Infrasound in wildfire

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Duration: Spring 2018 - Fall 2018
Team Name Team infrasound
Team Members:
  • Braydon Campbell
  • Mitch Patterson
  • Stephen Weeks
  • Yuhang You
  • Project Overview[edit]


    • It has recently been found that large wildfires generate infrasonic waves that can be detected by infrasound observatories.
    • Advances in measurement technology has made it possible for measuring devices that are both portables and inexpensive.

    Problem Statement[edit]

    • Design a deployable self sustaining package that can continuously measure infrasonic wave data at 2kHz/s and transmit that data wirelessly.
    • The package must be able to operate for 3 months without relying on existing power infrastructure.

    Deliverables & Specifications[edit]

    • 2-3 months of continuous power
    • Battery powered with possible solar generation and power switching technology
    • Wireless access to measure and upload data within 6 hours
    • Lora to cell tower or Zigby to cell tower
    • Possible chain network to increase range from package to communication infrastructure
    • GPS time sync stored with data
    • Prototype must cost under $1000
    • Portable package for one person to carry
    • Error correction on transmitted data
    • Possible command signals from control cente


    Currently as a group we have pinpointed our design constraints, what we want the system to do and what we believe will be an engineering solution for the project at hand. We have found that the major issue within our project will be power consumption, since we will not be relying on any major infrastructure to power our system we need to be able to run it for a couple of months. We have also found that for the communication we have to piggyback on the cell towers to connect to the internet. This will require setting up a 3G/4G/LTE network for the system. We currently are researching what this will take to communicate. In the near future we are wanting to learn how to pull data from the sensor using only an RP-3B and write/send that data in a readable format. This will involve setting up a daisy chained network, using Xbee or Zigbee, to send the data long distance. Our future goals is to set up and have testing of the communication network with the sensor data collection incorporated. We will continue to try to find solutions to the power issue and how we will power the entire design system. Future plans will look into green energy, DC-DC conversion, and restrictions of 3G/4G/LTE network communication.


    Recent pricing for Infrasound Design[edit]

    Recent budget.png
  • 3x Raspberry Pi 3 B $36.33 = $108.99
  • 3x SD Cards 8 GB $6.98 = $20.94
  • 2x ADS1015 12-bit ADC $12.55 = $25.10
  • 2x MCP3008-I/P 10-bit ADC $3.90 = $7.80
  • Total Cost = $162.83 Cost
  • Possible future design cost[edit]

  • Xbee Pro 60mW Wire Antenna – Series 1 (802.15.4) = $37.95 (1 mile/60mW/250kbps)
  • Xbee Cellular 3G = $89.00
  • Digi Xbee-PRO S2C Zigbee = $20.25 (2 miles/63mW(+18dBm)/250kbps)
  • Digi Xbee-PRO 900HP = $39.00 (9 miles-10Kbs/4 miles-200 klbs)
  • Digi Xbee-PRO XSC S3B = $42.00 (9 miles-dipole antenna/ 28 miles-high-gain antenna/250 mW/10 Kbps – 20 Kbps)
  • 900 MHz dipole antenna = $20.00 1W
  • W1010 2.3 GHz dipole antenna = $2.266 for 5
  • Raspberry Pi3G – 4G/LTE Base Shield V2 = $39.00
  • Quectel EC25 Mini PCIe $G/LTE Module = $89.00 - $66.00
  • Design[edit]

    Using devices[edit]

    Infrasound sensor
    The IFS-5000 Seismically Decoupled Infrasound Sensor is the result of years of research, development and testing of infrasound sensors by leading scientists in the field of infrasound acoustics . The IFS-5000 series is available in both analog and digital versions and provide excellent relative seismic sensitivity, thermal sensitivity and and sensor-to-sensor amplitude and phase matching . The IFS-5000 sensors have been designed and tested to provide reliable and durable performance for prolonged field installations . The attributes along with low initial and recurring costs allow array installations in cases where such applications were cost prohibitive in the past .
    raspberry pi
    Raspberry Pi as a world’s most inexpensive and powerful Single Board Computer. This is world’s cheapest microprocessor unit specially built for learner and makers. We can easily learn how software and hardware work together without been worrying about damage/cost. We can buy Raspberry Pi board with just somewhere around 35$. The cost of Pi allows newbies to celebrate mistakes and learn most out of it. Also Raspberry Pi has a huge community and plenty of online resources which make learning smooth.
    MCP 3008 ADC
    The MCP3008 10-bit Analog-to-Digital Converter (ADC) combines high performance and low power consumption in a small package, making it ideal for embedded control applications. The MCP3008 features a successive approximation register (SAR) architecture and an industry-standard SPI serial interface, allowing 10-bit ADC capability to be added to any PIC® microcontroller. The MCP3008 features 200k samples/second, 8 input channels, low power consumption (5nA typical standby, 425µA typical active), and is available in 16-pin PDIP and SOIC packages. Applications for the MCP3008 include data acquisition, instrumentation and measurement, multi-channel data loggers, industrial PCs, motor control, robotics, industrial automation, smart sensors, portable instrumentation and home medical appliances.

    Current design[edit]

    Flow diagram
    Block diagram
    The block diagram shown presents our current plan for data communication from the infrasonic sensor back to the control center.The infrasonic measurement device will stream its differential voltage measurements to the raspberry pi from which the pi will digitize and communicate that data through an attached LoRa module. Additional raspberry pis will be placed in between the measurement device and 4G communication infrastructure to form a connected daisy chain to increase the operational distance of the infrasonic device.The final raspberry pi will communicate the measured data through a local cell tower via a 3G/4G shield module. The upload data will be stored back at the control center.


    Top Right Photo credit: Stacy Isenbarger

    Future Plan[edit]

    Next steps for measurement system[edit]

    • Pull data in from Raspberry Pi at 2kSamples/s
    • Check to see if the ADC channels are parallel or is there a lag in sampling
    • Save data from ADC to the SD card
    • Run data logging scheme using hardware interrupt based on RPi CPU speed
    • Integrate GPS hat and test for lag
    • Select proper file type for data storage
    • Determine the final file size based on data file type

    Next steps for point to point communication[edit]

    • Select a Point to Point communication module
    • Need to obtain file size
    • Priority on module selection
    • Sufficient rate of transfer for file size like Power consumption,range and price
    • Looking at Zigbee and Xbee family of modules
    • Set up the Point to Point module to communicate with the pi
    • Select controller for communication nodes
    • Communicate/transmit data between controllers

    Next steps for 3G/4G communication[edit]

    • Select a 3G/4G module and network plan
    • Priority on module selection
    • Sufficient rate of transfer for file size
    • Communicate with 3G/4G module
    • Transfer Data via 3G/4G
    • Set up a server to receive data

    Team Information[edit]

    Biography Discipline
    Mitch Patternson

    He is studying Electrical Engineering and is hoping to graduate in the spring of 2019. His interests are backpacking and cross-country skiing. The emphasis of his studies have been microelectronics and signals which is what attracted him to this project.

    Electrical Engineering.
    Stephen Weeks

    His interest in sub-discipline is embedded systems, digital system design, hardware design, and signals processing. He has experience in op-amp design, digital design, embedded programming, and side projects including Arduino and FPGA design flow as well as working experience with digital signal processing. He has a strong interest in power regulation, communications systems, bio-wearable devices and smart devices, including self-learning electronics.

    Electrical Engineering
    Braydon Campbell
    Senior desgin.jpg

    Thorough experience in various disciplines that include digital design, embedded programming in both FPGAs and microcontrollers, microelectronic design, and statistical analysis. Career experience includes test development engineering intern at On Semiconductor. There he statistically correlated image capture boards that are used to test photo image capturing silicon devices, resolved wafer fallout issues, and established cost-efficient test protocols.

    Electrical Engineering
    Yuhang You

    He is a transfer and senior student, and he is trying to apply a UI master degree.

    Electrical Engineering

    Documentation Archive[edit]

    Gannt chart.png

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