Plant Doctor: Harnessing Backscatter Radio Sensors for Agriculture

WINLAB Summer Internship 2024
Group Members: Sam-Fone Cheung, Shriya Das, Aly Mustafa, Xiang Meng
Advisor: Aggelos Bletsas

Project Objective

Backscatter radio, or reflection radio, offers a low-cost and low-power alternative to conventional radio sensor networks. This is crucial for modern agriculture which requires continual monitoring of environmental conditions such as soil moisture or temperature. Prior research using capacitance sensors to measure soil moisture has shown promising results using backscatter radio, despite the limited range.

Our group expanded this work to use temperature sensors on a plants which will transmit information using a network of RFID (radio frequency identification) tags. These sensors should be battery-less and low-cost as they will harvest ambient radio frequency (RF) energy.

Over the summer, our team split into two groups to build the transmitter and receiver, ultimately converging.

Weekly Progress

WEEK ONE

​Weekly Presentation

Receiver: Read prior art about ​backscatter radio [1], RFID tags, and ​capacitance sensors [2].

Transmitter: Started learning how to use the TI Launchpad microcontroller, read the documentation, and spoke to Dr. Rich Howard.

WEEK TWO

​Weekly Presentation

Receiver: Used RTL-SDR's to explore software-defined radios (SDR) and tune into local FM stations. Also familiarized ourselves with ​GNURadio and its tutorials.

Transmitter: Learned how to use TI Launchpad MCU MSP-EXP430G2ET. Implemented an adjustable 200kHz-300kHz 50% duty cycle square wave output. Also implemented user input through digital input using the I/O pins. Attempted potentiometer user input, but we did not successfully complete it.

WEEK THREE

​Weekly Presentation

Progress: Continued using GNURadio to implement ​frequency shift keying (FSK) and ​periodograms (maximum likelihood estimators). We also used MATLAB/Octave to compare our results from GNURadio using the SDR.

WEEK FOUR

​Weekly Presentation

Receiver: Explored the accuracy of the receiver while changing the power transmission, frequency, and distance between the SDR and signal generator. Introduced about matched filters and how to ​implement them into the receiver. Despite a frequency measurement error, we implemented logging into GNURadio using a file sink.

Transmitter: Using the TI Launchpad Microcontroller we were able to implement FSK. also created a block diagram to illustrate how both the transmitter and receiver should work together to send information about a plant's temperature.

WEEK FIVE

​Weekly Presentation

Progress: This week, we received three different kinds of thermistors. We were able to implement a backscattered signal that encoded the information from the ADC (using a potentiometer). We are now investigating ways of measuring values from the thermistors, mainly considering a Wheatstone bridge.

We also worked on the receiver, changing from GNURadio to MATLAB. This has so far shown to work extremely well and much better than GNURadio. We can receive the backscattered signal. However, there are still some variances in the received signal we have to account for.

WEEK SIX

​Weekly Presentation

Progress: We moved the bench to on top of an antistatic mat. We also implemented twisted pair cables and an external DC power supply. All of these changes were made to get cleaner signals and avoid accidental antennas. We also made major progress on our work, being able to measure voltage across a Wheatstone bridge (see below) and encode it as a backscattered signal between 100kHz and 200kHz.

We were also able to unite the transceiver-receiver system.

WEEK SEVEN

​Weekly Presentation

Progress:

We fixed a small broken plexiglass chamber that we will use to store plants. Instead of breaking the entire panel, we chose to glue another sheet of plexiglass on top of it to prevent further cracking.

References

(1) A. Bletsas, P. N. Alevizos and G. Vougioukas, "The Art of Signal Processing in Backscatter Radio for μW (or Less) Internet of Things: Intelligent Signal Processing and Backscatter Radio Enabling Batteryless Connectivity," in IEEE Signal Processing Magazine, vol. 35, no. 5, pp. 28-40, Sept. 2018, doi: 10.1109/MSP.2018.2837678.

(2) A. Bletsas, P. N. Alevizos and G. Vougioukas, "The Art of Signal Processing in Backscatter Radio for μW (or Less) Internet of Things: Intelligent Signal Processing and Backscatter Radio Enabling Batteryless Connectivity," in IEEE Signal Processing Magazine, vol. 35, no. 5, pp. 28-40, Sept. 2018, doi: 10.1109/MSP.2018.2837678. keywords: {Backscatter;Frequency shift keying;Loaded antennas;Reflector antennas;Baseband},

(3) J. Kimionis, A. Bletsas and J. N. Sahalos, "Increased Range Bistatic Scatter Radio," in IEEE Transactions on Communications, vol. 62, no. 3, pp. 1091-1104, March 2014, doi: 10.1109/TCOMM.2014.020314.130559. keywords: {Receivers;Modulation;Radiofrequency identification;Radio frequency;Wireless sensor networks;Bit error rate;Signal to noise ratio;Bistatic scatter radio;wireless sensor networks;modulation schemes;software defined radio},