Abstract : The integration of Artificial Intelligence (AI) in smart food packaging represents a transformative paradigm in the food industry. This innovative approach leverages AI algorithms to enhance food safety, quality assurance, and shelf-life prediction. Smart packaging equipped with sensors and data analytics capabilities enables real-time monitoring of food conditions, leading to reduced food waste, improved supply chain management, and heightened consumer satisfaction. This chapter underscores the pivotal role of AI in shaping the future of smart food packaging, heralding a new era of efficiency and safety in the food supply chain.
Keywords :
Cite : Musheer, N., Bharti, S., A., Mallira, N., A., S., & Yusuf, M. (2023). Artificial Intelligence In Smart Food Packaging (1st ed., pp. 89-95). Noble Science Press. https://doi.org/10.52458/9788196897437.nsp.2023.eb.ch-13
References :
N. N. Misra, Y. Dixit, A. Al-Mallahi, M. S. Bhullar, R. Upadhyay, and A. Martynenko, “IoT, big data and artificial intelligence in agriculture and food industry,” IEEE Internet of Things Journal, vol. 1, p. 1, 2020.
G. Soltani-Fesaghandis and A. Pooya, “Design of an artificial intelligence system for predicting success of new product development and selecting proper market-product strategy in the food industry,” International Food and Agribusiness Management Review, vol. 21, no. 7, pp. 847–864, 2018.
P. K. Donepudi, “Technology growth in shipping industry: an overview,” American Journal of Trade and Policy, vol. 1, no. 3, pp. 137–142, 2014.
S. Vadlamudi, “Agri-food system and artificial intelligence: reconsidering imperishability,” Asian Journal of Applied Science and Engineering, vol. 7, no. 1, pp. 33–42, 2018.
O. Castillo and P. &Meliif, “Automated quality control in the food industry combining artificial intelligence techniques with fractal theory,” WIT Transactions on Information and Communication Technologies, vol. 10, 1970.
S. Bera, “An application of operational analytics: for predicting sales revenue of restaurant,” in Machine Learning Algorithms for Industrial Applications, pp. 209–235, Springer, Cham, Switzerland, 2021.
N. Tyagi, R. Khan, N. Chauhan, A. Singhal, and J. Ojha, “E-rickshaws management for small scale farmers using big data-Apache spark,” in IOP Conference Series: Materials Science and Engineering, vol. 1022, no. 1, Bandung, Indonesia, April 2021.
P. Jayaraman, A. Yavari, D. Georgakopoulos, A. Morshed, and A. Zaslavsky, “Internet of things platform for smart farming: experiences and lessons learnt,” Sensors, vol. 16, no. 11, p. 1884, 2016.
X. Morvan, N. P. A. Saby, D. Arrouays et al., “Soil monitoring in Europe: a review of existing systems and requirements for harmonisation,” Science of the Total Environment, vol. 391, no. 1, pp. 1–12, 2008.
