In-Pavement Wireless Sensor Network for Vehicle Classification Ravneet Bajwa, Ram Rajagopal, Pravin Varaiya and Robert Kavaler IPSN’11 Outline • • • • • • • Motivation Introduction Description Communication Protocol Design Experiment Setup Performance Conclusion & Future Work Outline • • • • • • • Motivation Introduction Description Communication Protocol Design Experiment Setup Performance Conclusion & Future Work Motivation • Intrusive technologies – Piezoelectric sensors, inductive loops – High installation and maintenance costs • Non-intrusive technologies – Infrared, video imaging – Sensitive to traffic and weather condition • Propose an alternative system base on a WSN that is both cost effective and insensitive to environmental conditions • • • • • • • Motivation Introduction Description Communication Protocol Design Experiment Setup Performance Conclusion & Future Work Problem Statement • Cars, buses, three-axle single unit trucks, and five-axle single trailer trucks • A vehicle travels in a traffic lane at some varying speed and we wish to count the number of axles and the spacing between each axle in an accurate manner Proposed WSN System • Vibration sensor (accelerometer) embedded in the road – Calculate the axle spacings • Vehicle detection sensor (magnetometers) – Report the arrival and departure times of a vehicle • Access point (AP) – Send commands to sensors – Log the incoming data • First in-pavement, easy to deploy, WSN based system for counting axles and axle spacing Outline • • • • • • • Motivation Introduction Description Communication Protocol Design Experiment Setup Performance Conclusion & Future Work Wireless Vehicle Detection Sensor • Measures the changes in magnetic field to infer the local presence of a vehicle • Synchronous Nanopower Protocol(SNP), a TDMA based protocol – Last 10 years with a single 7200 mAhr battery • Given the arrival times tai and taj at the two sensors i and j, the speed v will be v = dij / |taj – tai| • Estimate the length(L) of the vehicle L = v(tdj - taj) Wireless Vibration Sensor • Sample the analog output of an accelerometer and transmit the data via a radio • Sample fast enough to capture the transient vibrations • Sensor needs to be insensitive to the vehicles traveling in the neighboring lanes • Insensitive to the truck engine and environmental noise • Sensor resolution target is 500 ug • Bandwidth 50Hz • Sampling frequency 512 Hz( > 5 times Nyquist Frequency) – Power consumption increases for higher sampling rates Selecting an accelerometer • SD1221-005 has higher sensitivity and lower noise density • However, it consumes more than 20 times the current than MS9002.D and has to be operated at higher voltage • Both devices achieved the aimed minimum resolution of 500 ug – Select MS9002.D due to its low operating voltage and low current consumption Filters for mitigating sound noise • Accelerometer is sensitive to sound • MS9002.D behaves like a microphone under the device’s bandwidth • 3rd order low-pass filter with cutoff frequency of 50 Hz is sufficiently aggressive to filter out most of the sound in the audible spectrum Casing • Sound isolation • Protect the electronics from rain water and oil spill on the road Circuit Description • 2.5 V supply voltage • Amplifier with gain 10 • The gain of 10 reduces the range of the accelerometer to ≈±225mg • This is necessary in order to ensure that the quantization noise from the ADC is less than the noise from the accelerometer – Otherwise, the resolution of the system will be limited by ADC noise • The reduced range is still sufficient – For heavy trucks ± 200 mg Outlin • • • • • • • Motivation Introduction Description Communication Protocol Design Experiment Setup Performance Conclusion & Future Work Communication Protocol Design • MAC Layer – TDMA based – Time is divided into multiple frames with each frames about 125 ms long – Each frame is further divided into 64 time slots – Slot 0 is used by AP to send clock synchronization information and other commands to the sensors – AP assigns every node unique time slots and a node ID to communicate with it. Application Layer • Sync Application – AP sends sync packets on a periodic basis – Sensor node listens to sync packets every 125 ms – When the clock converges to steady state, then is listens for a sync packet only once in 30 s – Sync application is also used to send commands – Set Mode, Reset, Set Timeslot, Set RF, Download Firmware, Set ID Application Layer • Accelerometer Application – Idle Mode: accelerometer and related circuitry are turned off by disabling the voltage regulator • Once every 30 s, the microcontroller and the transceiver wake up and acquire the sync packet Application Layer – Raw Data Mode: microcontroller wake up every 1/512 s, and samples the analog output from accelerometer • 32 samples at a sampling freq. 512Hz, and each sample containing 12 bits of information • In every frame(125ms) we accumulate 96 bytes of information to transmit • To have a reasonable packet size, we fragment the data in two parts, 48 bytes each, and transmit it using two different time slots 62.5ms apart Application Layer • Download Firmware Application – Reprogram the entire flash memory of a sensor node over the air – AP transmits new code repeatedly and the node updating its code in small pieces – Only the data that do not overwrite the current running program are updated by the node Axle Detection(ADET) Algorithm Axle Detection(ADET) Algorithm • Using data from 4 trucks at different speeds, we observed the bandwidth of the energy signal and empirically defined by M(v) = 900/v • Low-pass filter is optional • Minimum time separation ζ(v) was chosen by assuming that the axles are at least 6ft apart Wide Lane ADET Algorithm • Wander movement in a lane • Combining vibration readings from multiple sensors • Delay Di = di / v Outline • • • • • • • Motivation Introduction Description Communication Protocol Design Experiment Setup Performance Conclusion & Future Work Experiment Setup • 4 vibration sensors and 4 vehicle detection sensor were installed on California Highway I-680 • Vehicles come from Sunol Weigh Station • Slow down at weigh station – Easy to collect ground truth • Data from 53 different trucks, ranging from pickup trucks to 5-axle commercial trucks Installation • Boring a 4-inch diameter hole approximately 2.25 inches deep • Installed on a road in less than 20 minutes • Installation of a small sensor is much cheaper and convenient than installing special material pavements required for piezoelectric sensors Deployment Challenges • Packet Drops – Drop rate was low(1%) retransmit packets with a delay of 1 packet drop rate is almost 0 • Packet 1, 2, 1, 2 • Vehicle Wander – use Wide Lane ADET algorithm • Sensor failure – Sensor k did not work – Vibration data was available from 3 sensors Outline • • • • • • • Motivation Introduction Description Communication Protocol Design Experiment Setup Performance Conclusion & Future Work Vibration Sensor Performance • Noise with no vehicle in vicinity – 414 ug RMS • Truck was parked on top of the sensor with engine were on vs. truck blew its horn – 7% vs. 4% • With a heavy truck traveled in the closed lane – Sensor did not register any noticeable peaks Axle Count • Error difference between the ground truth axle count and the estimated axle count • By combining the measurements from all sensors, the algorithm always gives the correct axle count • Error results form the wander movement Axle Spacing • Left: for tandem axle • Middle: pick up trucks, small two axle commercial trucks • Right: axles of trailers Outline • • • • • • • Motivation Introduction Description Communication Protocol Design Experiment Setup Performance Conclusion & Future Work Conclusion • A novel algorithm that estimates the axle count and spacing from pavement acceleration was designed and tested on the collected data • ADET is simple enough to implement a sensor node with limited processing power • Majorities of the existing technologies are wired solutions • Both the sensors and the AP are powered by batteries and consume much less power than other technologies • The installation procedure and sensors themselves are much cheaper • There is minimal maintenance compared to other technologies Future Work • Find an optimal arrangement of sensors in order to minimize the number of sensors deployed • Reduce the amount of data transmitted • Reduce the sensor power consumption