BYOE: Student-built Versatile Platforms Integrate Solar-powered Microprocessor and Sensors for Chemical Engineering Data Acquisition
Author(s) -
Rachel Monfredo,
David Schinsing,
James Alkins,
T.O. Olsen
Publication year - 2018
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--27996
Subject(s) - microprocessor , data collection , data logger , data acquisition , electrical engineering , photovoltaic system , curriculum , computer science , embedded system , engineering , computer hardware , multimedia , operating system , psychology , pedagogy , statistics , mathematics
Chemical Engineering freshmen at the University of Rochester were tasked with building their own solar-powered microprocessor systems to experience hands-on machine shop training, coupled with exposure to microprocessors, sensors, and data collection in a weekly workshop associated with their Green Energy course. The student-built unit was supported on plywood cut on a table or miter saw, with mounting holes created by a drill press. Students were taught the fundamentals of soldering to attach a power cable to a 2.5W solar panel to provide power to the microprocessor, and a small voltmeter panel to provide real-time voltage readings. Students had a variety of low-powered sensors (i.e. temperature, humidity, sound, light) to choose from. In alignment with the objectives of their Green Energy course curriculum, students, acting individually or on self-selected teams, were challenged to collect data from sensors chosen for creative application to some simulated aspect of green energy production or use—monitoring environmental effects, evaluating a future collection site, or assessing the production process itself. The on-board EEPROM enabled students to store up to 512 sensor readings on the microprocessor for subsequent transfer to a computer. Students were shown how to collect data generated by their solar-powered sensor and perform rudimentary calculations to understand the implications of the data. Forty-seven students presented their findings orally at the end of the semester (seven individuals, and fifteen ‘teams’ of two to four students). The experience exposed students early in the major to the use of sensors, microprocessors, Arduino software, (remote) data acquisition, and the data processing methods useful for their upper level unit operations and process control laboratory courses. Projects included evaluating the economic potential of solar panels or wind turbines installed on campus buildings, monitoring the temperature changes in a recyclable-material parabolic trough, and developing smart agriculture irrigation systems based upon soil moisture readings. Voluntary feedback from thirty-seven students at the end of the course indicated that more than two-thirds of the respondents ‘Agreed or Strongly Agreed’ to queries that the machine shop training was valuable, the hands-on assembly of components was enjoyable, and developing and running experiments was enjoyable. Nearly fifty percent of the class experienced an increased interest in green energy generation. Over ninety percent of the team-based respondents indicated that the opportunity to work on a team was valuable.
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