The State and Future of Smart Agriculture: Insights from mining social media
Martinson Ofori, Omar El-Gayar
- 发表年份
- 2019
- 引用次数
- 11
摘要
Smart agriculture involves the use of technology such as drones, GPS, robotics, IoT, AI, big data, and solar energy to improve farming practices. As with any disruptive innovation, however, stakeholder expectations can be misaligned from what the innovation can actually deliver. There can also be varying perspectives on what the innovation entails, related topics of interest, and impediments to large scale adoption. This study examines public perception of smart agriculture and its perceived drivers and challenges as present in social media discourse. We collected online posts from Twitter, Reddit, forums, online news and blogs between January 2010 and December 2018 for analysis. Results show that 38% of social media posts contained emotion with 52% joy, 21% anger and 12% sadness. Through topic analysis, we discovered seven key drivers and challenges for smart agriculture which included: enabling technologies, data ownership and privacy, accountability and trust, energy and infrastructure, investment, job security, and climate change.
关键词
相关论文
Artificial intelligence: a modern approach
1995
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun
2012
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martı́n Abadi, Ashish Agarwal, Paul Barham 等 20 位作者
2016
Vision meets robotics: The KITTI dataset
Andreas Geiger, Philip Lenz, Christoph Stiller 等 4 位作者
2013