| | Category | EGCH | P07 | Determining light-source location using Machine Learning and |
| | Solar Cells |
| | Abstract | BACKGROUND |
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| | The current generated by a single solar cell is highly sensitive to the |
| | angle, the intensity, and the color of the light incident upon it. In this |
| | project, I want to investigate whether this property can be utilized to |
| | design an “intelligent” solar panel that can “predict” the position of a |
| | light source incident upon it (and, possibly, also its distance and its |
| | color). A potential application of such an “intelligent” panel would be as |
| | a solar tracker, facilitating the determination of the position of the Sun |
| | and feeding positional data to the tilting control unit. |
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| | HYPOTHESIS |
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| | My hypothesis is that if an array of solar cells can be properly |
| | designed, then the electrical response of each cell in the array will be |
| | different for different locations of an incandescent source of light |
| | pointed towards it. These electrical response values can then be read |
| | by a computer using proper sensors. The latter data, along with the |
| | positional information of the light source can then be used to train a |
| | supervised Machine Learning algorithm. The generated model can then |
| | be used to predict the position of any incandescent light source |
| | pointed at the array. |
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| | EXPERIMENT: |
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| | 1.Use Ruthenizer-535 synthetic dye to create dye-sensitized solar cells |
| | (DSSCs). I choose to use DSSCs because I can produce them at home. |
| | Moreover, DSSCs are environmentally friendly, cheaper to |
| | manufacture than their silicon-based counterparts, and work in low-light |
| | conditions. |
| | |
| | 2.Use 6-9 such DSSCs to create an array so that each cell responds |
| | differently to an incandescent light source pointed at the array. |
| | |
| | 3.Connect each cell to the ADC input of an Arduino. |
| | |
| | 4.Read the voltage-drop on a 560-ohm resistor connected to each cell |
| | using an Arduino program. |
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| | 5.Record the position of the light source in a 2-dimensional / 3- |
| | dimensional unit. |
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| | 6.Use MatLab programs to train a Machine Learning algorithm and |
| | generate a model for light-source-position prediction. |
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