การพัฒนาระบบ IoT รีไซเคิลน้ำและเศษน้ำแข็งโดยใช้การสะกิดเตือนเชิงนิเวศเพื่อเสริมสร้างพฤติกรรมการคัดแยกขยะอย่างยั่งยืน

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Apichan Kanjanavapastit
อนุวัฒน์ สงค์โพธิ์กลาง
ชวมิน ชุมแวงวาปี
ภัทรพล ศรีโสดาพล

Abstract

In the framework of smart city development, efficient waste management and water resource circularity are critical challenges. An environmental issue frequently overlooked in buildings is the contamination of dry waste by liquids, caused by disposing of beverage cups containing fluid and ice scraps directly into general bins. This study presents an IoT-based water and ice scrap recycling system prototype that integrates Internet of Things technology with Eco-Nudge mechanisms to foster waste sorting behavior change. The architecture employs an ESP32 microcontroller paired with flow sensors to manage liquid storage via a stainless-steel filter mesh, alongside a Three.js graphical engine to generate real-time 3D visualizations that deliver psychological rewards to users by converting collected water volume into a corresponding number of chili plants. The stored water can be automatically distributed to a plant irrigation system. Engineering evaluations demonstrated that the flow sensors achieved mean measurement errors of 1.16% and 4.23%, with standard deviations of ±7.9 and ±31.8 mL, respectively. The data recovery system achieved a 100% success rate, and the automated control system successfully triggered plant irrigation under the specified conditions. A preliminary field test indicated that the system attracted passerby attention; however, systematic behavioral evaluation is required in future research.

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How to Cite
1.
Kanjanavapastit A, สงค์โพธิ์กลาง อ, ชุมแวงวาปี ช, ศรีโสดาพล ภ. การพัฒนาระบบ IoT รีไซเคิลน้ำและเศษน้ำแข็งโดยใช้การสะกิดเตือนเชิงนิเวศเพื่อเสริมสร้างพฤติกรรมการคัดแยกขยะอย่างยั่งยืน. featkku [internet]. 2026 Jun. 26 [cited 2026 Sep. 9];12(1):40-51. available from: https://ph02.tci-thaijo.org/index.php/featkku/article/view/264839
Section
Research Articles

References

Belaïd F, Arora A, editors. Smart cities: social and environmental challenges and opportunities for local authorities. Cham: Springer; 2023. Available from: https://doi.org/10.1007/978-3-031-35664-3.

University of Washington Sustainability. What is recycling contamination? [Internet]. Seattle: University of Washington; 2021 Apr 20 [cited 2026 Apr 5]. Available from: https://sustainability.uw.edu/blog/recycling-contamination

Froehlich J, Findlater L, Landay J. The design of eco-feedback technology. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10); 2010 Apr 10; Atlanta, GA. New York: ACM; 2010. p. 1999–2008.

Sosunova I, Porras J. IoT-enabled smart waste management systems for smart cities: A systematic review. IEEE Access 2022; 10: 73326-50.

Hasan MK, Khan MA, Issa GF, Atta A, Akram AS, Hassan M. Smart waste management and classification system for smart cities using deep learning. Proceedings of the 2022 International Conference on Business Analytics for Technology and Security (ICBATS); 2022 Feb 24-25; Dubai, United Arab Emirates. New York: IEEE; 2022. p. 1-7.

Thaler RH, Sunstein CR. Nudge: Improving Decisions About Health, Wealth, and Happiness. New Haven: Yale University Press; 2008.

Barker H, Shaw PJ, Richards B, Clegg Z, Smith D. What nudge techniques work for food waste behaviour change at the consumer level? A systematic review. Sustainability. 2021;13(19):11099.

Linder N, Lindahl T, Borgström S. Using behavioural insights to promote food waste recycling in urban households-evidence from a longitudinal field experiment. Front Psychol. 2018;9:352.

Mataloto B, Calé D, Carimo K, Ferreira JC, Resende R. 3D IoT System for Environmental and Energy Consumption Monitoring System. Sustainability 2021; 13(3): 1495.