Abstract
There are multiple participants, such as farmers, wholesalers, retailers, financial institutions, etc., involved in the modern food production process. All of these participants and stakeholders have a shared goal, which is to gather information on the food production process so that they can make appropriate decisions to increase productivity and reduce risks. However, real-time data collection and analysis continue to be difficult tasks, particularly in developing nations, where agriculture is the primary source of income for the majority of the population. In this paper, we present a smart decision-support system for pig farming. Specifically, we first adopt rail-based unmanned vehicles to capture pigsty images. We then conduct image stitching to avoid double-counting pigs so that we can use image segmentation method to give precise masks for each pig. Based on the segmentation masks, the pig weights can be estimated, and data can be integrated in our developed mobile app. The proposed system enables the above participants and stakeholders to have real-time data and intelligent analysis reports to help their decision-making.
Subject
Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering
Reference45 articles.
1. Weis, A.J., and Weis, T. (2007). The Global Food Economy: The Battle for the Future of Farming, Zed Books.
2. Despommier, D. (2010). The Vertical Farm: Feeding the World in the 21st Century, Macmillan.
3. Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology;Janssen;Agric. Syst.,2017
4. Agricultural decision making and climate uncertainty in developing countries;Waldman;Environ. Res. Lett.,2020
5. Hu, Y. (2022, October 03). Graphics: The Real Situation of African Swine Fever in China. Available online: https://news.cgtn.com/news/3d3d774e3559444f33457a6333566d54/index.html.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献