Design of an Artificial Intelligence-Supported Temperature-Controlled Arduino uno Ph Meter for Student Laboratories
Özet
This study introduces the design and implementation of an artificial intelligence (AI) supported, temperature-controlled pH meter tailored for educational laboratories. The device uses Arduino microcontrollers and open-source technologies to offer a cost-effective alternative to commercial pH meters, which are often prohibitively expensive. Integrating AI tools enhances the system's accuracy, usability, and adaptability, enabling real-time data analysis, and temperature-controlled. The device was rigorously tested against standard buffer solutions, natural water samples, and food products, yielding results comparable to commercial pH meters with acceptable experimental errors and high reliability. Moreover, the system promotes experiential learning by simplifying complex measurement processes and fostering student engagement with AI and microcontroller programming. Despite certain limitations, such as dependency on regular calibration and reduced accuracy compared to high-end commercial devices, the developed system demonstrates potential as an accessible, customizable, and educationally enriching tool. Future improvements aim to expand its functionalities to support additional parameters, further advancing its applicability in scientific education.
Referanslar
Abrahams, I., & Millar, R. (2008). Does practical work really work? A study of the effectiveness of practical work as a teaching and learning method in school science. International journal of science education, 30(14), 1945-1969.
Dochshanov, A. M., & Tramonti, M. (2023). The Design and Implementation of an Open-source Programmable Bot for Educational Purposes. Digital Presentation and Preservation of Cultural and Scientific Heritage, 13, 289-298.
Guzmán-Fernández, M., Zambrano de la Torre, M., Ortega-Sigala, J., Guzmán-Valdivia, C., Galvan-Tejeda, J. I., Crúz-Domínguez, O., ... & Durán-Muñoz, H. A. (2021). Arduino: A Novel Solution to the Problem of High-Cost Experimental Equipment in Higher Education. Experimental Techniques, 1-13.
Haefner, N., Wincent, J., Parida, V., & Gassmann, O. (2021). Artificial intelligence and innovation management: A review, framework, and research agenda✰. Technological Forecasting and Social Change, 162, 120392.
Hofstein, A., & Lunetta, V. N. (2004). The laboratory in science education: Foundations for the twenty‐first century. Science education, 88(1), 28-54.
Huang, X., & Qiao, C. (2024). Enhancing computational thinking skills through artificial intelligence education at a STEAM high school. Science & Education, 33(2), 383-403.
Irawan, Y., Febriani, A., Wahyuni, R., & Devis, Y. (2021). Water quality measurement and filtering tools using Arduino Uno, PH sensor, and TDS meter sensor. Journal of Robotics and Control (JRC), 2(5), 357-362.
Ismailov, A. S., & Jo‘Rayev, Z. B. (2022). Study of Arduino microcontroller board. Science and Education, 3(3), 172–179.
Jawad, H. M., Ahmed, S. S., Jassim, M. M., & Korniichuk, B. (2024, April). Design a pH Meter Using Arduino. In 2024, 35th Conference of Open Innovations Association (FRUCT) (pp. 307–318). IEEE.
Jin, H., Qin, Y., Pan, S., Alam, A. U., Dong, S., Ghosh, R., & Deen, M. J. (2018). An open-source, low-cost wireless potentiometric instrument for pH determination experiments.
Julian, J., Wahyuni, F., & Ulhaq, F. D. (2023). Reliability Analysis of pH Measurement on TLC4502 with E201C Electrodes based on ATmega328P Microcontroller: Approach to Analysis of Variation with ANOVA. ELKHA: Jurnal Teknik Elektro, 15(1), 32-40.
Kang, S. J., Yeo, H. W., & Yoon, J. (2019). Applying Chemistry Knowledge to Code, Construct, and Demonstrate an Arduino–Carbon Dioxide Fountain. Journal of Chemical Education, 96(2), 313-316.
Kibirige, I., & Tsamago, H. E. (2019). Grade 10 learners’ science conceptual development using computer simulations. Eurasia Journal of Mathematics, Science and Technology Education, 15(7), em1717.
Kitcharoen, P., Howimanporn, S., & Chookaew, S. (2023). Review Process to Investigate Trends of Using Arduino to Enhance AI Study. In 31st International Conference on Computers in Education, ICCE (pp. 448–455).
Kolb, D. (1984). Experiential learning: Experience as the source of learning and development.New Jersey: Prentice-Hall.
Linn, M. C., Bell, P., & Davis, E. A. (2004). Specific design principles: Elaborating the scaffolded knowledge integration framework. In M. Linn, E. A. Davis & P. Bell (Eds.), Internet environments for science education (pp. 315- 341). Mahwah, NJ: Lawrence Erlbaum Associates.
Morchid, A., El Alaoui, M., El Alami, R., Qjidaa, H., El Khadiri, K., & Mehdaoui, Y. (2021, January). Design and realization of a fire safety system for controlling and monitoring a siren using Arduino Uno. In International Conference on Digital Technologies and Applications (pp. 433-445). Cham: Springer International Publishing.
Mukaka MM (2012). Statistics Corner: A guide to the appropriate use of correlation coefficient in medical research. Malawi Med J 24:69–71
Oh, P. K., & Kang, S. J. (2021). Integrating Artificial Intelligence to Chemistry Experiment: Carbon Dioxide Fountain. Journal of Chemical Education, 98(7), 2376-2380.
Orellana, J. L. R., & Chang, O. (2021). Artificial intelligence-controlled pole balancing using an Arduino board. Revista Tecnológica-ESPOL, 33(2), 189-204.
Papadopoulos, N. J., & Jannakoudakis, A. (2016). A chemical instrumentation course on microcontrollers and op amps. Construction of a pH meter. Journal of Chemical Education, 93(7), 1323-1325.
Polat, M. Y., Beyaz, A., & Çilingir, İ. (2020). Development of a Low-Cost pH Meter for Liquid Chemical Fertilizers. Turkish Journal of Agriculture-Food Science and Technology, 8(4), 840-846.
Qutieshat, A., Aouididi, R., & Arfaoui, R. (2019). Design and construction of a low-cost Arduino-based pH sensor for the visually impaired using universal pH paper.
Sadraey, M. H. (2024). Microcontroller Boards. In Unmanned Aircraft Design: A Review of Fundamentals (pp. 151–169). Cham: Springer International Publishing.
Sanusi, I. T., Agbo, F. J., Dada, O. A., Yunusa, A. A., Aruleba, K. D., Obaido, G., ... & Oyelere, S. S. (2024). Stakeholders’ insights on artificial intelligence education: Perspectives of teachers, students, and policymakers. Computers and Education Open, 7, 100212.
Schweingruber, H. A., Hilton, M. L., & Singer, S. R. (Eds.). (2006). America's lab report: Investigations in high school science. National Academies Press.
Skoog, D. A., Holler, F. J., & Crouch, S. R. (2018). Principles of instrumental analysis (7th ed.). Cengage Learning.
Skoog, D. A., West, D. M., Holler, F. J., & Crouch, S. R. (2021). Fundamentals of Analytical Chemistry (10th ed.). Cengage Learning.
Soni, G. (2022, February). Implementation of LM35 interfacing of a temperature sensor with Arduino using LabVIEW 2015. In 2022 IEEE Delhi Section Conference (DELCON) (pp. 1–3). IEEE.
Soong, R., Agmata, K., Doyle, T., Jenne, A., Adamo, T., & Simpson, A. (2018). Combining the maker movement with accessibility needs in an undergraduate laboratory: a cost-effective multipurpose text-to-speech Universal Chemistry Sensor Hub (MUCSH) for Students with Disabilities.
Tay, K. S., & Eng, J. L. (2024). Integrating Maker Education into the Research Project of Undergraduate Chemistry Program: Low-Cost Arduino-Based 3D Printed Autotitrator. Journal of Chemical Education.
Wu, Y., Chen, Y., & Cheng, Y. (2024). Building an Arduino-Based Open-Source Programmable Multichannel Syringe Pump: A Useful Tool for Fluid Delivery in Microfluidics and Flow Chemistry. Journal of Chemical Education, 101(5), 1951-1958.
Yang, W., Hu, X., Yeter, I. H., Su, J., Yang, Y., & Lee, J. C. K. (2024). Artificial intelligence education for young children: A case study of technology‐enhanced embodied learning. Journal of Computer Assisted Learning, 40(2), 465-477.
Yue, M., Jong, M. S. Y., & Dai, Y. (2022). Pedagogical design of K-12 artificial intelligence education: A systematic review. Sustainability, 14(23), 15620.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). A systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1-27.
Referanslar
Abrahams, I., & Millar, R. (2008). Does practical work really work? A study of the effectiveness of practical work as a teaching and learning method in school science. International journal of science education, 30(14), 1945-1969.
Dochshanov, A. M., & Tramonti, M. (2023). The Design and Implementation of an Open-source Programmable Bot for Educational Purposes. Digital Presentation and Preservation of Cultural and Scientific Heritage, 13, 289-298.
Guzmán-Fernández, M., Zambrano de la Torre, M., Ortega-Sigala, J., Guzmán-Valdivia, C., Galvan-Tejeda, J. I., Crúz-Domínguez, O., ... & Durán-Muñoz, H. A. (2021). Arduino: A Novel Solution to the Problem of High-Cost Experimental Equipment in Higher Education. Experimental Techniques, 1-13.
Haefner, N., Wincent, J., Parida, V., & Gassmann, O. (2021). Artificial intelligence and innovation management: A review, framework, and research agenda✰. Technological Forecasting and Social Change, 162, 120392.
Hofstein, A., & Lunetta, V. N. (2004). The laboratory in science education: Foundations for the twenty‐first century. Science education, 88(1), 28-54.
Huang, X., & Qiao, C. (2024). Enhancing computational thinking skills through artificial intelligence education at a STEAM high school. Science & Education, 33(2), 383-403.
Irawan, Y., Febriani, A., Wahyuni, R., & Devis, Y. (2021). Water quality measurement and filtering tools using Arduino Uno, PH sensor, and TDS meter sensor. Journal of Robotics and Control (JRC), 2(5), 357-362.
Ismailov, A. S., & Jo‘Rayev, Z. B. (2022). Study of Arduino microcontroller board. Science and Education, 3(3), 172–179.
Jawad, H. M., Ahmed, S. S., Jassim, M. M., & Korniichuk, B. (2024, April). Design a pH Meter Using Arduino. In 2024, 35th Conference of Open Innovations Association (FRUCT) (pp. 307–318). IEEE.
Jin, H., Qin, Y., Pan, S., Alam, A. U., Dong, S., Ghosh, R., & Deen, M. J. (2018). An open-source, low-cost wireless potentiometric instrument for pH determination experiments.
Julian, J., Wahyuni, F., & Ulhaq, F. D. (2023). Reliability Analysis of pH Measurement on TLC4502 with E201C Electrodes based on ATmega328P Microcontroller: Approach to Analysis of Variation with ANOVA. ELKHA: Jurnal Teknik Elektro, 15(1), 32-40.
Kang, S. J., Yeo, H. W., & Yoon, J. (2019). Applying Chemistry Knowledge to Code, Construct, and Demonstrate an Arduino–Carbon Dioxide Fountain. Journal of Chemical Education, 96(2), 313-316.
Kibirige, I., & Tsamago, H. E. (2019). Grade 10 learners’ science conceptual development using computer simulations. Eurasia Journal of Mathematics, Science and Technology Education, 15(7), em1717.
Kitcharoen, P., Howimanporn, S., & Chookaew, S. (2023). Review Process to Investigate Trends of Using Arduino to Enhance AI Study. In 31st International Conference on Computers in Education, ICCE (pp. 448–455).
Kolb, D. (1984). Experiential learning: Experience as the source of learning and development.New Jersey: Prentice-Hall.
Linn, M. C., Bell, P., & Davis, E. A. (2004). Specific design principles: Elaborating the scaffolded knowledge integration framework. In M. Linn, E. A. Davis & P. Bell (Eds.), Internet environments for science education (pp. 315- 341). Mahwah, NJ: Lawrence Erlbaum Associates.
Morchid, A., El Alaoui, M., El Alami, R., Qjidaa, H., El Khadiri, K., & Mehdaoui, Y. (2021, January). Design and realization of a fire safety system for controlling and monitoring a siren using Arduino Uno. In International Conference on Digital Technologies and Applications (pp. 433-445). Cham: Springer International Publishing.
Mukaka MM (2012). Statistics Corner: A guide to the appropriate use of correlation coefficient in medical research. Malawi Med J 24:69–71
Oh, P. K., & Kang, S. J. (2021). Integrating Artificial Intelligence to Chemistry Experiment: Carbon Dioxide Fountain. Journal of Chemical Education, 98(7), 2376-2380.
Orellana, J. L. R., & Chang, O. (2021). Artificial intelligence-controlled pole balancing using an Arduino board. Revista Tecnológica-ESPOL, 33(2), 189-204.
Papadopoulos, N. J., & Jannakoudakis, A. (2016). A chemical instrumentation course on microcontrollers and op amps. Construction of a pH meter. Journal of Chemical Education, 93(7), 1323-1325.
Polat, M. Y., Beyaz, A., & Çilingir, İ. (2020). Development of a Low-Cost pH Meter for Liquid Chemical Fertilizers. Turkish Journal of Agriculture-Food Science and Technology, 8(4), 840-846.
Qutieshat, A., Aouididi, R., & Arfaoui, R. (2019). Design and construction of a low-cost Arduino-based pH sensor for the visually impaired using universal pH paper.
Sadraey, M. H. (2024). Microcontroller Boards. In Unmanned Aircraft Design: A Review of Fundamentals (pp. 151–169). Cham: Springer International Publishing.
Sanusi, I. T., Agbo, F. J., Dada, O. A., Yunusa, A. A., Aruleba, K. D., Obaido, G., ... & Oyelere, S. S. (2024). Stakeholders’ insights on artificial intelligence education: Perspectives of teachers, students, and policymakers. Computers and Education Open, 7, 100212.
Schweingruber, H. A., Hilton, M. L., & Singer, S. R. (Eds.). (2006). America's lab report: Investigations in high school science. National Academies Press.
Skoog, D. A., Holler, F. J., & Crouch, S. R. (2018). Principles of instrumental analysis (7th ed.). Cengage Learning.
Skoog, D. A., West, D. M., Holler, F. J., & Crouch, S. R. (2021). Fundamentals of Analytical Chemistry (10th ed.). Cengage Learning.
Soni, G. (2022, February). Implementation of LM35 interfacing of a temperature sensor with Arduino using LabVIEW 2015. In 2022 IEEE Delhi Section Conference (DELCON) (pp. 1–3). IEEE.
Soong, R., Agmata, K., Doyle, T., Jenne, A., Adamo, T., & Simpson, A. (2018). Combining the maker movement with accessibility needs in an undergraduate laboratory: a cost-effective multipurpose text-to-speech Universal Chemistry Sensor Hub (MUCSH) for Students with Disabilities.
Tay, K. S., & Eng, J. L. (2024). Integrating Maker Education into the Research Project of Undergraduate Chemistry Program: Low-Cost Arduino-Based 3D Printed Autotitrator. Journal of Chemical Education.
Wu, Y., Chen, Y., & Cheng, Y. (2024). Building an Arduino-Based Open-Source Programmable Multichannel Syringe Pump: A Useful Tool for Fluid Delivery in Microfluidics and Flow Chemistry. Journal of Chemical Education, 101(5), 1951-1958.
Yang, W., Hu, X., Yeter, I. H., Su, J., Yang, Y., & Lee, J. C. K. (2024). Artificial intelligence education for young children: A case study of technology‐enhanced embodied learning. Journal of Computer Assisted Learning, 40(2), 465-477.
Yue, M., Jong, M. S. Y., & Dai, Y. (2022). Pedagogical design of K-12 artificial intelligence education: A systematic review. Sustainability, 14(23), 15620.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). A systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1-27.
