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ISBN NO : 378 - 26 - 138420 - 8
Development of Sensing Device to Detect Persons Hiding in a Car 1
Mohammed Sanaullah Shareef.M.Y, 2Mohammed Tharique.PM Department of Electronics and Communication Engineering, C.Abdul Hakeem College of Engineering and Technology 1 sanaullahshareef786@gmail.com, , 1 +919944738419.
1,2,3
and places a heavywork load on border officers, resulting in high costs in view ofthe thousands of vehicles that cross the borders. Alternatives tothis manual method have been considered, such as the X-rayequipment used to check vehicles and their cargo [4] and theuse of a mobile inspection robot [5]. However, these methodsrequire a high initial cost as well as a large setup area. Moreover, danger of using the X-ray method for finding illegal immigrants is indicated because the illegal immigrants would beexposed to X-ray [6]. A simpler method, which uses microvibrations to detect a concealed person, has been proposed [7].We also presented a similar method that detects heartbeat signals by means of a piezoceramic device set under the tire of avehicle [8]. These methods, however, are sensitive not only tohuman micro vibrations but also to external disturbances such asground vibration and wind force acting on the vehicle. This paper describes a novel pneumatic method that uses silicon air tubes and a low-frequency condenser microphone asa pressure sensor highly sensitive to the heartbeat signals of aperson hiding in a vehicle but robust against external disturbances such as ground vibration and wind force.
Abstract—This paper describes a novel method for detecting the presence of a person hiding in a car. One of the important strategies of homeland security is border control. In particular, strict and effective monitoring to control illegal immigration is a key strategy for maintaining public safety and a healthy local economy, and is essential for preventing the entry of terrorists. Here, we focused on
developing a method to detect a person trying to illegally cross the border by hiding in a car. The proposed method is based on pneumatics. A silicon tube (inner diameter 4 mm) with one end plugged by a highly sensitive pressure sensor and the other end capped is sandwiched between two rigid boards and placed on the ground at the entrance gate of the border. When one wheel of the car is on the board and the engine is stopped, the pressure sensor can detect human vital signs such as the heartbeat, which cannot be concealed. Due to the high sensitivity of the pressure sensor, consideration was given to the effect of external disturbances such as ground vibration and wind force acting on the car. Here, we propose a heartbeat detection filter robust against disturbances but sensitive to the heartbeat signal and an index to discriminate between the presence and non-presence of a person, and we present the experimental results obtained using the proposed method under various disturbance conditions. Index Terms—Automobile, condensermicrophone, security, silicon tube.
II. DESIGN OF SENSING DEVICE A. Principle of the Sensing Device Using Silicon Tube andCondenser Microphone Fig. 1 shows the principle of the sensing device used to measure themicro vibrations. The silicon tube is set between flexiblespacers on the base board. At one end of the tube is the low-frequency condenser microphone used as the pressure sensor, andthe other end of the tube is capped. A cover board is placed ontop of the tube and flexible spacers. When one wheel of the caris on the board and the engine is stopped, and if there is a personhiding inside the car, the vibration from the person’s heartbeatwill be transmitted through the car chassis, wheel, tire, coverboard, and finally to the silicon tubes and spacers. Displacementcaused by the vibrating cover board compresses the silicon tubesand spacers, which decreases the crosssection area of the tubeand increases the air pressure in the tube. The pressure sensordetects the change in pressure. The pressure change is producednot only by the heartbeat but also by the resonance frequencycomponent of the car chassis fromthe dynamic pressure of windacting against the car and the movement of a person changingposition.
I. INTRODUCTION ILLEGAL immigration from neighboring countries is a serious problem from the viewpoint of homeland security and crime prevention. In the United States, the number of illegal immigrants exceeds 1,20,00,000 [1]. In bordering countries, illegal immigration is frequently attempted via ground vehicles such as cars and trucks in which one or more persons are hidden under the seats, in the engine compartment or in spaces carved out of the dashboard [2]. In one case, an officer of the Arizona State Border Control found 13 people hiding in a van disguised as a transport truck [3]. Accurate devices to quickly and easily find people hiding in vehicles are necessary to maintain strict border control as well as make the legal immigration procedure more effective. Generally, a border officer checks the inside and/or outside of a vehicle to determine if anyone is hiding there. The inspectionis a visual search, which is time-consuming
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S[m2]surface upon which the force acts; K[N/(m2)]spring constant of the silicon tube γratio of specific heat; Ththreshold for discriminating between presenceand non-presence of person; The total force acting on the surface of the tube is given by
(1)
Fig. 1. Principle of the microvibration sensing device using silicon tubes.
Fig. 3. Signal processing flow for extracting fh(t) andfb(t)components. As the change in the state of air in the tube is adiabatic, the relationship between the pressurep(t) and the volume v(t)is given by Poisson’s law as follows: (2) Total differentiation of (2) forp(t) is given by
Fig. 2. Mathematical model of air tube with condenser microphone.
(3) By lettingP(t)=P0,V(t)=V0,dv(t)=Sx(t),f(t)=Sdp(t)then (2) can be rewritten as
B. Mathematical Model of the Silicon Tube and CondenserMicrophone We considered a mathematical model for the sensing device depicted in Fig. 1, Fig. 2 shows a schematic model of the device. The variables and constants for themodel are defined as follows: t[s]continuous time; K discrete time by sampling interval ; T[s]total measurement time; Po[Pa]steady-state pressure in the tube; p(t)[Pa]change in pressure P(t)[Pa]pressure with change in pressure ; V0[m3]air volume of the tube under steadystatepressure; v(t)[m3] total air volume in the tube with change involume fh(t)[N] force acting on the tube due to human heartbeat; fb(t)[N] force acting on the tube due to body movement; fc(t)[N]force acting on the tube due to resonancevibration of the car chassis; n(t)[N]force acting on the tube due to random noise f(t)[N]total force acting on the tube; x(t)[m]surface displacement due to total force e(t)[V]output voltage from the pressure sensor
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(4) Equation (4) shows the characteristics of the air spring of thesilicon tube. On the other hand, the silicon tube itself has stiffness with spring constant K. Thus, from (3) or (4), the changein pressure in the tube due to the total force is given by (5) Thus, from (5) above, the coefficient * which corresponds to thecross-sectional area that relates the external force to the tubeand the internal pressure, is a function of the contactingarea S. Thecoefficient increases in proportion to S forthe range , whereas for the range , it decreases in proportion to S. Thesilicon tube is flexible and thus the spring constant K issmall, smaller than that of the air spring. Then, the coefficientincreases in proportion to S the contacting area . Thus, toobtain a larger coefficient, we must make the contacting area S wider and reduce the spring constant of the tube and spacer. Torealize these conditions, the spacer must be as soft as possibleto
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make the contacting area wider; the tube is pressed not onlyby the upper plate but also by the side spacer, as shown in thefront view in Fig. 1.
sensor. Sensitivity is 10 mV/Pa withflat-gain characteristics for the frequency range of 0.1 Hz to 10kHz, allowing the detection of heartbeat and body movement.
C. Signal Processing Flow The pressure expressed in (5) is detected by the condensermicrophone acting as a highly sensitive pressure sensor. Outputvoltage e(t) from the sensor includes various vibration forces asgiven by (1). Fig. 3 shows how to extract the force components fh(t)andfb(t), which are the vital signs of a person hiding inthe car. The fundamental frequency of the adult human heartbeat is around 0.7 to 3.0 Hz. However, the frequency range alsocovers part of the mechanical vibration component fc(t)of thechassis, which must be distinguished from the heartbeat. Theheartbeat includes higher harmonic components of up to severalhundred Hz.We monitored the higher harmonic components of8 to 12 Hz with a relatively high spectrumand less noise and discriminated the components by means of a band pass filter. Thecomponent is rectified and smoothed using a band pass filterwitha cutoff frequency of 0.5 and 2.0 Hz, which yields a shift backto the fundamental frequency range. The other vital sign,fb(t) for body movement, is much greater than the heartbeat and thuscan be directly detected. The output voltage from the pressure sensor is an A-D converted with the sampling time andexpressed by e(k) for the discrete time .
Fig. 4.Sensing device for verification experiment.
D. Index for Judging Human Presence Here, we define the index for judging whether or not a personis present in the car. In the filtering process in Fig. 3, the disturbance componentsfc(t) and n(t) are filtered out. Thus, the standard deviation of the output signal becomes greater whena person is present compared to when no one is present. Thus,the simple standard deviation of can serve as the index:
(6) The presence of aperson is discriminated by comparing the index with thethreshold .
Fig. 5. Experimental conditions for Case 1. The cover board is made of polycarbonate with a thickness of 5 mm.
III. VERIFICATION EXPERIMENT A. Measurement System for Verification Experiment Fig. 4 shows the sensing device used in the verification experiments. Forty-eight rectangular shaped spacers with dimensions 400*30*10 mm are set on the base board. The spacersare made of a soft, sponge-type material. Six silicon tubes, each with a pressure sensor, are set among the spacers. The tubescover the entire area of the board and are compressed by verticaland horizontal forces, as shown in the front view in Fig. 1. Sincesilicon tubes are softer and more flexible and durable than vinylchloride tubes, the spring constant K of the tube and spaceris smaller and the sensitivity becomes high. A low-frequencymicrophone (MX-E4758) was selected as thehighly sensitive pressure . As shown in Fig. 5, we placed a blower 1 m away from a sedan-type car to blow air at different strengths: strong 132
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B. Measurement Procedures In order to verify the validity of the sensing method, we carried out the experiment for two cases using the sensing device shown in Fig. 4. We let T=2.56s and ∆t=10ms and acquired data 40 times and calculated index F for each experimental condition. (Case 1) Verification experiment for robustness against wind and vibration. In practical case, this system might be used outdoors. In that case, the chassis is shaken by thewind and itmight cause a factor of the error for judgment. Hence, we verified the robustness ofthe system against the wind
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m3/min, medium 102 m3/min, weak 72 m3/min and none. We compared how index F changed depending on whether or not a person wasin the car. (Case 2) Ability to detect a person in a camper with varioushiding places.
Fig.
6.
Experimental conditions for Case 2. Fig. 7.Heartbeat vibration from a person in the car (no wind). (a) Output from the sensing device. (b) Result of FFT.
As shown inFig. 6, we checked for the presence of peoplein a camper,where there are various hiding places. The sensing plate was set under the front left-side wheel. One or two persons were hiding in the driver’s seat and the assistant driver’s seat, rear cabin, or roof.With no one in the vehicle, we measured the output signal when there were no people around the car and when there were many people in the vicinity of the car.
calculated is F=0.81.Fig. 8(a) for the wave whenno one is in the car, shows a smaller signal level than that of Fig. 7(a). Furthermore, Fig. 8(b) has no conspicuous spectrum as seen in Fig. 7(b) but a small spectrum extends over a wide range. The value of index F=0.012 in this wave. Index Fwhen a person was in the car is 25 times greater than when no one was in the car. Fig. 9 shows the histogram for index Funder four different wind conditions when a person was in the car. Fig. 10 shows the histogram under the same wind conditions but with no one in the car.
IV. RESULTS OF THE EXPERIMENT A. Robustness Experiments in Case 1 Fig. 7 shows the output signal e(k) and its Fourier transform by FFT when a person was in the car and there was no wind. Fig. 8 shows the resultswhen no one was in the car and there was no wind. Fig. 7(a) shows the periodic wave with the same period as the heartbeat of the person. Fig. 7(b) shows thefundamentaland higher components of theheartbeat. For the signal in Fig. 7, the index
Fig. 8.Car vibration (no one in the car, no wind). (a) Output from the sensing device. (b) Result of FFT.
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camper is greater than that for the sedan. Fig. 11(b) shows the histogram when a person is in the assistantdriver’s seat. The distribution range is almost the same as thatof Fig. 11(a), but the distribution fluctuation range is narrower than in the case of a person sitting in the driver’s seat. This is because the sensing device board is just under the assistant driver’s seat, where the person was sitting. Fig. 11(c) shows the results when two people are sitting in the rear cabin.
Fig. 9. Histogram of index F when a person was in the car. In Fig. 9, when a person was in the car, despite the strength of wind blowing, index F is distributed in the range from 0.20 to 0.40; whereas in Fig. 10 with no one in the car, index F is distributed from 0.015 to 0.21. The frequency in the histogram increases in medium wind of 102 m/min and strong wind of 132 m /min due to the vibration caused by the wind. These figures show the clear difference in the histograms of the index F between the presence and the absence of persons inthecar, despite the wind blowing at different strengths. Therefore, we consider that this system is robust over the wind and can be used outdoors.
Fig. 10. Histogram of index Fwhen no one was in the car. B. Results of Case 2 Fig. 11(a)–(d) shows the histogram of the index when one person or two persons are (a) in the driver’s seat of the camper,(b) in the assistant driver’s seat, (c) in a seat in the back cabin, and (d) on the roof. Fig. 11(e) is the histogram of the index when no one was in the car and no one was walking near the car, and when many people were walking in the vicinity of the car, as shown in the photo in Fig. 11(e). In the histogram in Fig. 11(a), index F is distributed from 0.02 to 0.40, which are lower values compared to that of the sedan-type car. This is because the distance between the sensing device board and the seating position in the
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Fig. 11.Histogram of index for Case 2. (a) Driver’s seat. (b) Assistant driver’s
seat. (c) Seat in rear cabin. (d) On the roof. (e) No person in the car.
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The histogramdistribution of the index ranges from 0.15 to 0.20, which is lowerthan that in Fig. 11(a) and (b). This is due to the greater distance between the sensing device and the seats in the rear cabin. Fig. 11(d) shows the results when a person is on the roof. The distribution is similar than that in Fig. 11(c), but more widely spread because the roof is an unstable location resulting in frequent body movements. Fig. 11(e) shows the results when no one was in the car and there were either weak or strong disturbance vibrations. The distribution is similar to that shown in Fig. 10 when no one was in the sedan-type car. The most frequent distribution is concentrated around F=0.015. From the histograms in Fig. 11(a)–(e), index F decreases in proportion to the distance between the person’s position and the sensing device board. This is because the signal attenuates in proportion to the distance. However, when a person is in the car, even a slight body movement provides a greater value of index .Thus, the distribution is more widely spread than when no one is in the car. Even with the difference in histogram distribution due to the different cars and hiding positions, there was still a clear difference in distribution when people were in the car and when no one was in the car. Index F can be used to discriminate between the presence and nonpresence of people in a car being inspected.
Fig. 12. Cumulative frequency distribution of index F for Case 1 (presence) and Case 2 (non-presence). In this system, we used heartbeat signal. Actually, there are other bio-signals such as breath, but the frequency of the heartbeat and those of breath are different. As shown in Fig. 3, we extract only the band width of the heartbeat frequency by signal processing for the index. In general, humans cannot stop heartbeat consciously regardless of the breathing status. Therefore, breathing and other biosignals whose frequencies are different from that of heartbeat do not affect the judgments of thesystem.Furthermore, even if animals are hidden in the vehicle, this system is capable of detecting their presences if the forces of the heartbeats or the motions of the animals are as strong as human heartbeats. This system can detect if at least one person is hiding or notin the vehicle. So the system does not detect how many persons are hiding in the vehicle. In a real scene at border security, border officers require the drivers and all fellow passengers to get out of the vehicles. In this condition, if the system finds at least one person hiding in the vehicle, the vehicle and the parties including the drivers and all fellow passengers should be investigated more strictly by the border officers. Hence, we consider that role of this system is not to find how many persons are hiding in the vehicles, but to find out atleast one person hiding in the vehicle. Regarding detection time, the X-ray method requires shortertime than this system, but [6] indicates the danger of using the X-ray method for finding illegal immigrants because of their exposure to X-ray. This system needs more detection time than X-ray because the system requires the drivers and all fellow passengers to get out of the vehicles, but compared with the hands-on searching by border officers, the system can reducethe detection time without the dangers such as the exposure to radiation.
V. DISCUSSIONS From the histograms in Figs. 9–11, we considered how to set a threshold Thfor judging the presence or non-presence of a person hiding in the car. Fig. 12 shows the cumulative frequency distribution of index F for Case 1 (presence) and Case2 (non-presence). Both the sedan-type car and the camper show a similar tendency when no one was in the car even under conditions of blowing wind and external ground vibration. The distribution when a person was in the sedan begins to increase fromF=0.12.Here, we decided the threshold so that the cumulative frequency distribution for non-presence would be over 90%. Then, for the camper, the threshold valueTh=0.08,i.e., ifthere might be people hiding in the vehicle, and forthe sedantype car Th=0.12, i.e., if F>0.12, there might be people hiding. For both the sedan and camper, if index F is less than 0.12, there is a 90% probability that no one is hiding inthe vehicle. The results did not perfectly discriminate between the presence and non-presence of a person due to the disturbance from the dynamic pressure of wind and ground vibration. If the inspection was conducted in a closed area with less vibration, the judgment accuracy would be improved. Nonetheless, by identifying the high probability of a concealed person, a more detailed inspection could be carried out and vice versa, which would make the inspection procedure more efficient.
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VI. CONCLUSION This paper describes a novel method for detecting the presence of a person hiding in a car. This pneumatic method uses silicon tubes and highly sensitive pressure sensors to monitor the vibrations from human vital signs. The employment of a low frequency condenser microphone as the pressure sensor provides sufficient sensitivity to detect the signals from human vital signs transmitted to one of the wheels of the car. From the filtered sensing signal, an index using the standard deviation of the signal is presented to discriminate
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between the presence and non-presence of a person in the car. The validity of the proposed method was examined using a sedan-type car and a camper. For both vehicles, when no one was in the car, distribution of the indexwas concentrated in the lowrange. For the sedan, the index when a person was in the car was clearly greater than that when no one was in the car. For the camper with a concealed person, the signal level decreased in proportion to the distance between the position of the person and the sensor location. Furthermore, the body movements of a concealed person enhanced index. REFERENCES [1] M. Zargham, “Obama to tackle immigration reform this year: Report,” REUTERS, Sep. 9, 2009. [Online]. Available: http://www.reuters.com/article/GCABarackObama/idUSTRE5380MU20090409 [2] D. Williams, “The immigrants stuffed into car seats and under bonnets trying to get into Europe,” Daily Mail, Dec. 29, 2007. [Online]. Available: http://www.dailymail.co.uk/news/article-504994/Theimmigrants-stuffed-car-seats-bonnets-tryingEurope.html [3] T. Gaynor, “U.S. border cops nab migrants in fake beer truck,” REUTERS, Nov. 25, 2008. [Online]. Available: http://www.reuters.com/article/domesticNews/idUSTR E4AO9RS20081125 [4] “The border security buildup: True border security requires reforming our broken immigration laws,” National Immigration Forum, 2010. [Online]. Available: http://www.immigrationforum.org/images/uploads/2010 /Border_Security_Fact_Sheet.pdf [5] “Robotic ferret will detect hidden drugs and weapons,” Engineering and Physical Sciences Research Council (U.K.) Jun. 12, 2009. [6] J. Doyle and L. Sorrell, “French ban X-ray scans for illegal immigrants as radiation makes them ‘too dangerous’,” Mail Online, May 14, 2010. [Online]. Available: http://www.dailymail.co.uk/news/article1278565/French-ban-X-ray-scans-illegal-immigrantsradiation-makes-dangerous.html [7] W. Dress, T. Hickerson, and R. Pack, “Enclosed space detection system,” in Proc. IEEE Security Technol., 30th Annu. Int. Carnahan Conf. 2–4, Oct. 1996, pp. 26–28. [8] Y. Kurihara et al., “Measurement of micro vibration of car by piezoelectric ceramics—Detection of bioinformations in the car and application for security,” IEEJ Trans. EIS, vol. 130, no. 5, pp. 844–851, 2010.
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