Team:Dundee/Project/SoftwareTheory

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           <h2><b>Insight to the Mop-topus and Toxi-Tweet</b> </h2>
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           <h2><b>Moptopus - Hardware</b> </h2>
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          <h2>Aims:</h2>
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           <p>Using mathematical tools to allow us to predict the limiting factors in the production of PP1 and its mopping applications. Working alongside the biologists to produce models which are relevant and can predict what is expected to happen during the synthetic engineering of the mop and detection bacteria.</p>
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            <img id="image-6" src="https://static.igem.org/mediawiki/2013/thumb/d/d2/MoptopusBanner.jpg/800px-MoptopusBanner.jpg" style="width:100%;height:300px">
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          <p>The Moptopus is an electronic environmental sensor,  developed to collect and relay real-time data from water reservoirs. The device could be placed in a water body to measure:</p>
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          <ul style="padding-left:15px">
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            <li>Light Levels</li>
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            <li>Temperature</li>
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            <li>Humidity</li>
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            <li>pH level of the water</li>
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            <li>Dissolved oxygen level</li>
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            <li>An on-board camera</li>
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          </ul>
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            <p>The Moptopus device could  be used in conjunction with the biological microcystin detection system that we attempted to develop. Presence of microcystin in water would trigger the production of Green Fluorescence Protein (GFP) by the <i>E. coli</i> detector. The Moptopus has been designed to quantify the amount of GFP produced by the excitation of GFP  via a blue light and the capture of fluorescence emitted via a highly green light sensitive photodiode.</p>
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                <img id="image-6" src="https://static.igem.org/mediawiki/2013/thumb/c/c1/Moptopus_prototype.jpg/800px-Moptopus_prototype.jpg" style="width:100%">
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<p><strong>Figure 1:</strong> Prototype design of the Moptopus</p>
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            <h2>Important Guidelines</h2>
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            <p>To ensure adequate monitoring of water bodies and the presence of toxic algal blooms, guidelines developed by relevant agencies (such as World Health Organization and United States Environmental Protection Agency among other) were analysed. <br><br>
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            Keeping the guidelines below in mind, readings taken remotely by the moptopus can be used to aid in the rapid identification of water bodies susceptible to algal blooms and more specifically to toxic algal blooms.<br><br>
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            <ul style=”padding-left:15px”>
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            <li>Blooms are most expected to occur in late summer/early autumn and are most common in water bodies which are eutrophic or hypereutrophicWHO.  Temperatures around 32oC correspond to the greatest growth rate. <sup>AJOL</sup></li>
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            <li>Water temperatures between 15oC and 30oC  and pH levels between 6 and 9,with adequate levels of nutrients, are required for the persistence of an algal bloom <sup>WHO</sup></li>
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            <li>The optimal temperature for toxin production in cyanobacteria is between 20oC and 25oC<sup>.WHO</sup> Greatest toxicity has been recorded at temperatures of approximately 20oC.<sup>AJOL</sup></li>
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            <li>Water temperatures greater than 25oC have proven advantageous for the growth of harmful algae when competing with non-harmful algae which grow faster than other non-harmful algae (specifically shown for <i>Microcystis Aeruginosa</i>). This advantage increases the likelihood of harmful algal blooms above this temperature.<sup>EPA</sup></li>
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            <li>The optimal growth rate of Microcystis Aeruginosa occurs at light levels between 3600 and 18000 lux. Light levels greater than 18000 lux result in a rapid decline in the growth rate. <sup>AJOL</sup>, White light intensity over 40 microeinsteins m-2 s-1 (equivalent to approx. 2160 lux) results in an increase in toxicity of cyanobacteria.<sup>WHO</sup></li>
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            <li>In terms of growth rate, However, in terms of toxicity the greatest cyanobacteria growth rate does not directly correspond to greatest toxicity.
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            <li>Hypoxia (a decrease in oxygen content in the water body) is often caused by algal blooms. This occurs when the organic matter of cyanobacteria decomposes and reduces oxygen dissolved in the water.<sup>NOAA</sup></li>
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            <h2>Sources </h2>
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            <p>
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            WHO: <a href="http://www.who.int/water_sanitation_health/dwq/chemicals/cyanobactoxins.pdf">http://www.who.int/water_sanitation_health/dwq/chemicals/cyanobactoxins.pdf</a><br>
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            EPA: <a href="http://www2.epa.gov/sites/production/files/documents/climatehabs.pdf">http://www2.epa.gov/sites/production/files/documents/climatehabs.pdf<br></a>
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            AJOL: <a href="http://www.ajol.info/index.php/ajb/article/download/14935/61493</">http://www.ajol.info/index.php/ajb/article/download/14935/61493</a><br>
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            NOAA: <a href="http://www.noaa.gov/features/earthobs_0508/algal.html">http://www.noaa.gov/features/earthobs_0508/algal.html</a><br>
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          <h2>Development of Moptopus:</h2>
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    <h2> Platforms and Communication</h2>
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          <p> The current method for detecting toxic levels of microcystin is to take a sample of water from different regions of the site being investigated and then to carry out high performance liquid chromatography (HPLC). This process currently takes approximately 24 hours, we hope to reduce this to a more suitable 1 hour.</p><br>
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          <p>Assuming the cyanobacteria undergo binary fission and grow unbounded we were able to determine how the problem increases over 24 hours in comparison to 1 hour detection.
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In order to use the sensors and detectors mentioned above, the Moptopus was created using two main control boards: the Raspberry Pi (Model B) and an Arduino (Mega 2560).</p> <br><br>
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          where MC(t) is the number of microcystin at time t b0 is the initial number of algae</p><br>
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          <p>The ratio for time t=24:1 is 8.4million:1. To put this into perspective this is the same as the height of the empire state building compared with the length of 7 E.coli bacterium. This model therefore emphasises that the 1 hour detection period is much more efficient and worth pursuing.</p>
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            <img id="image-6" src="https://static.igem.org/mediawiki/2013/0/08/Dundee-Arduino.png" style="height:200px">
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            <img id="image-6" src="https://static.igem.org/mediawiki/2013/thumb/7/7c/Dundee-Raspberry.png/497px-Dundee-Raspberry.png" style="height:200px">
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<br><br>A Raspberry Pi (<a href="http://www.raspberrypi.org">http://www.raspberrypi.org</a>) is a low cost, low power computer system which can fit in the palm of your hand. It has no onboard storage and instead runs various distributions of linux via insert-able SD Cards.  The Raspberry Pi was chosen for our project due to its low cost and power requirements and the ability to easily program on it. <br>
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We implemented a Raspberry Pi as the control centre of the Moptopus. It carries out some information processing and controls the flow of information to any users. It is able to connect to the internet and allow a user to control the Moptopus while in operation. Our Raspberry Pi runs the Rasbian operating system (<a href="http://www.raspbian.org">http://www.raspbian.org</a>). . <br><br>
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An Arduino (<a href="http://www.arduino.cc">http://www.arduino.cc</a>) is a cheap microcontroller, able to control and read voltages from metal pins which are connected to it. The digital and analogue input/output pins on our Arduino Mega have been used to control modules such as an LCD screen, light sensors, temperature sensors and the dissolved oxygen and pH sensors. . <br><br>
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        <h2>The Toxi-Tweet System:</h2>
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A number of methods of communication between the Raspberry Pi, Arduino and internet have been used. The Raspberry Pi is able to request data from a specific sensor by use of some of its own onboard pins. The configuration we used is called an I2C bus which is a serial communication method requiring just two pins on the Raspberry Pi and Arduino to communicate. Using this I2C bus, the Raspberry Pi asks the Arduino to take a specific measurement using one of the sensors. . <br>
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        <p>We considered different limiting factors of our mop bacteria.  The factor discussed in this section is the maximum number of PP1 which can fit either on the surface of B.subtilis, or in the periplasm of E.coli.  We considered the volumes of the bacteria and PP1 and used a cube approximation that took into account volume which was wasted, in packing, by the spherical shape of the protein. For this model we assumed there were no other surface proteins and protein production was not limited by any factors.</p><br>
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The Arduino is also equipped with an Ethernet shield allowing it to be connected to the Ethernet port aboard the Raspberry Pi. This allows the streaming of data from the Arduino to the Pi.
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Finally, the Raspberry Pi has an added USB Wi-Fi device for connection to a local wireless network. This allows the Raspberry Pi to be communicated with and remotely logged into.<br><br>
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        <p>Calculations show the maximum number of PP1 which can fit on the surface of B.subtilis is between 60 000 -70 000. From the average we can calculate that the number of bacterial mops required to clean a toxic level of microcystin in a litre of water is 1.40x1010.</p><br>
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        <p>In E.coli, PP1 which would bind microcystin is free-flowing in the periplasm. The volume of the periplasm is much greater than the surface of B.subtilis. Therefore E.coli has the capacitive potential to be a more efficient mop. The maximum number of PP1 which can be packed into the periplasm is between 150 000 -200 000. Consequently, less bacterial mops are required to clean the same level of microcystin: 0.52x1010.</p><br>
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        <p>When we have accurate numbers from the biology team on how many PP1 are attached to the surface or in the periplasm for B.subtilis and E.coli respectively, we can compare these numbers and compute the efficiency of our PP1 expressing bacteria.</p><br>
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        <h2>Progress and Future Plans </h2><br>
 
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        <p>An Ordinary Differential Equation (ODE) uses a function f(t) to describe how the output changes as a result of changing the input dx(t)/dt. For example how PP1 concentration changes with time in a single cell. In order to model transcription and translation of PP1 we used a system of ODEs , which is more than one ODE where the outputs are coupled.</p><br>
 
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        <p>We used law of mass action to obtain a system of ODEs to describe the production of mRNA to PP1. mRNA and PP1 are coupled in the sense we need mRNA before we can produce any PP1. Also, the mRNA is not used up. We also took into consideration the degradation rates of mRNA and PP1 which are denoted as .</p><br>
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<h2>Sensors</h2>
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        <ul>
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</div>
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        <li>k1 – rate mRNA production - 4.98x10-9</li>
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        <li>kd1 – rate mRNA degradation – 1x10-2</li>
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        <li>k2 – rate PP1 production – 4x10-2</li>
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        <li>kd2 – rate PP1 degradation – 4x10-4</li>
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        <br> <p><i><b>Figure 1.</b> How mRNA and PP1 are produced over 20 minute cell division time. Note scaling on PP1 compared to mRNA.</i></p><br>
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<Strong>Light</strong><br><br>
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The sensors used to detect light were simple and cheap Light Dependent Resistors (LDRs). The specific LDRs used were Excelitas Tech – VT90N1. These light sensors were implemented in the moptopus in order to monitor the intensity of light falling on the lake on a day to day basis. <br></div>
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          <p><br><i>Figure 2. A steady state is when the quantities describing a system are independent of time – they reach an equilibrium i.e dx/dt = 0. The steady state for (mRNA, PP1) is (0.04, 0.04) corresponding to a non-dimensionalised system. This plot demonstrates that during a 20 minute cell division period mRNA reaches the steady state but PP1 does not.</i></p><br>
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<Strong>Temperature and Humidity</strong><br><br>
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        </div>
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A combined temperature and humidity sensor was implemented to sense at the surface of the water with high accuracy. The sensor used was a SHT71, which provided temperature and humidity measurements to 2 decimal places. According to the datasheet for the sensor, the typical error present in these measurements was ±0.4% for temperature and ±3% for humidity.</div>
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        <br><p><i>Figure 3. This plot shows that given a time longer than cell division time both the mRNA and PP1 eventually reach their steady states.</i></p><br>
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<Strong>pH</strong><br><br>
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        </div>
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The pH of the fresh water is of significance when determining whether an algal bloom is likely to break out and also has implications on the toxicity of the algal bloom. The pH sensor used was a silver/silver chloride probe produced by Atlas Scientific. This was accompanied by a data stamp via which communication with the Arduino system was possible.<br></div>
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<Strong>Dissolved Oxygen</strong><br><br>
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The dissolved oxygen concentration of a water body is significant in determining whether algal bacteria can grow in an explosive manner. Furthermore, it can also help detect the breakdown of cyanobacteria after an algal bloom. Thus, a dissolved oxygen sensor and accompanying stamp by Atlas Scientific was implemented and built into the Moptopus.<br></div>
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            <img id="image-6" src="https://static.igem.org/mediawiki/2013/thumb/9/95/DissolvedOxygen.png/600px-DissolvedOxygen.png" style="height:100px">
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<Strong>Onboard camera</strong><br><br>
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The Moptopus was fitted with an onboard camera in order to view its surroundings. The camera selected was a Logitech C310 HD and this was mounted on the top of the Moptopus. By allowing a user to view the surroundings of the Moptopus, the conditions of the lake at any time can be viewed. The potential for such viewings would be to allow the monitoring of aspects such as the amount of waste rubbish which has been discarded into the water reservoir. Such waste can provide cyanobacteria with nutrients required for growth. Furthermore, should an algal bloom occur viewing of the site could allow for a monitoring of the growth pattern of the algae and in such a fashion be informative to potential action to reduce the likelihood of future algal blooms.<br></div>
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            <img id="image-6" src="https://static.igem.org/mediawiki/2013/thumb/e/e3/Microscope2IconBackground.png/600px-Microscope2IconBackground.png" style="height:100px">
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<div class="span12"><h2> Testing the Moptopus in Clatto</h2>
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<p>A prototype of the Moptopus was finalised and tested in Clatto reservoir, just north of Dundee. This test demonstrated the viability of deploying such a system and displayed its operational use. There were several testing stages in the course of development, some of which are shown below.<br><br>
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Initially, all of the hardware and software components of the Moptopus were developed and tested in the lab with no exposure to water. This initial, somewhat disorganised, setup was required to ensure that all of the hardware parts functioned as required and could be implemented together.<br><br>
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<p>The next step in development was the packaging of the Moptopus into a waterproof enclosure built to protect the electronics from any water damage. This involved a great deal of space management in dealing with the number of wires which were required to connect the device to its parts. We selected a lunch box  as the optimal enclosure, because of its size and watertight seal. </p>
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<p>After testing the Moptopus in an environment free from the danger of water, a local test of the waterproof enclosure was required. Naturally, the most obvious progression was to take the Moptopus for a bath!</p><br><br>
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<p><strong>Figure 2:</strong> Moptopus circuitry inside enclosure.</p>
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<center><img src="https://static.igem.org/mediawiki/2013/thumb/f/f1/Moptopus_3.JPG/800px-Moptopus_3.JPG" width="100%"></img</center>
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<p><strong>Figure 3:</strong> Deployment and testing in aquatic environment.</p>
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<Br><Br><p>Finally, the Moptopus was ready to be deployed in the Clatto reservoir and to be tested in its intended environment. Data from the Moptopus was streamed back to a laptop by the shore and measurements from the array of sensors were taken.</p><br><br>
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<center><img src="https://static.igem.org/mediawiki/2013/a/ac/Moptopus.jpg" width="100%"></img</center>
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<p><strong>Figure 4:</strong> Deployment in Clatto Reservoir.</p>
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<center><img src="https://static.igem.org/mediawiki/2013/e/e6/Moptopus2.jpg" width="100%"></img</center>
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<p><strong>Figure 5:</strong> Uploading data by the dock.</p>
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<h2> Moptopus in Action!</h2></div><br><br><br><br>
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Latest revision as of 17:12, 27 October 2013

iGEM Dundee 2013 · ToxiMop

The Moptopus is an electronic environmental sensor, developed to collect and relay real-time data from water reservoirs. The device could be placed in a water body to measure:

  • Light Levels
  • Temperature
  • Humidity
  • pH level of the water
  • Dissolved oxygen level
  • An on-board camera

The Moptopus device could be used in conjunction with the biological microcystin detection system that we attempted to develop. Presence of microcystin in water would trigger the production of Green Fluorescence Protein (GFP) by the E. coli detector. The Moptopus has been designed to quantify the amount of GFP produced by the excitation of GFP via a blue light and the capture of fluorescence emitted via a highly green light sensitive photodiode.

Figure 1: Prototype design of the Moptopus

Important Guidelines

To ensure adequate monitoring of water bodies and the presence of toxic algal blooms, guidelines developed by relevant agencies (such as World Health Organization and United States Environmental Protection Agency among other) were analysed.

Keeping the guidelines below in mind, readings taken remotely by the moptopus can be used to aid in the rapid identification of water bodies susceptible to algal blooms and more specifically to toxic algal blooms.

  • Blooms are most expected to occur in late summer/early autumn and are most common in water bodies which are eutrophic or hypereutrophicWHO. Temperatures around 32oC correspond to the greatest growth rate. AJOL
  • Water temperatures between 15oC and 30oC and pH levels between 6 and 9,with adequate levels of nutrients, are required for the persistence of an algal bloom WHO
  • The optimal temperature for toxin production in cyanobacteria is between 20oC and 25oC.WHO Greatest toxicity has been recorded at temperatures of approximately 20oC.AJOL
  • Water temperatures greater than 25oC have proven advantageous for the growth of harmful algae when competing with non-harmful algae which grow faster than other non-harmful algae (specifically shown for Microcystis Aeruginosa). This advantage increases the likelihood of harmful algal blooms above this temperature.EPA
  • The optimal growth rate of Microcystis Aeruginosa occurs at light levels between 3600 and 18000 lux. Light levels greater than 18000 lux result in a rapid decline in the growth rate. AJOL, White light intensity over 40 microeinsteins m-2 s-1 (equivalent to approx. 2160 lux) results in an increase in toxicity of cyanobacteria.WHO
  • In terms of growth rate, However, in terms of toxicity the greatest cyanobacteria growth rate does not directly correspond to greatest toxicity.
  • Hypoxia (a decrease in oxygen content in the water body) is often caused by algal blooms. This occurs when the organic matter of cyanobacteria decomposes and reduces oxygen dissolved in the water.NOAA

Sources

WHO: http://www.who.int/water_sanitation_health/dwq/chemicals/cyanobactoxins.pdf
EPA: http://www2.epa.gov/sites/production/files/documents/climatehabs.pdf
AJOL: http://www.ajol.info/index.php/ajb/article/download/14935/61493
NOAA: http://www.noaa.gov/features/earthobs_0508/algal.html

Platforms and Communication

In order to use the sensors and detectors mentioned above, the Moptopus was created using two main control boards: the Raspberry Pi (Model B) and an Arduino (Mega 2560).







A Raspberry Pi (http://www.raspberrypi.org) is a low cost, low power computer system which can fit in the palm of your hand. It has no onboard storage and instead runs various distributions of linux via insert-able SD Cards. The Raspberry Pi was chosen for our project due to its low cost and power requirements and the ability to easily program on it.
We implemented a Raspberry Pi as the control centre of the Moptopus. It carries out some information processing and controls the flow of information to any users. It is able to connect to the internet and allow a user to control the Moptopus while in operation. Our Raspberry Pi runs the Rasbian operating system (http://www.raspbian.org). .

An Arduino (http://www.arduino.cc) is a cheap microcontroller, able to control and read voltages from metal pins which are connected to it. The digital and analogue input/output pins on our Arduino Mega have been used to control modules such as an LCD screen, light sensors, temperature sensors and the dissolved oxygen and pH sensors. .

A number of methods of communication between the Raspberry Pi, Arduino and internet have been used. The Raspberry Pi is able to request data from a specific sensor by use of some of its own onboard pins. The configuration we used is called an I2C bus which is a serial communication method requiring just two pins on the Raspberry Pi and Arduino to communicate. Using this I2C bus, the Raspberry Pi asks the Arduino to take a specific measurement using one of the sensors. .
The Arduino is also equipped with an Ethernet shield allowing it to be connected to the Ethernet port aboard the Raspberry Pi. This allows the streaming of data from the Arduino to the Pi. Finally, the Raspberry Pi has an added USB Wi-Fi device for connection to a local wireless network. This allows the Raspberry Pi to be communicated with and remotely logged into.

Sensors

Light

The sensors used to detect light were simple and cheap Light Dependent Resistors (LDRs). The specific LDRs used were Excelitas Tech – VT90N1. These light sensors were implemented in the moptopus in order to monitor the intensity of light falling on the lake on a day to day basis.


Temperature and Humidity

A combined temperature and humidity sensor was implemented to sense at the surface of the water with high accuracy. The sensor used was a SHT71, which provided temperature and humidity measurements to 2 decimal places. According to the datasheet for the sensor, the typical error present in these measurements was ±0.4% for temperature and ±3% for humidity.


pH

The pH of the fresh water is of significance when determining whether an algal bloom is likely to break out and also has implications on the toxicity of the algal bloom. The pH sensor used was a silver/silver chloride probe produced by Atlas Scientific. This was accompanied by a data stamp via which communication with the Arduino system was possible.


Dissolved Oxygen

The dissolved oxygen concentration of a water body is significant in determining whether algal bacteria can grow in an explosive manner. Furthermore, it can also help detect the breakdown of cyanobacteria after an algal bloom. Thus, a dissolved oxygen sensor and accompanying stamp by Atlas Scientific was implemented and built into the Moptopus.


Onboard camera

The Moptopus was fitted with an onboard camera in order to view its surroundings. The camera selected was a Logitech C310 HD and this was mounted on the top of the Moptopus. By allowing a user to view the surroundings of the Moptopus, the conditions of the lake at any time can be viewed. The potential for such viewings would be to allow the monitoring of aspects such as the amount of waste rubbish which has been discarded into the water reservoir. Such waste can provide cyanobacteria with nutrients required for growth. Furthermore, should an algal bloom occur viewing of the site could allow for a monitoring of the growth pattern of the algae and in such a fashion be informative to potential action to reduce the likelihood of future algal blooms.


Testing the Moptopus in Clatto

A prototype of the Moptopus was finalised and tested in Clatto reservoir, just north of Dundee. This test demonstrated the viability of deploying such a system and displayed its operational use. There were several testing stages in the course of development, some of which are shown below.

Initially, all of the hardware and software components of the Moptopus were developed and tested in the lab with no exposure to water. This initial, somewhat disorganised, setup was required to ensure that all of the hardware parts functioned as required and could be implemented together.

The next step in development was the packaging of the Moptopus into a waterproof enclosure built to protect the electronics from any water damage. This involved a great deal of space management in dealing with the number of wires which were required to connect the device to its parts. We selected a lunch box as the optimal enclosure, because of its size and watertight seal.

After testing the Moptopus in an environment free from the danger of water, a local test of the waterproof enclosure was required. Naturally, the most obvious progression was to take the Moptopus for a bath!



Figure 2: Moptopus circuitry inside enclosure.

Figure 3: Deployment and testing in aquatic environment.



Finally, the Moptopus was ready to be deployed in the Clatto reservoir and to be tested in its intended environment. Data from the Moptopus was streamed back to a laptop by the shore and measurements from the array of sensors were taken.



Figure 4: Deployment in Clatto Reservoir.

Figure 5: Uploading data by the dock.

Moptopus in Action!