Towards a secure and self-adapting smart indoor farming framework
Clemens Gnauer, Harald Pichler, Markus Tauber, Christoph Schmittner, Korbinian Christl, Johannes Knapitsch, Martin Parapatits
- 发表年份
- 2019
- 引用次数
- 20
- 访问权限
- 开放获取
摘要
Abstract Facing the increase in world population and the stagnation in available arable land there is a high demand for optimizing the food production. Considering the world-wide and ongoing reduction of the agricultural labor force novel approaches for food production are required. Vertical farming may be such a solution where plants are being produced indoors in racks, cared by robotic appliances which will be operated by specialized software. Given the multitude of parameters which determine the ideal condition, a lot of data needs to be acquired. As this data is used to adapt the entire Cyber-Physical System to a changing environment the data has to be secure and adaptations have to consider safety aspects as well. Such systems must hence be secure, safe, scalable and self-adaptable to a high degree. We present an important element for such solutions, a cloud, IoT and robotic based smart farming framework.
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