IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION

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1 INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 7, NO. 3, SEPTEMBER 2014 IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION E-jie Dig, Xi Qiao, Fei Chag IoT Perceptio Mie Research Ceter, Chia Uiversity of Miig ad Techology Xuzhou, P. R. Chia s: Submitted: May 17, 2014 Accepted: July 5, 2014 Published: Sep. 1, 2014 Abstract- Node localizatio is oe of the key techologies of wireless sesor etworks (WSN). Due to the idoor eviromet requires a high positioig accuracy, a improved algorithm based o RSSI is put forward. I terms of RSSI ragig, the error correctio coefficiet received from self-correctig locator beaco odes, ad the had bee applied to distace solvig from ukow odes to the beaco odes. I the choice of weights, the algorithm uses iverse distace ad replaces the method of determiig the distace ad the reciprocal of the weights, ad also fixes the weight factor. O the complexity of the algorithm, select oe of the most recet four from ukow ode to beaco odes, reducig the amout of data calculatio. Simulatio results show that the proposed algorithm positioig accuracy has bee greatly improved. Idex terms: Node localizatio, RSSI, differetial correctio, wireless sesor etworks, idoor eviromet 1156

2 E-jie Dig, Xi Qiao, Fei Chag, IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION I. INTRODUCTION Node localizatio is the key techology of WSN, positioig accuracy has a crucial impact o the moitorig of the regio. With the developmet of wireless commuicatio techology, because idoor precise positio iformatio demad that more ad more positio iformatio should be high, simple, rapid, accurate, ad positioig of the iterior has also become a hot issue i WSN. At preset, more mature GPS positioig system ca achieve WSN ode localizatio, but takig ito accout the ode price, volume, eergy cosumptio ad evirometal factors, sesor odes with GPS positioig module ca ot be large-scale arragemet. May researchers have proposed various positioig algorithm for o GPS module, the proposed localizatio algorithm for WSN ca be divided ito two categories: which ca be divided ito rage-based localizatio algorithms (Rage-Based) ad rage-free localizatio algorithm (Rage-Free) [1-8]. The former eeds to be measured the absolute distace or agle iformatio betwee adjacet odes. Ragig positioig usig more techology RSSI (Received Sigal Stregth Idicatio) positioig algorithm [1], TOA (Time of Arrival) positioig algorithm [2], TDOA (Time Differece of Arrival) positioig algorithm [3], AOA(Agle of Arrival) positioig algorithm [4]; The latter oly eeds to kow which etwork coectivity iformatio to achieve positioig, such as cetroid algorithm [5], covex programmig algorithm [6], DV-Hop algorithm [7], approximate-poit i-triagulatio test [8]. Amog which localizatio algorithm is based o high precisio positioig ragig, but eeds higher hardware requiremets[11]; Locatio algorithm with distace has less demadig o the hardware-idepedet, but has lower precisio positioig. Amog them, RSSI locatio algorithm with simple, low cost, low power cosumptio ad requires o additioal hardware ad other advatages are widely used. But i the actual eviromet, locatio techology of RSSI are strogly iflueced by the eviromet based o the techology, complexity i iterior buildig structure of differet circumstaces, the positioig error is large. I recet years, the ode localizatio algorithm ad localizatio scheme have bee proposed by domestic ad foreig scholars[12-18], Literature [9] preseted a improved weighted cetroid localizatio algorithm. The algorithm uses iverse distace istead of the distace ad the sum of the weights as the reciprocal. A better solutio to the effects of large errors brought o positioig accuracy. However, this algorithm oly improve the positioig stage, without 1157

3 INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 7, NO. 3, SEPTEMBER 2014 cosiderig the effect of RSSI ragig techology brought the locatio results. Literature [10] proposed a distace measuremet algorithm based o RSSI hybrid filter ad least square estimatio. The value RSSI is corrected by the preferred method. Reductio due to evirometal factors o RSSI ragig, But i terms of positioig calculatios, which still ca ot meet the positioig accuracy requiremets. Literature [14] proposed a idoor positioig algorithm based o RFID experimet, the paper uses RFID techology to achieve the idoor positioig algorithm by gettig high positioig accuracy. The literature [15] presets a weighted hybrid localizatio scheme for improved ode positioig i wireless sesor etworks, the algorithm adopt RSSI ad DV-Hop techology to solve the hop depedecy problem. Literature [19] preseted the improved measure algorithm based o cosamp for image recovery. The algorithm superimposed determiistic rig measuremet matrix to optimize measuremet process o the basis of Fourier measuremet matrix. Ad solve the iterative iverse operatio by usig FFT fast Fourier calculatio method. Literature [20] preseted detectig wormhole attacks i wireless sesor etworks usig hop cout aalysis. The algorithm set up maximum ecessary hop cout betwee the sesor odes i the same eighbor. The algorithm have bee improved by all above these literatures, But it still ca ot meet the requiremets of accuracy. Based o this, we put forward a improved localizatio algorithm with high accuracy. The algorithm is maily positioig error usig the beaco odes, the ukow odes ad beaco odes distace correctio usig iverse distace; ad replace the traditioal distace ad reciprocal to determie weights, fixed weight coefficiet, ad the beaco ode is optimized, which reduce the ifluece of errors o the positioig results, improve the28% positioig precisio. II. POSITIONING ALGORITHM MODEL a. Idoor Radio Propagatio Loss Model I wireless sesor etwork localizatio algorithm, there is RSSI ragig techique commoly used positioig techology [16-18]. O the oe had, Commuicatio fuctio of sesor itself ad its RSSI fuctio make the simple measuremet rage. O the other had, whe positioig uder the complexity of the differet buildig structure, there may be more serious multipath effect, reflectio, refractio ad other iterferece, resultig i RSSI measuremet error will be 1158

4 E-jie Dig, Xi Qiao, Fei Chag, IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION large ad positioig error icreasig. The relatioship betwee received sigal stregth RSSI ad sigal trasmissio distace d ca be give by Eq. (1): RSSI P P d k = sed ( ( 0) + 10 log10( )) + ξ (1) d0 where, P is the trasmitted sigal power, sed k is the path loss factor, ξ is a mea zero ad variace σ of the Gaussia radom distributio fuctio, Pd ( 0) is radio sigal propagatio distace d ( d 0 0 = 1m ) of loss, it ca be writte as trasmittig power ad the receivig power differece ad calculated by Eq. (2): k P r GG t rλ Pd ( 0) = 10 lg 10 lg (4 ) k k Pt π d0 L d = (2) where P ad r P t are respectively the receivig ad trasmittig atea power, P =1W, t G ad G are respectively the trasmittig ad receivig atea gai, G r = G t =1, λ = c f, λ is the 8 wavelegth, c is the speed of electromagetic wave propagatio, c= 3 10 ms. By the formula (1) ad (2) ca be see, relatio betwee the size of the received sigal stregth RSSI ad the path loss factor k as well as that betwee RSSI ad the distace betwee the receivig ad trasmittig atea d are very close. I the differet eviromet that the path loss factor k values are ot the same, with the icrease of distace, the relatioship betwee the received sigal stregth RSSI ad k is show i Figure 1. I the theoretical ad practical situatios, the relatioship betwee the received sigal stregth RSSI ad sigal trasmissio distace d is show i Figure 2: r t 1159

5 INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 7, NO. 3, SEPTEMBER 2014 Figure 1. The relatioship betwee RSSI ad path loss factor Figure 2. The relatioship betwee RSSI ad sigal trasmissio distace After a large umber of experimets show that, whe the complexity of the idoor eviromet of buildig structure is higher, the path loss factor is 3.2 ad the Gauss radom distributio fuctio variace is 11.8dBm, Pd ( 0) = 35.2dBm. b. Cetroid Localizatio Algorithm The core idea of the cetroid algorithm [5, 13]: Beaco odes periodically broadcast iformatio to ukow odes, ad the iformatio icludig its ow ID ad positio coordiates. Lots of differet beaco odes of packets iformatio are recorded by ukow odes. After a certai 1160

6 E-jie Dig, Xi Qiao, Fei Chag, IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION time t, the threshold of commuicatio success rate P is set to the δ, is calculated betwee the ukow ode ad beaco odes. Oce the commuicatio success rate of ukow odes ad beaco odes exceeds the threshold, the ode ca be cosidered to be i the rage of the commuicatio ad commuicates with beaco odes, the the ukow odes is the cetriod of polygo regio composed of these beacos. Figure 3: ( X1, Y1) ( X, Y ) m m ( X, Y) t t ( X, Y ) 2 2 ( X, Y ) 4 4 ( X, Y ) 3 3 Figure 3. Polygo regio The coordiates of the ukow ode ca be estimated by usig Eq. (3): X + X + X Y + Y + Y X Y = < m M M M 1 2 m 1 2 m ( t, t) (, ),0 where ( X1, Y1) ( Xm, Ym) are the coordiates of these beaco odes that ca commuicate with the ukow odes, M is the umber of beaco odes. c. Weighted Cetroid Localizatio Algorithm The core idea of weighted cetroid localizatio algorithm [5,13]: Accordig to the ukow ode receives the sigal stregth RSSI size of these beaco odes, calculate weights betwee the ukow ode ad every beaco odes. These weights ca idicate beaco odes have ifluece o cetroid positio ad reflect the itrisic relatioship betwee them. The coordiates of the ukow ode ca be estimated by usig Eq. (4): i=m i=m i i i i i=1 i=1 est Yest = i=m i=m ( X, ) W X W Y (,) (4) W W i i=1 i=1 where ( X, Y ) is the coordiates of the ukow ode, ( X, Y ) is the first i coordiates of est est beaco ode, M is the umber of beaco odes, W i is the first i weight of beaco ode i i i (3) 1161

7 INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 7, NO. 3, SEPTEMBER 2014 ifluecig o the ukow ode, is a fuctio of the distace betwee ukow odes ad beaco odes. Typically, the farther the distace, the smaller the weight, if the beaco ode is ot withi the scope of commuicatio odes, the W i is 0. The traditioal locatio algorithm, the locatio techology of RSSI are strogly iflueced by the eviromet based o the same ode, the measured RSSI values are very differet, although the cetroid localizatio algorithm is simple, but the positioig accuracy is low, the weighted cetroid algorithm certai extet high positioig accuracy, but there are still some disadvatages. For these reasos, this paper proposes a improved positioig method, which greatly improves the positioig accuracy. III. IMPROVED LOCALIZATION ALGORITHM IMPLEMENTATION a. RSSI-based ragig techology of differetial correctio Effect of obstacles ad other evirometal factors i the actual eviromet, ragig out of the RSSI value does ot directly meet the radio to propagatio loss model. If you are still use the model without RSSI values ca be corrected will cause low positioig accuracy[21]. I this paper, usig the beaco ode from the earest ukow ode i the process of locatig the correctio coefficiet feedback to ukow odes, the ukow ode through the error correctio coefficiet obtaied to correct rage beaco ode. The method of error ragig from existece makes the improvemet to the algorithm, fudametally reduces the ifluece o positioig result, so it is possible to improve the positioig accuracy. 1) Beaco Nodes Self-correctig Positioig As is show i Figure 1, beaco ode A0( x0, y 0) is the earest distace from the ukow ode O. From the beaco ode withi its commuicatio rage of the odes A1( x1, y 1), A2( x2, y 2), Ai( xi, yi) are the actual distace d01, d02, d03,, d0i, Beaco ode A0( x0, y0) through RSSI ragig the distace betwee the estimated ad other beaco odes are respectively dˆˆˆˆ, 01 d02, d03,, d0i, Aˆ 0( xˆˆ0, y0) as the differece of beaco ode. 1162

8 E-jie Dig, Xi Qiao, Fei Chag, IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION A i A 4 A 1 d 01 d 0i A 0 dˆ 0 i d 04 ˆd 04 ˆd 01 R d 03 d 02 Â 0 ˆd 03 A 3 ˆd 02 A 2 Figure 4. Differetial correctio positioig of beaco ode (1) The Correctio Coefficiet of Beaco Nodes: where, β 1 M d dˆ dˆ 0i 0i = (5) r i= 1 0i M r are the stadard letters to all odes withi a radius of ukow ode commuicatio. Other beaco odes i a sesor etwork ca also gai correctio factor itself through the above methods, so that the beaco odes ca be corrected from its recet ukow ode. β represets the iformatio measuremet of RSSI usig beaco ode value differetial correctio coefficiet. (2) The correctio distace betwee beaco odes to ukow odes: d = d + βd (6) i 0' i 0' i where, d i is the ukow ode estimated distace from the differetial correctios; d 0'i is the measured distace from the ukow ode O to beaco odes; β is correctio coefficiet of beaco odes. b. Weighted cetroid algorithm based o modified Choose the right value weighted cetroid algorithm is very importat. It plays a key role for precise positioig. For the traditioal weight is the reciprocal of distace, there are a lot of methods to improve it. This article refereces [22]. O the basis of it cosiders differet beaco ode cotributio to the weight; the weight is modified, so that the positioig accuracy has bee greatly improved. 1163

9 INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 7, NO. 3, SEPTEMBER 2014 I this paper, the core idea of weighted cetroid algorithm weights modified is: Firstly, through the differece of radio propagatio loss model calculate the distace betwee odes, ad these distace values are arraged from small to large, take the first four values of beaco odes iformatio to calculate the ukow ode positio. The select oe of three odes i tur to be combied, there are a total of four combiatios, the beaco odes of each combiatio as the ceter of the circle respectively, the ukow ode to the correspodig combiatio of beaco ode distace as the radius of circle, calculate the three roud of overlappig regio cetroid coordiates of the triagle. Similarly, you ca fid the cetroid coordiates of other combiatios. Fially, the cetroid coordiates of these four weights which are revised; we ca calculate the coordiates of ukow odes. The improved coordiate of ukow odes i the algorithm as follows: I this paper, X1( + + )+X 2( + + )+X 3( + + )+X 4( + + ) d 1 d 2 d 3 d 1 d 2 d 4 d 1 d 2 d 4 d 2 d 3 d 4 X = ( ) d d d d Y1( + + )+Y 2( + + )+Y 3( + + )+Y 4( + + ) d 1 d 2 d 3 d 1 d 2 d 4 d 1 d 2 d 4 d 2 d 3 d 4 Y= ( ) d d d d 1 d + d + d is replaced by (7) ad is used to adjust the weightig d d d factor which make positioig accuracy of the proposed algorithm has bee greatly improved. By usig this approach, the iformatio of the distace of ukow odes ad beaco odes closer ca be fully utilized i the WSN odes localizatio. Therefore, we ca adjust the correctio factor, ad it is better robustess ad positioig accuracy for the proposig algorithm to arrage reasoable weights. IV. ALGORITHM IMPLEMENTATION PROCESS Accordig to the aalysis of the above model of the improved algorithm, the improved algorithm specific process ca be implemeted as follows: Step oe: beaco odes broadcasts ID iformatio as well as its ow coordiate iformatio to the surroudig ode periodically. 1164

10 E-jie Dig, Xi Qiao, Fei Chag, IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION Step two: ukow odes receive more tha M odes coordiate iformatio after a certai of time, which is o loger receive the iformatio, ad the differetial distace betwee the odes is obtaied by the radio propagatio model correctio. Step three: accordig to the improved differetial correctio value of RSSI locatio algorithm, by (5) (6) ca be obtaied from two ukow type differetial correctio beaco ode to ode distace d i. Step four: the ukow ode o the differetial correctio distace d i is arraged from small to large, ad establish the value of RSSI to the mappig relatioship betwee beaco odes ad ode distace, relevat set as follows: Beaco odes collectios: Beaco = { A A A A },,,, Beaco odes locatio iformatio collectio: {(, ),(, ),(, ) (, )} Positio = x y x y x y x y The differetial correctio distace collectio from ukow odes to beaco odes: Dista ce= { d, d, d, d }, d < d < d d Step Five: select the iformatio of the collectio of the first four beaco odes to calculate the ukow ode localizatio. The follow the modified weighted cetroid localizatio algorithm proposed i this paper, combied with equatio (7), which ca be calculated to estimate the coordiates of the ukow ode ( XY, ). V. SIMULATION RESULTS AND ANALYSIS I this paper, we use MATLAB platform for the improved algorithm simulatio aalysis, ad compared with the relevat methods to verify the performace of the proposed algorithm. a. Simulatio Parameters ad Defiitios Network emulatio eviromet settigs are as follows: WSN area size is 100x100m, radomly arraged 100 sesor odes i the area (icludig the ukow odes ad beaco odes). Assumig the radio sigal propagatio path loss model atteuatio factor k = 3.2, the carrier frequecy of the radio sigal of 2.4GHz, the distributio of radom oise i the chael betwee 5-8, the ode distributio as show i Figure 5. I order to verify the stability of the algorithm, 1165

11 INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 7, NO. 3, SEPTEMBER 2014 the algorithm simulatio 100 times ad take the average, the relevat defiitios ivolved are as follows: (1) Let us suppose that the actual positio of ode i ist i, the estimated positio ist i. The Ti T i j= 1 i= 1 average locatio error of the etire etwork ca be defied as e =. KN e (2) Normalized average locatio error e = : r is the commuicatio radius. r (3) To evaluate the performace of algorithms, it usually usig the root mea square as a performace measure of the algorithm, the specific formula is N 2 ( ei () ri ()) = M N + 1, M > N. i= M δ M, N where, ei () is a estimate value, ri () is the true value, M are the umber of achor odes, N = 1. N K Node distributio Beaco odes Ukow odes Simulatio area y coordiate/m Simulatio area x coordiate/m Figure 5. Simulatio odes distributed etwork eviromet b. Aalysis of Simulatio Results The simulatio compariso of RSSI algorithm, the weighted cetroid algorithm ad the algorithm proposed i this paper, maily from the relatioship betwee positioig deviatio, etwork ode positioig coverage rate, positioig error ad other factors. 1166

12 E-jie Dig, Xi Qiao, Fei Chag, IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION Figure 6. Ukow coordiate deviatio chart Figure 6 Simulatio beaco ode is 20, deviatio map of the estimated coordiates ad real coordiates for weighted cetroid algorithm ad improved algorithm. As it ca be see from the figure 6, the improved algorithm is much higher tha the positioig accuracy the weighted cetroid algorithm used, ad better stability. Figure 7. The relatioship betwee the percetage of beaco odes ad the coverage rate of positioig Commuicatio radius of 20, three differet algorithms for etwork localizatio coverage chages is show i figure 7. Cotrast from Figure 6 shows that, with the icrease of beaco odes, ode locatio coverage rate of RSSI algorithm ad weighted cetroid localizatio 1167

13 INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 7, NO. 3, SEPTEMBER 2014 algorithm icreased; but the ratio of beaco odes is low, RSSI algorithm ad weighted cetroid localizatio algorithm of coverage is low, whe the beaco ode ratio is about 0.15, two algorithms coverage rate is early 90%; ad the proposed algorithm the beaco ode is small, ca be full of WSN localizatio, effectively reduces the cost of etwork ode localizatio. Figure 8. Effect of path loss coefficiet of positioig error Figure 8 Simulatio beaco odes is 30, the path loss factor of the ifluece of the positioig error, as ca be see from Figure 8, with the icrease of path loss coefficiet, three algorithms of etwork ode positioig error is reduced, but obviously it ca be see that the proposed algorithm has good performace. Figure 9. Normalized average positio error 1168

14 E-jie Dig, Xi Qiao, Fei Chag, IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION Figure 9 simulated three differet methods of ormalized average locatio error, ca be see from the diagram, with the icrease i the umber of beaco odes, obtaiig useful iformatio to the RSSI values are also become more, positioig error first rapidly declie ad the slowly declie, ad fially teds to be a miimum error, compared with the weighted cetroid algorithm improved by about 27.3%. Figure 10. Impact of ode commuicatio radius of positioig error Figure 10 Simulatio of beaco odes is 30, the relatioship betwee the average locatio error with commuicatio radius chages. Commuicatio radius is too small to make the average error is too large, ad eve lead to a lot of ukow odes ca ot locate. Set up the commuicatio radius from 20m to 50m accordig step legth 5. As it ca be see from Figure 10, the commuicatio radius icreases, the average locatio error of three algorithms are the first declie ad the rise slowly, ad the proposed algorithm is much better tha the weighted cetroid localizatio algorithm. Therefore, the positioig process to select the best commuicatio radius is very importat, which is directly related to the error locatio, optimal commuicatio radius of the improved algorithm is 33m. 1169

15 INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 7, NO. 3, SEPTEMBER 2014 Figure 11. Relatioship betwee the average locatio error ad correctio factors Figure 11 simulated three differet methods of the relatioship betwee the average simulated average positio error ad correctio factor, As ca be see from the simulatio diagram, the average positioig error RSSI algorithm is , the average positioig error of weighted cetroid localizatio algorithm is m, the improved algorithm herei correctio coefficiet icreases as the average positioig error gradually declie. Whe the correctio factor =5, the positioig accuracy of the improved algorithm basically close to the same. Table 1 Algorithm performace compariso RSSI Improved algorithm Beaco odes Error /m RMS Error /m RMS I table 1, simulatio of the commuicatio radius of 30, performace evaluatio ad average positioig error of improved algorithm ad RSSI algorithm. As ca be see from the table 1, the average positioig error of improved algorithm is much smaller tha of RSSI algorithm. The error of improved algorithm root mea square is merely about 1/12 of RSSI algorithm, The improved algorithm has obvious advatage i the positioig performace. 1170

16 E-jie Dig, Xi Qiao, Fei Chag, IMPROVED WEIGHTED CENTROID LOCALIZATION ALGORITHM BASED ON RSSI DIFFERENTIAL CORRECTION VI. CONCLUSIONS With the higher complexity of iterior structures, we propose a improved weighted cetroid localizatio algorithm based o RSSI differetial correctio. Through the experimetal test of each parameter o the ifluece of RSSI value, model parameters are give i the wireless sigal trasmissio i idoor eviromets. Improvemets i the algorithm, makig full use of RSSI locatio algorithm ad weighted cetroid localizatio algorithm based o improvemets to improve the positioig accuracy of the algorithm from RSSI corrected ad weighted cetroid. Uder the same simulatio eviromet, the improved algorithm o the accuracy ad robustess which is better tha RSSI algorithm ad weighted cetroid algorithm, while the positioig algorithm has less demad for the hardware to meet the requiremets of low cost ad low power cosumptio, the paper has very high applicatio value. I future work, we will carry out further research o differet floors of wireless trasmissio model to idetify the wireless trasmissio model for differet floors ad do some experiece to be verified. ACKNOWLEDGEMENTS The research work was supported by Natioal Sciece ad Techology Support of Chia uder Grat No. 2012BAH12B01, 2012BAH12B02 ad Natioal Natural Sciece Foudatio of Chia uder Grat No REFERENCES [1] L Girod, V Bychkovskiy, J Elso, Locatig tiy sesors i time ad space: A case study, Proceedigs of the 2002 IEEE Iteratioal Coferece o Computer Desig, Freiburg (Germay), 2002, pp [2] A Harter, A Hopper, P Steggles, The Aatomy of a Cotext-Aware Applicatio, Wireless Network, 2001, pp [3] L Girod, D Estri, Robust Rage Estimatio Usig Acoustic ad Multimodal Sesig, IEEE Iteratioal Coferece o Itelliget Robots ad Systems. Hawaii (USA), March 2001, pp

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