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This article has been accepted for publication in a future issue of this journal,but has not been fully edited.Content may change prior to final publication.Citation information:DOI 10.1109/TMC.2020.3034354.IEEE Transactions on Mobile Computing IEEE TRANSACTIONS ON MOBILE COMPUTING,VOL.XX,NO.XX,2020 tomobiles.The pedestrians only need to use the system for sidewalk can utilize mobile phones'built-in microphones a few minutes to collect the traffic speed information in this and camera to estimate the speed of the automobile.IMU period.SpeedTalker estimates the speed of the automobiles sensors are utilized to compensate the jitters caused by and collects the speeding related information.Traffic speed users.Figure 1 illustrates the application scenario of the information will be uploaded onto the server of the related system.To perform speed detection,the user needs to hold department.With the help of volunteers,data from different the mobile phone in landscape orientation as shown in the regions at different time then can be analyzed for traffic figure,i.e.,the top microphone and the bottom microphone control.The distributions of traffic police and equipment are placed in a left-and-right manner.When the automo- can be optimized and the drivers and pedestrians can be bile passes by,both two microphones record the sound of warned of danger when moving in this area. the automobiles.And the camera records the movement of the automobile.According to the measurements from 1.2 Limitation of Prior Art these two kinds of sensors,SpeedTalker estimates the speed There exist two main approaches to measure the speed of of the automobiles.Specifically,during the process when the automobiles.One approach is to use the fixed devices the automobile is passing by,the sound wave reaches the to measure the speed of the automobiles.The cameras and top and bottom microphones at different time,respectively. coils are traditional fixed devices for speed detection.They According to the time difference of arrivals(TDOA)derived can monitor whether there exist automobiles at two pre-set from acoustic signals obtained by different microphones, locations.If the automobile passes the two corresponding SpeedTalker estimates the candidate trajectories of the auto- locations,the system then records the time interval the mobile as a set of hyperbolas.According to the obtained automobile uses.Thus the speed of the automobile can be frames from the camera,SpeedTalker estimates the vertical easily estimated.However,if the fixed speed measurement distance between the user's position and the automobile's devices are widely deployed to monitor the traffic,the cost trajectory,by referring to the pin-hole model of the camera. is unacceptable.Besides,the drivers can easily figure out Then,the trajectory of the automobile can be determined from the candidates by referring to the unique vertical dis- whether there exist speed measurement devices since their positions are fixed.Moreover,each speed detection camera fance.Combined with the temporal information in acoustic needs its own parameters to estimate the speed of the signals,SpeedTalker is able to estimate the speed of the automobiles.The height,gesture and the field of view(FOV) automobiles.Besides,since the mobile phones are held in determines the detection region of the camera deployed on hands,the jitters may cause rotation and translation of the the traffic pole.This makes the estimation simple but can mobile phones.IMU sensors can be used to compensate the translations and rotations and reduce the errors only work for the specific camera. Another approach to measure the speed of the automo- bile is to use portable devices,such as radar speed gun[4] 1.4 Challenges or lidar[5].Radar speed guns use Doppler Effect to perform speed measurement.They send out a radio signal in a nar- There are three main challenges in our work.The first row beam,then receive the same signal back after it bounces challenge is to propose a passive sensing method to mea- off the target object.If the object is moving,the frequency sure the speed of automobile.Passive sensing means the of the radio waves change.According to the difference detection system does not actively transmit any detecting between the reflected radio waves and transmitted waves, signals,such as ultrasonic and flash light.Active sensing the speed of the object can be calculated.However,there has two limitations for the speeding detection.First,the exist limitations when using these portable devices.First, active signals,e.g.,the electromagnetic wave,can be easily special devices are needed to emit the directional modulated detected by the radar detectors.Second,an ultrasonic wave or flash light actively generated by the mobile phone will electromagnetic waves in certain frequency.This increases be dramatically attenuated when it is transmitted outdoors. the cost of the hardware and prohibits it to be widely used by ordinary people.Second,the electromagnetic wave To address this challenges,we propose a passive sensing emitted by the equipment can be easily detected by radar method to estimate the speed of the automobile,by utilizing two microphones and one camera in the mobile phones. detector in the automobile.Usually this makes them fail to capture the speeding event,since the automobiles may Instead of actively transmitting the modulated signals and receiving the reflected signals,our solution only collects the intentionally slow down when they pass by. acoustic signals and the image frames from the automobiles Therefore,in order to make every pedestrian become in a passive manner.The trajectory of the automobiles can potential speeding inspectors,it is essential to leverage portable daily devices,such as mobile phone,and propose be estimated by the acoustic signals from the two separated microphones and the image frames from the camera.Com- easy-to-use measurements to measure the speed of automo- biles.In fact,by sufficiently using the embedded sensors bined with the timestamp of the trajectory,the speed of the automobiles can be estimated. like the microphones and cameras,we can effectively use the mobile phones to measure the automobiles'speed. The second challenge is to derive the automobile speed from the complicated acoustic signals.The complication of the acoustic signals comes from two aspects.On one hand, 1.3 Our Approach the automobile noises are made up of many parts,including In this paper,we propose SpeedTalker,a mobile phone- the tire noise,engine noise,exhaust noise,wind noise,etc based approach to perform speed detection on automobiles. [6].These noises are mixed not only in time domain but Instead of using special devices,the pedestrian on the also in frequency domain.Therefore,it is hard to separate 1536-1233 (c)2020 IEEE.Personal use is permitted,but republication/redistribution requires IEEE permission.See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to:Nanjing University.Downloaded on December 24,2020 at 09:11:21 UTC from IEEE Xplore.Restrictions apply.1536-1233 (c) 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TMC.2020.3034354, IEEE Transactions on Mobile Computing IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. XX, NO. XX, 2020 2 tomobiles. The pedestrians only need to use the system for a few minutes to collect the traffic speed information in this period. SpeedTalker estimates the speed of the automobiles and collects the speeding related information. Traffic speed information will be uploaded onto the server of the related department. With the help of volunteers, data from different regions at different time then can be analyzed for traffic control. The distributions of traffic police and equipment can be optimized and the drivers and pedestrians can be warned of danger when moving in this area. 1.2 Limitation of Prior Art There exist two main approaches to measure the speed of the automobiles. One approach is to use the fixed devices to measure the speed of the automobiles. The cameras and coils are traditional fixed devices for speed detection. They can monitor whether there exist automobiles at two pre-set locations. If the automobile passes the two corresponding locations, the system then records the time interval the automobile uses. Thus the speed of the automobile can be easily estimated. However, if the fixed speed measurement devices are widely deployed to monitor the traffic, the cost is unacceptable. Besides, the drivers can easily figure out whether there exist speed measurement devices since their positions are fixed. Moreover, each speed detection camera needs its own parameters to estimate the speed of the automobiles. The height, gesture and the field of view(FOV) determines the detection region of the camera deployed on the traffic pole. This makes the estimation simple but can only work for the specific camera. Another approach to measure the speed of the automobile is to use portable devices, such as radar speed gun[4] or lidar[5]. Radar speed guns use Doppler Effect to perform speed measurement. They send out a radio signal in a narrow beam, then receive the same signal back after it bounces off the target object. If the object is moving, the frequency of the radio waves change. According to the difference between the reflected radio waves and transmitted waves, the speed of the object can be calculated. However, there exist limitations when using these portable devices. First, special devices are needed to emit the directional modulated electromagnetic waves in certain frequency. This increases the cost of the hardware and prohibits it to be widely used by ordinary people. Second, the electromagnetic wave emitted by the equipment can be easily detected by radar detector in the automobile. Usually this makes them fail to capture the speeding event, since the automobiles may intentionally slow down when they pass by. Therefore, in order to make every pedestrian become potential speeding inspectors, it is essential to leverage portable daily devices, such as mobile phone, and propose easy-to-use measurements to measure the speed of automobiles. In fact, by sufficiently using the embedded sensors like the microphones and cameras, we can effectively use the mobile phones to measure the automobiles’ speed. 1.3 Our Approach In this paper, we propose SpeedTalker, a mobile phonebased approach to perform speed detection on automobiles. Instead of using special devices, the pedestrian on the sidewalk can utilize mobile phones’ built-in microphones and camera to estimate the speed of the automobile. IMU sensors are utilized to compensate the jitters caused by users. Figure 1 illustrates the application scenario of the system. To perform speed detection, the user needs to hold the mobile phone in landscape orientation as shown in the figure, i.e., the top microphone and the bottom microphone are placed in a left-and-right manner. When the automobile passes by, both two microphones record the sound of the automobiles. And the camera records the movement of the automobile. According to the measurements from these two kinds of sensors, SpeedTalker estimates the speed of the automobiles. Specifically, during the process when the automobile is passing by, the sound wave reaches the top and bottom microphones at different time, respectively. According to the time difference of arrivals (TDOA) derived from acoustic signals obtained by different microphones, SpeedTalker estimates the candidate trajectories of the automobile as a set of hyperbolas. According to the obtained frames from the camera, SpeedTalker estimates the vertical distance between the user’s position and the automobile’s trajectory, by referring to the pin-hole model of the camera. Then, the trajectory of the automobile can be determined from the candidates by referring to the unique vertical distance. Combined with the temporal information in acoustic signals, SpeedTalker is able to estimate the speed of the automobiles. Besides, since the mobile phones are held in hands, the jitters may cause rotation and translation of the mobile phones. IMU sensors can be used to compensate the translations and rotations and reduce the errors. 1.4 Challenges There are three main challenges in our work. The first challenge is to propose a passive sensing method to measure the speed of automobile. Passive sensing means the detection system does not actively transmit any detecting signals, such as ultrasonic and flash light. Active sensing has two limitations for the speeding detection. First, the active signals, e.g., the electromagnetic wave, can be easily detected by the radar detectors. Second, an ultrasonic wave or flash light actively generated by the mobile phone will be dramatically attenuated when it is transmitted outdoors. To address this challenges, we propose a passive sensing method to estimate the speed of the automobile, by utilizing two microphones and one camera in the mobile phones. Instead of actively transmitting the modulated signals and receiving the reflected signals, our solution only collects the acoustic signals and the image frames from the automobiles in a passive manner. The trajectory of the automobiles can be estimated by the acoustic signals from the two separated microphones and the image frames from the camera. Combined with the timestamp of the trajectory, the speed of the automobiles can be estimated. The second challenge is to derive the automobile speed from the complicated acoustic signals. The complication of the acoustic signals comes from two aspects. On one hand, the automobile noises are made up of many parts, including the tire noise, engine noise, exhaust noise, wind noise, etc [6]. These noises are mixed not only in time domain but also in frequency domain. Therefore, it is hard to separate Authorized licensed use limited to: Nanjing University. Downloaded on December 24,2020 at 09:11:21 UTC from IEEE Xplore. Restrictions apply