IEEE INFOCOM 2018-IEEE Conference on Computer Communications exist some differences among them.2 x 2,Squig and Squiggle duces them using high-speed video of the object.The authors have very close accuracy (i.e.,0.28Hz,0.25Hz and 0.30Hz in [16]make it possible to observe and capture a high-speed respectively).while Square model observes a lower accuracy periodic video well beyond the abilities of a low-frame-rate of 0.61Hz with a higher standard deviation of 0.43Hz.This can camera.The proposed reconstruction algorithms are inspired be explained by the size of tag's antenna,because Square has by compressive sensing.Wei et al.[17]recover loudspeaker a more compact volume (only 22.5mm x 22.5mm)compared sound by inspecting the subtle disturbance it causes to the with the other three types.Generally speaking,the tag with radio signals generated by the co-located WiFi transmitter. larger antenna could absorb more energy from the reader, making its backscattered signal stronger (i.e.higher SNR) VIII.CONCLUSION and thereby outputting more precise sensing result.In our experimentation,we use model "Squig"in most cases. This work presents an RFID-based spinning sensing system that is robust to noisy settings and achieves sub-hertz high ac- 5)Impact of Multipath:One prominent advantage of uti- curacy.Our key innovations lie in leveraging the relative signal lizing RFID to sense spinning over prior approaches is that of dual RFID tags to resist the system shaking and proposing it can work either in the absence of line-of-sight (LOS) a new form of compressive reading technique to recover the or the presence of rich multipath.To investigate this,we signal.We believe our system will promote more possibilities perform evaluation in two typical settings:(a)a clear free- of RFID-based sensing solution in practical deployments. space environment with no multipath effect;(b)a non-line- of-sight (NLOS)or strong multipath scenario with obstacles ACKNOWLEDGMENT between (or around)the turntable and reader.For each setting. we carry out 50 experiments and plot the CDF of frequency The research of Lei Yang is partially supported by ECS error in Fig.17.It is clear that the overall accuracy in LOS is (NO.25222917).NSFC General Program (NO.61572282). better than that in NLOS.The mean error is 0.32Hz with 90% and Alibaba Innovation Research.The research of Lei Xie below 0.54Hz in LOS scenario while that of NLOS is 0.79Hz is partially supported by NSFC (No.61472185),and JiangSu with 90%below 2.1Hz.Since more paths will arrive at the Natural Science Foundation (No.BK20151390). two tags in NLOS scenario instead of one dominant path,the REFERENCES error is accumulated along these paths.Besides,the reflected signal will traverse a longer path compared to the direct one, [1]Y.Lei,Z.He,and Y.Zi."Application of an intelligent classification impairing the signal strength.Even the accuracy drops a little method to mechanical fault diagnosis,"Expert Systems with Applica- in NLOS environment,it still overwhelms many traditional ions,vol.36.no.6.pp.9941-9948.2009. [2]L.Yang.Y.Li,Q.Lin,X.-Y.Li,and Y.Liu,"Making sense of mechan- instruments like laser which fails in such condition. ical vibration period with sub-millisecond accuracy using backscatter signals,"in Proc.of ACM MobiCom,2016. VII.RELATED WORK [3]ImpinJ,"Speedway revolution reader application note:Low level user We briefly review the literature that is related to our work. data support,"in Speedway Revolution Reader Application Note,2010 [4]D.M.Dobkin.The RF in RFID:UHF RFID in Practice.2012. Traditional sensing approaches:One typical way to in- [5]L.Yang,Y.Chen,X.-Y.Li,C.Xiao,M.Li,and Y.Liu,"Tagoram:Real- spect spinning is to employ mechanical sensors to capture the time tracking of mobile rfid tags to high precision using cots devices," force induced on the instrument and utilizes the fact that the in Proc.of ACM MobiCom,2014. [6]S.Kumar,S.Gil,D.Katabi,and D.Rus,"Accurate indoor localization centrifugal force on a rotating mass depends on the speed of with zero start-up cost,"in Proc.of ACM MobiCom,2014. rotation.These methods [9],[10]make sense of spinning via [7]D.Tse and P.Viswanath,Fundamentals of wireless communication infrared/laser,which is then reflected by a reflective tape on Cambridge university press,2005. [8]EPCglobal,"Low level reader protocol (lIrp)."2010. the object.The rotation speed is then measured as the rate [9]P.Castellini,M.Martarelli,and E.P.Tomasini,"Laser doppler vi- at which the light beam is reflected back.The authors in [11] brometry:Development of advanced solutions answering to technology's demonstrate nanometer vibration analysis of a target by a self- needs,"Mechanical Systems and Signal Processing,vol.20,no.6,pp. 1265-1285.2006. aligned optical feedback vibrometry technique.Optical-based [10]P.Cheng.M.S.M.Mustafa,and B.Oelmann,"Contactless rotor schema is a powerful choice when direct-contact measurement rpm measurement using laser mouse sensors,"IEEE Transactions on is infeasible for technical or safety reasons. Instrumentation and Measurement,vol.61,no.3,pp.740-748,2012. [11]K.Otsuka,K.Abe,J.-Y.Ko,and T.-S.Lim,"Real-time nanometer- RFID-based sensing approaches:A mountain of research vibration measurement with a self-mixing microchip solid-state laser," work in RFID area has focused on localization in the past Oprics letters.vol.27,no.15,pp.1339-1341,2002. years [5].[12].Tagbeat [2]makes the first attempt to inspect [12]C.Duan,L.Yang,and Y.Liu,"Accurate spatial calibration of rfid antennas via spinning tags,"in Proc.of IEEE ICDCS,2016. vibration via RFID technology,with the advantage of being [13]N.Roy.M.Gowda,and R.R.Choudhury,"Ripple:Communicating low-cost and applicable to occluded and non-line-of-sight through physical vibration,"in Proc.of USENIX NSDI.2015. scenario.But it is not robust to the shake of device,hindering [14]N.Roy and R.R.Choudhury,"Ripple ii:Faster communication through physical vibration,"in Proc.of USENIX NSDI,2016. its further application in real practice.In contrast,we tactfully [15]A.Davis.M.Rubinstein,N.Wadhwa.G.Mysore,F.Durand,and W.T. solve this issue by employing dual tags and utilizing their Freeman,"The visual microphone:Passive recovery of sound from relative phase as the spinning signal. video,"in Proc.of ACM SIGGRAPH,2014. [16]A.Veeraraghavan,D.Reddy,and R.Raskar,"Coded strobing pho- by sound hitting an object and recovers the sound that pro- tography:Compressive sensing of high speed periodic videos,"IEEE Other related issues:[13],[14]aim to communicate small Transactions on Pattern Analysis and Machine Intelligence,vol.33. no.4,Pp.671-686,2011. packets of information by modulating the vibrations of motors [17]T.Wei,S.Wang.A.Zhou,and X.Zhang."Acoustic eavesdropping present in mobile phones.[15]extracts small vibrations caused through wireless vibrometry,"in Proc.of ACM MobiCom,2015.exist some differences among them. 2⇥2, Squig and Squiggle have very close accuracy (i.e., 0.28Hz, 0.25Hz and 0.30Hz respectively), while Square model observes a lower accuracy of 0.61Hz with a higher standard deviation of 0.43Hz. This can be explained by the size of tag’s antenna, because Square has a more compact volume (only 22.5mm⇥22.5mm) compared with the other three types. Generally speaking, the tag with larger antenna could absorb more energy from the reader, making its backscattered signal stronger (i.e. higher SNR) and thereby outputting more precise sensing result. In our experimentation, we use model “Squig” in most cases. 5) Impact of Multipath: One prominent advantage of uti￾lizing RFID to sense spinning over prior approaches is that it can work either in the absence of line-of-sight (LOS) or the presence of rich multipath. To investigate this, we perform evaluation in two typical settings: (a) a clear free￾space environment with no multipath effect; (b) a non-line￾of-sight (NLOS) or strong multipath scenario with obstacles between (or around) the turntable and reader. For each setting, we carry out 50 experiments and plot the CDF of frequency error in Fig. 17. It is clear that the overall accuracy in LOS is better than that in NLOS. The mean error is 0.32Hz with 90% below 0.54Hz in LOS scenario while that of NLOS is 0.79Hz with 90% below 2.1Hz. Since more paths will arrive at the two tags in NLOS scenario instead of one dominant path, the error is accumulated along these paths. Besides, the reflected signal will traverse a longer path compared to the direct one, impairing the signal strength. Even the accuracy drops a little in NLOS environment, it still overwhelms many traditional instruments like laser which fails in such condition. VII. RELATED WORK We briefly review the literature that is related to our work. Traditional sensing approaches: One typical way to in￾spect spinning is to employ mechanical sensors to capture the force induced on the instrument and utilizes the fact that the centrifugal force on a rotating mass depends on the speed of rotation. These methods [9], [10] make sense of spinning via infrared/laser, which is then reflected by a reflective tape on the object. The rotation speed is then measured as the rate at which the light beam is reflected back. The authors in [11] demonstrate nanometer vibration analysis of a target by a self￾aligned optical feedback vibrometry technique. Optical-based schema is a powerful choice when direct-contact measurement is infeasible for technical or safety reasons. RFID-based sensing approaches: A mountain of research work in RFID area has focused on localization in the past years [5], [12]. Tagbeat [2] makes the first attempt to inspect vibration via RFID technology, with the advantage of being low-cost and applicable to occluded and non-line-of-sight scenario. But it is not robust to the shake of device, hindering its further application in real practice. In contrast, we tactfully solve this issue by employing dual tags and utilizing their relative phase as the spinning signal. by sound hitting an object and recovers the sound that pro￾Other related issues: [13], [14] aim to communicate small packets of information by modulating the vibrations of motors present in mobile phones. [15] extracts small vibrations caused duces them using high-speed video of the object. The authors in [16] make it possible to observe and capture a high-speed periodic video well beyond the abilities of a low-frame-rate camera. The proposed reconstruction algorithms are inspired by compressive sensing. Wei et al. [17] recover loudspeaker sound by inspecting the subtle disturbance it causes to the radio signals generated by the co-located WiFi transmitter. VIII. CONCLUSION This work presents an RFID-based spinning sensing system that is robust to noisy settings and achieves sub-hertz high ac￾curacy. Our key innovations lie in leveraging the relative signal of dual RFID tags to resist the system shaking and proposing a new form of compressive reading technique to recover the signal. We believe our system will promote more possibilities of RFID-based sensing solution in practical deployments. ACKNOWLEDGMENT The research of Lei Yang is partially supported by ECS (NO. 25222917), NSFC General Program (NO. 61572282), and Alibaba Innovation Research. The research of Lei Xie is partially supported by NSFC (No. 61472185), and JiangSu Natural Science Foundation (No. BK20151390). REFERENCES [1] Y. Lei, Z. He, and Y. Zi, “Application of an intelligent classification method to mechanical fault diagnosis,” Expert Systems with Applica￾tions, vol. 36, no. 6, pp. 9941–9948, 2009. [2] L. Yang, Y. Li, Q. Lin, X.-Y. Li, and Y. Liu, “Making sense of mechan￾ical vibration period with sub-millisecond accuracy using backscatter signals,” in Proc. of ACM MobiCom, 2016. [3] ImpinJ, “Speedway revolution reader application note: Low level user data support,” in Speedway Revolution Reader Application Note, 2010. [4] D. M. Dobkin, The RF in RFID: UHF RFID in Practice, 2012. [5] L. Yang, Y. Chen, X.-Y. Li, C. Xiao, M. Li, and Y. Liu, “Tagoram: Real￾time tracking of mobile rfid tags to high precision using cots devices,” in Proc. of ACM MobiCom, 2014. [6] S. Kumar, S. Gil, D. Katabi, and D. Rus, “Accurate indoor localization with zero start-up cost,” in Proc. of ACM MobiCom, 2014. [7] D. Tse and P. Viswanath, Fundamentals of wireless communication. Cambridge university press, 2005. [8] EPCglobal, “Low level reader protocol (llrp),” 2010. [9] P. Castellini, M. Martarelli, and E. P. Tomasini, “Laser doppler vi￾brometry: Development of advanced solutions answering to technology’s needs,” Mechanical Systems and Signal Processing, vol. 20, no. 6, pp. 1265–1285, 2006. [10] P. Cheng, M. S. M. Mustafa, and B. Oelmann, “Contactless rotor rpm measurement using laser mouse sensors,” IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 3, pp. 740–748, 2012. [11] K. Otsuka, K. Abe, J.-Y. Ko, and T.-S. Lim, “Real-time nanometer￾vibration measurement with a self-mixing microchip solid-state laser,” Optics letters, vol. 27, no. 15, pp. 1339–1341, 2002. [12] C. Duan, L. Yang, and Y. Liu, “Accurate spatial calibration of rfid antennas via spinning tags,” in Proc. of IEEE ICDCS, 2016. [13] N. Roy, M. Gowda, and R. R. Choudhury, “Ripple: Communicating through physical vibration,” in Proc. of USENIX NSDI, 2015. [14] N. Roy and R. R. Choudhury, “Ripple ii: Faster communication through physical vibration,” in Proc. of USENIX NSDI, 2016. [15] A. Davis, M. Rubinstein, N. Wadhwa, G. Mysore, F. Durand, and W. T. Freeman, “The visual microphone: Passive recovery of sound from video,” in Proc. of ACM SIGGRAPH, 2014. [16] A. Veeraraghavan, D. Reddy, and R. Raskar, “Coded strobing pho￾tography: Compressive sensing of high speed periodic videos,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 4, pp. 671–686, 2011. [17] T. Wei, S. Wang, A. Zhou, and X. Zhang, “Acoustic eavesdropping through wireless vibrometry,” in Proc. of ACM MobiCom, 2015. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications