Abstract
Giving early access to the knowledge and skills on the Internet of Things (IoT) and artificial intelligence (AI) technologies would lead to early innovations and inventions. The introduction of such technology to primary and high school students is felt significant to harness the creativity of youths faster and earlier. In order to do so, it is important to give them access to friendly and easy technologies. This eventually will help them realize the potential of IoT and AI. This project studies two platforms Arduino IDE and runlinc IDE on their user-friendliness, ease of IoT STEM AI application development. A system model-based experimental comparison was carried out. The microcontrollers and sensors are independent variables. The required program code in lines of statements, time taken to develop the program code, and parameters controlled by sensors as dependent variables. The user experience survey was conducted to supplement the experimental findings. The respondents are primary and high school students, university students and teachers, professionals, and researchers. Respondents are largely who had experience of using both Arduino and runlinc. Both the experiment result and the survey showed that the runlinc is easy and faster to realize the development of IoT and AI application development.
This work is supported by Sri Lanka Technological Campus through the Responsive Research Seed Grant with Grant ID RRSG/2020/B15. It is the joined project titled COVID-19 Online BabySitting: Engaging Children through Learning STEM AI and IoT Technologies between the Sri Lanka Technological Campus, SRI LANKA, and the Jigme Namgyel Engineering College, Royal University of Bhutan, Bhutan.
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Acknowledgements
Authors would like to thank Dr. Miroslav Kostecki, TechnicalDirector, STEMSEL Foundation, Adelaide, Australia, for helping us in capacity development on runlinc IDE and STEMSEL through several workshops and demonstrations via Skype. Authors also would like to express our gratitude to Mr. Michael Cheich for his continues support in Arduino learning by sharing Arduino learning resources provided by Electronics Programming Academy, USA.
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Chedup, S., Jayakody, D.N.K., Subba, B., Hydher, H. (2021). Performance Comparison of Arduino IDE and Runlinc IDE for Promotion of IoT STEM AI in Education Process. In: Gopi, E.S. (eds) Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication. Lecture Notes in Electrical Engineering, vol 749. Springer, Singapore. https://doi.org/10.1007/978-981-16-0289-4_18
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