Open Access
Issue
BIO Web Conf.
Volume 220, 2026
The 6th International Conference on Marine Sciences (ICMS 2025)
Article Number 05001
Number of page(s) 13
Section Marine Technology and Innovation
DOI https://doi.org/10.1051/bioconf/202622005001
Published online 11 February 2026
  • H.M. Hoang, S.H. Yousefi, R.K. Singh, Life cycle assessment of salmon cold chains. J. Clean. Prod. 132, 1–11 (2016). [Google Scholar]
  • A. Flammini, G. Brancoli, M.F. Petersen, Greenhouse gas emissions from cold chains in agrifood systems. Sustainability. 16, 21 (2024). https://doi.org/10.3390/su16219184 [Google Scholar]
  • FAO, Food loss and waste in fish value chains, FAO Fisheries Report (FAO, Rome, 2020). [Google Scholar]
  • F. Kruijssen, M.T.T. Tuan, P.C. Le, Loss and waste in fish value chains: A review of evidence. Glob. Food Sec. 26, 100373 (2020). https://doi.org/10.1016/j.gfs.2020.100434 [Google Scholar]
  • E.A. Setiawan, H. Thalib, S. Maarif, Techno-economic analysis of solar photovoltaic system for fishery cold storage in Indonesia. Processes. 9, 1930 (2021). https://doi.org/10.3390/pr9111973 [Google Scholar]
  • W. Wardi, M.A. Budiyanto, Design of a 10-ton capacity solar-powered cold storage at the fishery industry. IOP Conf. Ser. Earth Environ. Sci. 674, 012011 (2021). [Google Scholar]
  • M. Tassou, Y. Ge, A. Hadawey, D. Marriott, Energy consumption and conservation in food retailing. Appl. Therm. Eng. 31, 147–156 (2011). https://doi.org/10.1016/j.applthermaleng.2010.08.023 [Google Scholar]
  • R.A. Brown, Refrigeration load calculations in cold storage. Int. J. Refrig. 37, 123–132 (2014). [Google Scholar]
  • J. Gubbi, R. Buyya, S. Marusic, M. Palaniswami, Internet of Things (IoT): A vision, architectural elements, and future directions. Future Gener. Comput. Syst. 29, 1645–1660 (2013). https://doi.org/10.1016/j.future.2013.01.010 [CrossRef] [Google Scholar]
  • S. Bandyopadhyay, R. Sen, IoT-based smart cold storage monitoring system. IEEE Internet Things J. 5, 1767–1775 (2018). [Google Scholar]
  • L. Yan, J. Zhang, X. Liu, IoT-enabled cold chain logistics: Monitoring and energy efficiency. Comput. Ind. 98, 205–212 (2018). [Google Scholar]
  • P. Ghasemi, A. Faraji, M.B. Aryanezhad, Predictive maintenance in cold storage using IoT and machine learning. Sustain. Comput. Inform. Syst. 30, 100575 (2021). [Google Scholar]
  • R.F. Aziz, A.A. Mohamed, S.A. Khalil, Barriers to IoT adoption in emerging economies: A case study in food supply chain. Technol. Forecast. Soc. Change. 176, 121487 (2022). [Google Scholar]
  • M. Chen, Y. Ma, Y. Li, D. Wu, Y. Zhang, C. Youn, Wearable 2.0: Enabling human– cloud integration in next generation healthcare systems. IEEE Commun. Mag. 55, 54–61 (2017). https://doi.org/10.1109/MCOM.2017.1600410CM [Google Scholar]
  • L. Atzori, A. Iera, G. Morabito, From “smart objects” to “social objects”: The next evolutionary step of the Internet of Things. IEEE Commun. Mag. 52, 97–105 (2014). https://doi.org/10.1109/MCOM.2014.6710070 [Google Scholar]
  • Y. Sun, J. Zhang, X. Liu, Energy harvesting wireless sensor networks for food cold chain monitoring. Sensors. 20, 1236 (2020). [Google Scholar]
  • S.R.N. Kalid, A.Z. Shaikh, S.M. Mahmud, Development of portable IoT-based cold storage monitoring system for perishable goods. Int. J. Adv. Comput. Sci. Appl. 11, 450–456 (2020). [Google Scholar]
  • R.C. Juanda, T.A. Nugroho, F. Pradana, Design of IoT-based fish cold storage monitoring system using NodeMCU ESP8266, in Proceedings of the ICITEE 2021, pp. 196–201 (2021). [Google Scholar]
  • A.B. Hasan, R.M. Rizal, D. Hidayat, Application of Internet of Things (IoT) in supply chain management: A case study in fisheries. J. Supply Chain Manag. Innov. 3, 75–84 (2021). [Google Scholar]
  • Y. Liu, J. Wu, Z. Wang, Energy consumption analysis of cold storage systems in fishery industry. Appl. Energy. 285, 116396 (2021). [Google Scholar]
  • M.A. Islam, M.A. Hoque, T. Rahman, IoT-based intelligent cold storage monitoring system to reduce carbon emission, in Proceedings of ICSEEA 2022 conference, pp. 201–206 (2022). [Google Scholar]
  • H. Chen, L. Xu, X. Chen, IoT-enabled cold chain logistics: A framework and case study in perishable food transportation. Comput. Ind. 95, 82–95 (2018). [Google Scholar]
  • J. Cirera, J. A. Carino, D. Zurita Millan, J.A. Ortega, Improving the energy efficiency of industrial refrigeration systems by means of data-driven load management. Processes. 8, 1106 (2020). https://doi.org/10.3390/pr8091106 [Google Scholar]
  • H.-J. Lin, P.-C. Chen, H.-P. Lin, I.-Y. L. Hsieh, Quantifying carbon emissions in cold chain transport: A real-world data-driven approach. Transp. Res. Part D Transp. Environ. 142, 104679 (2025). https://doi.org/10.1016/j.trd.2025.104679 [Google Scholar]
  • B.R. Wicaksono, T. Sutandi, S. Tembo, Forecasting fisheries production in Indonesia. J. Econ. Stud. Pembangunan. 21, 170–184 (2020). https://doi.org/10.18196/jesp.21.2.5039 [Google Scholar]
  • R. Mehdipour, B.F. Beigi, R. Fathiraboki, H. Asgari, Z. Baniamerian, Cold storage systems for electricity management: Performance analysis in office and power plant applications. Next Energy. 8, 100363 (2025). https://doi.org/10.1016/j.nxener.2025.100363 [Google Scholar]
  • K. Koritsoglou, M.S. Papadopoulou, A. Boursianis, P.G. Sarigiannidis, S. Nikolaidis, S. Goudos, Smart refrigeration equipment based on IoT technology for reducing power consumption, in Proceedings of MOCAST 2022 conference, IEEE Xplore, Bremen, Germany, June 8-10 2022, (2022). https://doi.org/10.1109/mocast54814.2022.9837760 [Google Scholar]
  • R. Touaibi, H. Köten, Energy analysis of vapor compression refrigeration cycle using new-generation refrigerants with low global warming potential. J. Adv. Res. Fluid Mech. Therm. Sci. 87, 106–117 (2021). https://doi.org/10.37934/arfmts.87.2.106117 [Google Scholar]
  • PT Capricorn Indonesia Consult, A cold chain study of Indonesia. In The Cold Chain for Agri-food Products in ASEAN, edited by E. Kusano, pp. 101–147 (ERIA, Jakarta, 2019). [Google Scholar]
  • B. Lin, C. Guan, Assessing consumption-based carbon footprint of China’s food industry in global supply chain. Sustain. Prod. Consum. 35, 365–375 (2023). https://doi.org/10.1016/j.spc.2022.11.013 [Google Scholar]
  • A. Onyebuchi, U.O. Matthew, J.S. Kazaure, G.N. Ebong, C.C. Ndukwu, A.C. Nwanakwaugwu, O.D. Okey, Cloud-based IoT data warehousing technology for e- healthcare: A comprehensive guide to e-health grids. In Pioneering smart healthcare 5.0 with IoT, federated learning, and cloud security, pp. 1–19 (IGI Global, Hershey, 2024) [Google Scholar]
  • K. Wang, N. Du, Real-time monitoring and energy consumption management strategy of cold chain logistics based on the Internet of Things. Energy Inform. 8, 1 (2025). https://doi.org/10.1186/s42162-025-00493-w [Google Scholar]
  • J. Nunes, D. Neves, P. D. Gaspar, L.P. Andrade, Predictive tool of energy performance of cold storage in agrifood industries: The Portuguese case study. Energy Convers. Manag. 88, 758–767 (2014). https://doi.org/10.1016/j.enconman.2014.09.018 [Google Scholar]

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