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Lesson Ideas: Remote Sensing

Learning Activities

  • A Lesson On Heat Absorption Using Data from Temperature Sensors

    Thinking about the materials science experiment on the FunCube satellite, I wanted to find a way to explore an aspect of the materials science experiment on heat absorption in the classroom without the FunCube orbital constraints and in a more concrete way for my 8th grade students to understand. 

     

    I think a simple but relevant application of that idea is the issue of leaving children and pets in cars during the summer. This is a serious and relevant issue that students hear about quite frequently on the news. I will ask my students what they know about how the color of the car might affect the temperature inside the car on a hot summer day. Many have heard that black cars are hotter than light colored cars.  I’ll then ask them to design an experiment that might test their hypotheses. A valid experiment they might come up with is simply to measure the temperature in different colored cars. I will then remind them that we want to measure and collect temperature data over time and it might not be a good idea to ask several car owners to give up their cars for a few days.  I'll also remind them of the need to use adequate controls during a science experiment and that cars might be difficult to control for a number of reasons. 

     

    Another way we might approach this problem, especially if we're trying to simulate what’s happening in space, as with the FunCube materials science experiment, is to use remote sensors and APRS to collect the data.

       

    For this experiment, I'll have students in the tech class build four aluminum cubes. The design goal is to build cubes with thermo isolated surfaces so each one can be monitored independently of the others.  A suggestion will be to build a CubeSat sized frame (10cm x 10cm x 10cm) out of hardwood and the side panels out of aluminum sheet.  Attach the side panels to the wood frame using #4 wood screws so the panels do not make contact at the corners.  We’ll paint one cube black, one white, we'll polished one and brush the other.  We'll attach sensors, one to the center of each side plate, and one suspended in the middle of the cube.  We’ll then place the cubes outside in direct sunlight away from heat reflective surfaces such as concrete or buildings.  We'll orient the cubes so each cube's X axis is oriented differently - some N/S others E/W.  This will make it fun for students to determine the orientation of each cube by analyzing the varying temperature data.  Theoretically, the eastward pointing panel should be hottest in the morning and the westward facing panel in the afternoon.  An IO/TNC board will need to be built similar to the one used in the buoy only with additional sensor connections. 5 surfaces (not the bottom) will be monitored plus the sensor suspended in the middle of the cube will make a total of 6 sensors per cube or 24 total sensors for 4 cubes. The IO/TNC board will communicate via the 2m buoy radio with the APRS network. 


    I think this will be a relatively easy to execute project with many ham radio application opportunities and with opportunities for data collection and analysis.  This will get the students thinking about different ways to use remote sensing and will help students better understand what is going on in the abstract realm of CubeSats.

    from Tom Maxwell, AE5QB

  • How does the cell phone or processor in the phone translate your voice into a series of 1’s and 0’s?

    More than a few of my students have expressed an interest in this question. This provides an opportunity for a fundamental investigation of analog to digital conversion.   I’ll take a snapshot of a student’s voice with the Parallax USB Oscilloscope and use a slice of it, or use a sample waveform drawn from scratch.  Take the sample slice and put it onto a grid where I can either put it on the screen or on paper for handouts. Students will analyze the waveform, sampling every so many lines and give each sample a numerical value according to the Y value from right to left. Next students will convert the values to binary. Sampling will not be high due to the amount of data, but enough to learn the process. Then the students will be asked to convert the binary in reverse to see if they can duplicate the wave or signal from the original conversation. This would be a simulation of a conversation with the processors converting the analog data (voice) into a digital signal.  The result will no doubt give us an opportunity to discuss the improtance of sampling rate as well as digital signal processing.

     

    from Bill Richardson, N5VEI