID readers with capabilities almost any off-the-shelf RFID to record Time Of Arrival. Thus reader and active tags. not all RFID readers can be used for this technique

Vulnerability to obstacles

Signals are affected by obstacles. In case these are from a range of materials, it becomes very difficult to predict this varying affectation rate. As a result, the propagation speed of the signal will widely vary and yield highly inaccurate distances.

The presence of obstacles will mean that coverage areas will not be in the form of circular zones as proposed in theory but will have to be manually mapped for the first time. However, after the mapping is performed, the accuracy level will not vary anymore.

Computation

Distances will have to be calculated between each reader (at least 3) and the tracked object. Their intersection is then obtained using the formula presented earlier.

The only calculation needed is to determine which readers have detected the tracked object and the zone is determined through a table look up.

Table 1. Characteristics evaluation

5. Observations and Recommendations Based on table 1, the main advantage of TBDE as a localisation technique is its high level of accuracy but this can be lost in case obstacles are present. The high implementation costs as well as computation costs are other drawbacks. In the case of OZP, fewer readers are used without the need for specialised RFID readers, thus significantly reducing implementation cost. It is also a very scalable technique that can be easily deployed over large areas without increasing its complexity. However, the main disadvantage of OZP is its inability for high-precision localisation.

After considering the two localisation proposals with respect to our current situation, that is, an indoor environment with brick walls separating rooms and the availability of three very basic RFID readers, we recommend that that the OZP technique be employed.

OZP will permit the system to be deployed campus-wide with little technical complexity and is highly scalable mainly due to its simplicity and low processing requirements. The need for fewer RFID readers when compared to TBDE implies a far lower financial investment required for achieving a fully functional system.

6. Conclusion Although there has been some recent research work in localisation through RFID technology, most of them have suffered from the inherent limitation of this technology such as reading range limitation and susceptibility to obstacles. To overcome these challenges, more readers are normally required and thus resulting in higher implementation cost. We have thus proposed two localisation techniques, namely the time-based distance estimation (TBDE) and the overlapping zone-partitioning (OZP) which are intended to have a lower cost, more scalable and less prone to obstacles. While OZP has been recommended as the most appropriate technique for our current scenario (one floor of a building having rooms separated by walls), TBDE is a suitable technique and in fact can perform better in scenarios with limited or no obstacles such as outdoor environments whereby antennas are placed on rooftops. The current high pricing of specialised RFID readers hinders further research into more advanced localisation techniques through RFID technology. Even the TBDE proposal has not been implemented for testing due to the lack of proper equipments.

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