Infrasonic Wildfire Detector

The goal of the project is to create a MESH Network of Infrasonic Wildfire Sensors.

=Problem Definition= Wildfires ravage through the forests and destroy ecosystems and economies, yet still, our best means of detection is by seeing and smelling smoke. The ability to provide a signal to firefighting services when the fire is still small could save countless homes and wilderness areas. In order to modernize this detection process, we propose a device that uses infrasonic detection and signal processing to detect wildfires. Our aim is to set up a mesh network of smart nodes and dumb nodes that can detect infrasound waves (0 – 20 Hz) and communicate this information wirelessly. This technology has the potential to drastically improve our ability to mitigate wildfires by allowing us to detect the problem sooner.

Background
Wildfires ravage through the forests and destroy ecosystems and economies, yet currently, our best means of detection is by seeing and smelling smoke. To modernize this detection process, we propose a device that uses infrasonic detection and signal processing to detect wildfires. There is research precedent suggesting that wildfires emit inaudible low-frequency sound signatures in the infrasonic range. Our aim is to set up a mesh network of smart nodes and dumb nodes that can detect infrasound waves (0 – 20 Hz) and communicate this information wirelessly. This technology has the potential to drastically improve our ability to mitigate wildfires by allowing us to detect the problem sooner. The key features of this prototype are its robust enclosure, cost-effective infrasound sensor, and reliable networking capabilities. The enclosure allows the device to withstand large drops and survive inclement weather and will also use a parachute for potential deployment via aircraft. Meanwhile, the infrasound sensor minimizes the required hardware to detect a fire. Normal infrasonic detection utilizes specialized microphones that cost thousands of dollars, so our goal was to reduce the cost as much as possible by designing a cheaper version.

Deliverables
Our final design for the enclosure was constrained and inspired by our product requirements and our electronics sizing. We needed the device to survive a considerable drop, upwards of 100ft, and the microcontroller and electrical equipment would need safe and secure housing for the journey and wilderness. The final design consists of three separate components that work together to complete all the requirements: the shock absorbers, PVC housing, and parachute.

The shock absorbers were inspired by Naomi Wu’s “TTGO T-Beam Shock Resistant Enclosure” [12]. Her design has more spring-like attachments to the center chip slot, but we decided that our would-be dropped with a parachute, so we wanted more durability and less oscillation, so we came up with a honeycomb pattern. This design created more support in the plane of the shock, but still allowed movement and dampening in the orthogonal axis. The shocks are printed using a flexible TPU 3D printer filament. TPU or thermoplastic polyurethane is known to be specifically flexible and soft, has excellent impact resistance and vibrational dampening, which is why it was chosen for this application. The final design is shown below as a CAD model on the left and 3D printed on the right. The second part of our enclosure was the water-resistant casing, which was created with prefabricated PVC. This made the parts very consistent in shape and sizing and they were easily accessible and cheap. We designed around 2-inch Schedule 40 PVC which is shown below in clear to visualize the internal components but could easily be used in white for the final design. The caps are fabricated to fit onto the PVC and create a water-resistant seal and are press fit in such a way that they require quite a bit of force to take them off. The final piece of the puzzle was the parachute, which was prototyped to be helped by the end caps. The parachute was created out of cotton material to be biodegradable once it has served its purpose and landed the device safely, with the electronic components unharmed. The parachute had a diameter of 33 inches and was attached with 8 supporting ropes. A 3D model of the parachute and assembly can be shown below in Figure 9.

All of this came together for the final enclosure shown in Figure 10 with holes on the top for the microphone and antenna. The chip fits between two shock absorbers, with the PCB attached by the empty pin connections and held snugly between the shocks. As you can see, our entire design, from our chip choice to our fabricated PCB and 3D printed shock absorbers, was able to fit together properly as we had designed it.

To validate the mesh network, we created a tool called, Mesh Visualization Tool (MVT). The tool is designed to listen for broadcast UDP messages sent to the Wi-Fi network by a smart node. It is written in python for quick development and ease of use. Both the computer running the tool and the smart node must be connected to the same Wi-Fi network. The MVT will capture UDP messages and process them. It will strip out the desired information from the JSON message and create plots. These plots show information about the mesh network. It shows the number of nodes connected to the network, the average signal strength between node connections, the battery discharge current, the battery voltage, and very basic visualization of the network. Another feature of the MVT is that it auto-generates an HTML page that is interactive. A user can zoom into plots, save plots, and check/uncheck what information to show. Lastly, the MVT is inside the source development GitLab repository under the mesh visualization tool folder.

We designed the PCB to be a more compact and usable version of our testing breadboard circuit. We wanted it to contain all the analog filters and amplifiers needed to get a clean reading from the microphone using the dev board. We chose to use KiCAD to design this PCB, since it is open-source, and many resources exist for learning to use the software suite. The first iteration of the board was compact and only attached to the T-beam using 3 pins. The compact size made assembly with through-hole components difficult and error-prone, and the 3-pin connection was unstable and positioned poorly so that the PCB would interfere and collide with the shock absorbers. Version 2 of the PCB was changed dramatically to resolve these issues. We expanded the size of the board to spread out the components for ease of assembly and added two full headers to both sides of the board. With these adjustments, the PCB was easier to assemble, and it fits snugly and securely with the rest of the design. These changes are all tracked in a repository in the GitLab. Unfortunately, we were unable to take a valid sensor reading using this PCB, and we were unable to debug it due to time constraints.

Specifications

 * Detect infrasonic sound waves.
 * Creates a mesh network of similar devices to transmit fire status.
 * Has a rugged enclosure capable of surviving drops and impacts, as well as surviving the elements.

Project Learning

 * Fire Infrasound - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929188/
 * LoRa Range and Reliability - https://medium.com/home-wireless/testing-lora-radios-with-the-limesdr-mini-part-2-37fa481217ff
 * LoRa Mesh Example - https://nootropicdesign.com/projectlab/2018/10/20/lora-mesh-networking/
 * Simple LoRa Library - https://github.com/sandeepmistry/arduino-LoRa
 * RadioHead Mesh Networking Library - https://www.airspayce.com/mikem/arduino/RadioHead/
 * Shock Absorber Inspiration - https://www.fabbaloo.com/blog/2020/6/15/design-of-the-week-ttgo-t-beam-shock-resistant-enclosure
 * KiCAD Tutorials - https://learn.sparkfun.com/tutorials/beginners-guide-to-kicad
 * KiCAD Resources - https://www.kicad.org/help/learning-resources/

Final Design
In Progress.













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