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Towards a secure and self-adapting smart indoor farming framework

Clemens Gnauer, Harald Pichler, Markus Tauber, Christoph Schmittner, Korbinian Christl, Johannes Knapitsch, Martin Parapatits

Year
2019
Citations
20
Access
Open access

Abstract

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.

Keywords

Cloud computingScalabilityComputer securityArable landPopulationComputer scienceAgricultureEngineeringDatabaseGeography

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