OVERVIEW

The hardware component of Rumino forms the connection between the biochemical reaction and the digital monitoring framework. It converts the wettability-based output of the biosensor into an electrical signal that can be recorded and transmitted remotely. This allows Rumino to function as a continuous detection system for avian influenza RNA in environmental water sources.

The circuit operates as an integrated part of the detection pipeline. When the biochemical reaction restores the capillary wall’s hydrophilicity, the rising liquid completes an electrical circuit. The resulting voltage change is processed by the hardware, interpreted by the microcontroller, and transmitted through a wireless communication module. This design enables real-time monitoring of samples without manual intervention, while maintaining stability and efficiency under field conditions.



CIRCUIT DESIGN

In Rumino’s biosensor, a toehold-mediated strand displacement reaction alters the surface properties of the capillary tube. When the reaction restores the wall’s hydrophilicity, the sample fluid rises and completes an electrical circuit. This transition generates a measurable voltage change, which the hardware detects through its input pins. The electrical response thus acts as the quantifiable counterpart to the biochemical event, bridging molecular and digital domains.


Rumino design figure

Figure 1. Visual diagram of the automated Rumino detector, displaying circuit completion upon target recognition.

The electronic system was developed using an ESP32 microcontroller, chosen for its support for WiFi communication [1]. We created two different versions, one utilizing an analog-to-digital converter (ADC) to take in variable input and another simplified to using a GPIO. These features allow data acquisition and signal transmission to be performed within a single platform.

During early development, a potentiometer was used to simulate the change in conductivity expected from the biosensor. The ESP32 continuously measured voltage through the ADC pin and activated an LED indicator when the signal exceeded a predefined threshold. This test confirmed the firmware’s ability to recognize and respond to the sensor’s signal.

Our final design was powered by a 9V battery, followed by a resistor that was attached to the biosensor. From there, it connected to an ESP32-C6 that processed the voltage change and outputted a signal via WiFi.


Circuit schematic

Figure 2. Circuit schematic of Rumino’s continuous monitoring system showing integration between the 9V power source, resistor, LED indicator, and microcontroller.



FIRMWARE AND SIGNAL TRANSMISSION

The firmware governs two core functions: threshold validation and wireless transmission.

The initial firmware used an ADC pin that continuously updated the voltage reading. If this reading reads above a predefined threshold, an LED is lit and a signal is output via WiFi. The current iteration now uses a GPIO pin instead but still performs the same output function.

Initial testing used Wi-Fi for local data transfer. However, due to the limited range and instability of Wi-Fi in rural areas, the final system implemented LoRa (Long Range) technology. LoRa enables low-power, long-distance data transmission, allowing Rumino sensors to communicate across multiple kilometres without relying on existing infrastructure [3]. This choice ensures continuous, scalable monitoring with minimal maintenance requirements.



SYSTEM OPERATION

The hardware and biosensor function together as a single sensing system:

  1. The biochemical reaction triggers the strand-displacement event and restores capillary wettability.
  2. Fluid movement completes the electrical pathway and generates a measurable voltage change.
  3. The ESP32 reads this voltage change either through a continuous ADC value or a binary value from a GPIO pin.
  4. The result is transmitted via LoRa to a centralized database for further data analysis, visualization, and record keeping.

This sequence allows each biochemical reaction to be directly translated into a digital event, linking molecular detection to real-time electronic output.



FUTURE DEVELOPMENT

Future iterations will integrate the finalized capillary module directly with the circuitry to validate performance under environmental conditions. Testing will focus on response consistency and power efficiency across extended deployments. These developments aim to establish a fully autonomous, network-connected biosensing platform capable of large-scale viral surveillance in agricultural settings.

A functional housing unit will also be developed to protect the circuitry and biochemical components during outdoor deployment. The initial design of this structure has been completed and future iterations will ensure waterproofing, durability against environmental exposure, and accessibility for component replacement or maintenance. Together, these improvements will establish a fully autonomous, field-ready biosensing platform capable of large-scale, continuous surveillance of avian influenza in agricultural water systems [4].



REFERENCES

[1] Espressif Systems. 2024. ESP32-C6 Product Overview. Espressif Systems. https://products.espressif.com

[2] Hassan MU, et al. 2023. Low-cost microcontroller-based biosensing platforms: principles and applications. Biosens Bioelectron. 230:115232. https://doi.org/10.1016/j.bios.2023.115232

[3] Augustin A, Yi J, Clausen T, Townsley WM. 2016. A study of LoRa: long range & low power networks for the Internet of Things. Sensors. 16(9):1466. https://doi.org/10.3390/s16091466

[4] Kumar A, et al. 2021. IoT-based environmental monitoring systems: a review. Environ Monit Assess. 193:801. https://doi.org/10.1007/s10661-021-09488-9