Teaching and Learning Innovation in Management of Technology and Innovation: SAS Smart AI Features
Keywords:
Smart refrigerator, Artificial intelligence, Food waste reduction, Smart-home technology, Sustainable consumptionAbstract
The SAS Smart AI-Enhanced Refrigerator System is an innovative smart-home solution developed to reduce household food waste through intelligent food storage management. The system uses AI-based food scanning technology to identify food type, packaging, and freshness before recommending the most suitable refrigerator compartment and temperature zone. Integrated smart compartments and an AI Alert System monitor food placement and provide expiry reminders to minimize spoilage and extend shelf life. In addition to improving food preservation, the system promotes energy efficiency and environmental sustainability. Although currently at the conceptual stage, the innovation demonstrates strong commercialization potential and supports Sustainable Development Goal 12 on responsible consumption.
References
Devarajan, R. (2022). Intelligent refrigerator using machine learning and IoT. In Proceedings of the 2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI). https://doi.org/10.1109/ACCAI53970.2022.9752587
H. Nasir, W. B. W. Aziz, F. Ali, K. Kadir, and S. Khan (2018). The implementation of IoT Based Smart Refrigerator System. 2nd Int. Conf. Smart Sensors Appl. ICSSA 2018, pp. 48–52.
Lantz., M. P. (2022). Effects of customization and product modularization on financial performance. Journal of Engineering and Technology Management.
Lucie K. Ozanne, P. W. (2022). Understanding food waste produced by university students: A social practice approach. Journal of Sustainability, Vol.14, (17).
Moro-Visconti, R. C. (2023). Artificial intelligence-driven scalability and its impact on the sustainability and valuation of traditional firms. Humanit Soc Sci Commun 10, 795.
S. Dey, A. Dutta, M. Mishra, and S. Banerjee (2019). Artificial intelligence based intelligent storage device for commoners. Proc. 4th Int. Conf. Commun. Electron. Syst. ICCES 2019, pp.960–965.
Samsung Electronics. (2025, March 30). Samsung Electronics unveils ‘AI Home’ vision at Welcome to Bespoke AI event. Samsung Newsroom. Retrieved from https://news.samsung.com/global/samsung-electronics-unveils-ai-homevision-at-welcome-to-bespoke-ai-event?utm_source=chatgpt.com
Schilling, M. A. (2020). Appropriability. In M. A. Schilling, Strategic Management of Technological Innovation (p. 202). New York: McGraw Hill Education.
Tuany Gabriela Hoffmann, C. M. (2023). Fresh food shelf-life improvement by humidity regulation in domestic refrigeration. Procedia Computer Science.
UN, U. N. (2025). The world wastes 1.05 billion metric tons of food even as hundreds of millions face hunger. Retrieved from SDG Goals: https://unstats.un.org/sdgs/report/2024/Goal-12/
United Nations Environment Programme, U. N. (2024). Global estimates of food waste. Food Waste Index Report 202. Retrieved from https://www.unep.org/resources/report/food-waste-index-report-2024
V. S. Aurel-Dorian Floarea (2016). Smart Refrigerator: A next generation refrigerator connected to the IoT. Proc. 8th Int.Conf. on Electronics, Computers and Artificial Intelligence (ECAI) 2016, pp. 4–7.
Varzakas, T. &. (2024). Global Food Security and Sustainability Issues: The Road to 2030 from Nutrition and Sustainable Healthy Diets to Food Systems Change. Foods, 13(2), 306.
Zohra Dakhia, R. (2025). AI-enabled IoT for food computing: Challenges, opportunities, and future directions. Journal of Sensors.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Mariam Setapa, Muhammad Azrul Adzahar, Nur Syuhada Adilah Mahadi, Putri Sofea Mohamed Yusoff, Nor Halida Haziaton Mohd Noor, Wan Yusrol Rizal W. Yusof

This work is licensed under a Creative Commons Attribution 4.0 International License.