Application of the IoT in the Food Supply Chain─From the Perspective of Carbon Mitigation

碳足迹 杠杆(统计) 环境经济学 供应链 粮食安全 持续性 业务 农业 生命周期评估 温室气体 物联网 计算机科学 计算机安全 营销 经济 生产(经济) 宏观经济学 生态学 机器学习 生物
作者
Zhenyi Luo,Jingyu Zhu,Tingting Sun,Yuru Liu,Shuhan Ren,Huanhuan Tong,Lei Yu,Xunchang Fei,Ke Yin
出处
期刊:Environmental Science & Technology [American Chemical Society]
卷期号:56 (15): 10567-10576 被引量:29
标识
DOI:10.1021/acs.est.2c02117
摘要

With the rising demands on supply chain transparency and food security, the rapid outspread of the Internet of Things (IoT) to improve logistical efficiency, and the rising penetration of sensor technology into daily life, the extensive integration of the IoT in the food sector is well anticipated. A perspective on potential life cycle trade-offs in regard to the type of integration is necessary. We conduct life cycle assessment (LCA) integrated with shelf life–food loss (SL–FL) models, showing an overall 5-fold leverage on carbon reduction, which is diet dependent and a function of income. Meat presents the highest leverage, 35 ± 11-times, owing to its high carbon footprint. Two-thirds (65%) of global sensors (1 billion) engaged in monitoring fruits and vegetables can mitigate less than 7% of the total reduced carbon emissions. Despite the expected carbon emission reductions, widespread adoption of the IoT faces multiple challenges such as high costs, difficulties in social acceptance, and regional variability in technological development. Furthermore, changes in the distribution of transportation resources and dealer service models, requirements regarding the accuracy of sensor data analysis, efficient and persistent operation of devices, development of agricultural infrastructure, and farmer education and training have all increased uncertainty. Nonetheless, the research trend in smart sensors toward smaller chips and the potential integration of machine learning or blockchain as further steps make it possible to leverage these advantages to facilitate market penetration. These insights facilitate the future optimization of the application of IoT sensors for sustainability.
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