Ultralow Power Sensor Package for Early Warning of Wildland Fires (2020)

Introduction: The wildfires in California and throughout the western USA have been devastating especially over the past two years causing loss of lives, incredible property losses, and the bankruptcy of a giant utility (Pacific Gas and Electric) with over $50B of debt. It is not just California that suffers from such fiery disasters, there are devastating fires throughout Australia, Siberia, and around the world. The premise is that early detection could provide avenues for emergency response and the limitation of lost lives and property damage. Current methods to detect these fires include deployment of local forest rangers, satellite optical and thermal IR imaging, and public education. None of these are quite adequate as satellites may not have resolution required for small startup fires and a ranger’s view can be obscured by weather. Since fires produce emissions that can provide an atmospheric signature including gases and particles as well as thermal plumes, the hypothesis is that detection of these “fire” signatures with sensitivity could provide early warning. The case can be made for sensing atmospheric emissions in that carbon monoxide (CO) is produced in high concentrations especially in smoldering fires and has been used for early warning of fires in coal mines for half a century or more. Figure 1 (top left) illustrates the use of CO to map the impact of 2018 fires in California through IR imaging up to 18,000 feet of the atmosphere[1] at 200 ppb and lower concentrations. Clearly CO is related to the fire activity but how early can a fire be sensed? What confounding variables will be present, such as T, P, RH, local activity, and natural variability of the chemical composition of the air at low levels? Is CO the best emission to monitor or are better variables available? The answer to these questions is key to the design and deployment of an early warning system based on measurement of atmospheric emissions! Methods The approach has two objectives in this early research: 1) to understand the emission signatures from fires as recorded by low cost environmental sensors, and 2) to evaluate the feasibility of a practical early warning fire detector based on emission signatures. Clearly, we know CO is one possible emission but also other variables include particles, CO2, O 3 , NO 2 and other gases (VOCs and SO 2 ). A monitoring system was designed, made from low cost COTS (commercially off the shelf) sensors and electronics that could be used to gather field data. The system would be complete with sensor hardware, communication alternatives, and computational capabilities. SPEC Sensors [2] and KWJ Engineering’s [3] electronic hardware and algorithms were selected to partner with commercial particulate and environmental (T, P, RH) sensors[4] in order to build a system that could address objective 1. Evaluation of actual field data could then be used to achieve objective 2; as it is clear that a deployed sensor system must have low cost, near zero power, and long-term stability as well as be free from interfering signals. Results The construction of the integrated monitoring and analysis system node (figure 1, top right) was completed, and included SPEC Sensors for CO, NO 2 , O 3 ; Alphasense SO 2 sensor, Sensirion SPD30 (NDIR) CO 2 and SPS30 particulate sensor as well as wind speed and direction, a 4.4 A∙h LiPo Battery, two x 3.4 W adjustable solar panels, and a USB connection for power/communications. The data from a deployed CO sensor taken by a third party is illustrated in figure 1 (bottom). The SPEC CO sensor was only calibrated once at the start of the deployment and the data from it are plotted vs an EPA reference instrument that is co-located. The correlation over months support the hypothesis that an ultra-low-cost tiny screen-printed electrochemical sensor can possess the stability that will be needed in a practical application scenario. There is significant agreement between a frequently calibrated instrument with 100 ppb resolution reading once per hour and the hourly average of a real-time sensor at 0-2000 ppb! Concluding Remarks: A current deployment model suggests that a city like Santa Rosa, CA with billions in assets and 200,000 lives could be protected with about 2,500 sensors over 100 square miles. While the current prototype node would be too expensive for thousands of locations, once a model of “fire starts” is obtained, a reduced complexity “smart node” can be envisioned with fewer sensors (e.g. CO, O 3 , NO 2 , and particles) that could be built for &lt;$100. A cost of $2.5M to protect billions is a good start. Future improvements and higher volumes for mass manufactured sensors will make such a system practical. Our current data and model support a rationale for further investment in this fire warning technology through deployed low-cost and low power sensors. [1] Greicius, Tony. Carbon Monoxide from California Wildfires Drifts East., NASA, 14 Aug. 2018, https://www.nasa.gov/feature/jpl/carbon-monoxide-from-california-wildfires-drifts-east. [2] www.Spec-sensors.com [3] www.KWJengineering.com [4] www.sensirion.com Acknowledgement: support from EPA Contract Number 68HERD19C0020; KWJ Engineering Inc., and JST Consulting LLC. Figure 1