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title: Mussel-driven voting system

date: 2025-04-23

toc-depth: 2

format: stylish-report-pdf: pdfversion: "2.0" pdfstandard: [A-4f, UA-2] pdftestphase: latest

metadata-files:

  • _actors.yml keywords:
  • voting
  • bioindicator
  • Arduino
  • drinking water

breaks: false


Abstract

TODO: Menna is in charge of this section (not written in section title itself because this section must use the exact name for layout to work)

This project explores the development of a prototype voting system inspired by the natural behavior of freshwater mussels detected and examined by biomonitoring. We have defined the prototype as a "research archetype 3", meaning that the driving force for this project is illustration and demostration purposes.

TODO: come back and write about each step, OUR THREE REQUIRED COMPONENTS,and a conclusion

Copyright and licensing

FIXME: this section cannot be a subsection of Abstract: Abstract must be a standalone section Suggested alternative location is in section "Project Planning and theoretical framework"

To encourage collaboration and stimulate a circular gift economy as introduced by @Mikkelsen2000, this project is copyleft licensed: Code parts are licensed under the GNU Public Licence version 3 or newer, and non-code parts are licensed under the Creative Commons crediting share-alike 4.0.

Introduction - amal

In Poland, several waterworks use biomonitoring systems that rely on freshwater mussels to detect water contamination by measuring and analysing the mussels' gaping behavior [@FerreiraRodriguez2023, p. 3732] Our project aims to simulate a similar system. We will be using Arduino-based hardware and software to do so, and have additionally made a P5 program to simulate night and day, which influences the pseudomussels' behaviour (reaction). We have defined a research question to work around:

How do we simulate and visualise an existing biomonitoring technology for its core purpose

Our simulation is inspired by SYMBIO -- a biomonitoring system -- developed by the company PROTE [@Prote2024]. The SYMBIO system measures the opening angle of the mussel once per second, by using magnets attached to their shells. Superficially, if the mussels gape is closed, it is a bad sign, and if it is open, they are happy and there is no sign of water contamination. There is a wire from each mussel/magnet that connects to a computer. The computer then processes the data in following phases: collect, align, qualify (and analyse) the gaping data, and then -- in our understanding of the process -- treats the now normalized data as votes [@Prote2024]. The threshold we are inspired by for these votes will be defined in a a later paragraph. To be more in depth about the mussels behavior, the gapes are not as simple as just opening/closing their gap to signal happy/unhappy, but is more of a behavioural spectrum. Therefore, if either half of the mussel closes rapidly, or if a mussel remains closed for a long time, it indicates contaminated water. An alarm will then be triggered and further laboratory tests are done [@Nazaruk2016].

To meet this question, we will be using touch and light sensors to represent our virtual models on Arduino -- also referred to as pseudomussels -- and they should mimic somewhere close to real mussel responses such as normal behavior or stressed behavior.

Although our coding logic is inspired by an existing study and implemenation, we wish to delineate ourselves from the real-world criterias that concerns this technology and actual authentic mussel behaviour.

Project Planning and theoretical framework - amal og menna

Use of course curriculum

The beggining of our work process consisted of researching bioindication as a concept and the associated technology. Then we tried to define the purpose of our prototype. Were we interested in the UI/UX design? or perhaps we wanted to prototype a fitting reaction that leads to a dramatic output? Should the prototype be useful or spark reflection? is it merely a state of the art prototype? Concurrently, we learned about the roles artefacts can play in the research process, and used that framework to help define the aim of our project.

The following framework, as introduced in @Wensveen2014, explains how prototypes can serve different purposes depending on the type of knowledge a project aims to produce. A role consists of characteristics, that helps guide the design process and scope of the prototype. There are four roles to choose from, and we chose to work from the perspective of role number three, which views the prototype as a research archetype and tool for critical reflection, in both a physical and abstract sense [@Wensveen2014 p. 8-9].

Next we each did early prototyping and pseudocoding for about three weeks. During this phase, we worked on the sensor setups and on the logic behind the voting mechanism and the possible communication-methods between them.

Our project group has received a brief introduction to APIs during a lecture session, and through additional notes on the topic, that are available on the lecture slides for week 5. From these notes, we learned that API works as a standardized "messenger", that allows different software applications to communicate through defined rules and protocols. API enables seamless integration between the systems.

We decided to use a combination of bluetooth and API, to connect the sensor-data to the voting program. Bluetooth handles the connection between the sensors and our computer/phone, whilst the API is being used to send/retrieve data and trigger an output. A further explanation of this process will be displayed in @sec-user-guide.

Detecting stressful mussel behavior

We wish to expound some of the ways that freshwater mussels behave and how the detection works, in real-life implementation. The thresholds and logic for our sensors and voting-mechanism are mostly based upon the following.

The use of a mussel as biodetector requires distinction between slow-paced valve gaping change (normal), paused valve gaping at the closed position (resting or starved) and rapid valve gaping change (stressed) [@Miller2022 p. 1097; @Robson2006 p. 1200].

Detecting behavioural change to a rapid gaping pace, measurements are needed at a much higher sampling rate than that of the normal gaping pace. E.g. one mussel with normal gaping pace of about 1 minute required a sample rate of 5 seconds to detect its normal pace, and another mussel with normal gaping pace of 3-4 minutes required a sample rate of 0.5 seconds to detect more rapid cycles [@Robson2009 p. 195]. Another measurement of both normal and stressed behaviour, assuming that x-axis is in seconds (not hours as indicated), similarly shows a need for fast sampling rate to detect a normal pace of about 1.2 minutes and a stressed pace faster than the visualized resolution of about 1 second [@FerreiraRodriguez2023 fig. 2].

One concrete approach used in @Robson2009 and @Robson2010 is to collect data at a sample rate of 0.5 seconds, i.e. 2 hZ, and convert that into gape angle per second (CHIGA) to then monitor gape movement instead of gape position.

User Guide (product use) - Tanishka {#sec-user-guide}

TODO

Analysis and Design (physical components) - Menna

The physical setup of our prototype consists of a simple Arduino-based circuit. The following components were used:

ESP 32: Runs the core program that simulates mussel behavior, reads sensor data and outputs voting signals. The logical parts of the ESP32 used in our setup include Bluetooth, a touch sensor input, LEDC (LED control) and a logging system for tracking behavior and communication.

Breadboard: Used to easily connect all components.

Jumper Wires: Connect the ESP32 to the sensors, LED and power/ground rails on the breadboard. One wire is repurposed as a touch sensor, detecting when it is touched and triggering a behavioral change in the simulated mussel.

LED pins: Light up to indicate if the water quality is good or not.

Light Sensor: Detects environmental input and triggers a behavioral change in the simulated mussel.

P5: Used to indicate

FIXME: above paragraph is unfinished

Coding approach - Tanishka

In this paragraph we want to highligt t

FIXME: above paragraph is unfinished

The goal of the system is to replicate the behavioral response of mussels under stress, and translate that into a form of output. Real-world use of mussels as biosensors relies on monitoring their behavior to detect environmental stress. In our project, we simulate this behavior using programmable hardware.

The system is composed of two major components, the sensor ... the mussels behavior and the vote handling system that collects readings from all mussel instances, evaluates their state and triggers output.

*FIXME: in above paragraph, some text is missing at the ellipsis (...).

TODO: not sure this text passage belongs here, as it is the program that is interesting in this section

TODO: here we need to introduce the source we know this from, and to give a little insight into why there is different roles to choose from

TODO

!include components.puml

TODO: if the plantUML is here, we should have a text section that explains it also, and show snippets of our most important/difficult code for each-ish file.

The p5.js code shows a button where, when you press it, it changes from day to night. This change helps the mussel to know how to think? The p5.js code is connected to the sensor system. Here it reads the data from the the p5.js and normalizes it.

FIXME: above paragraph need revisiting: It seems wrong that the sun affects mussels' ability to think, and the P5.js code does not normalize anything -- probably an interesting and valid point was intended, but it is unclear with current phrasing what that is.

TODO

Sensor system

!include Arduino/sensor/sensor.puml

Voting system

The voting system is the client that scans after network to find "is there any beacons here?". The sensor system is our beacon and it works like a lighthouse. It sends signals out to say "im here, i exist". Then Boom! a bluetooth connection is made.

!include Arduino/vote/vote.puml

TODO

Testing - tanishka

TODO

Discussion and reflections- jonas

TODO: discussion about our project e.g. what could have been included, what we could not make SUGGESTION: reflection/discussion about, whether used the guide from role 3 archetype (see course curriculum), and if it was helpful/right/wrong

We have chosen not to use AI in our project. This is mainly for imitation of the current technology and for scope purposes. Although, we have reflected upon how AI could be useful in an expansion of our prototype or hypothetically in an existing system. For an instance, in the future -- when scientists have analysed and interpreted enough data to feed to a MLM -- ai could be used for detecting subtle behavioral changes, that humans would otherwise miss, or spot patterns that further indicates pollution or predicts contamination or enviromental stress.

FIXME: the abbreviations AI and MLM must be introduced before used, and then used consistently (e.g. all caps or no caps)

It could also be put into perspective of surrounding cases, and through datacentric AI, it could be visualized like a weatherforecast on a dashboard. It could be based on patterns like "When x conditions rise, contamination tends to follow."

TODO: in above paragraph, "cases" intents to refer to ANT

This hypothesis would come at the cost of a lot of x, which would be a research question in itself.

FIXME: in above paragraph, "x" should say something about consuming a lot of space and resources

Conclusion - menna

TODO

Bibliography {.appendix}

\begingroup \raggedright ::: {#refs} ::: \endgroup

\appendix

Code

P5.js sketch light.js {.appendix}

Arduino sketch sensor.js {.appendix}

Arduino sketch vote.js {.appendix}