An Approach for a Self-Growing Agricultural Knowledge Cloud in Smart Agriculture
Typically, most of the agricultural works have to consider not only fixed data related with a cultivated crop, but also various environmental factors which are dynamically changed. Therefore, a farmer has to consider readjust the fixed data according to the environmental conditions in order to cultivate a crop in optimized growth environments. However, because the readjustment is delicate and complicated, it is difficult for user to by hand on a case by case. To solve the limitations, this paper introduces an approach for self-growing agricultural knowledge cloud in smart agriculture. The self-growing agricultural knowledge cloud can offer a user or a smart agricultural service system the optimized growth information customized for a specific crop with not only the knowledge and the experience of skillful agricultural experts, but also useful analysis data, and accumulated statistics. Therefore, by using the self-growing agricultural knowledge cloud, a user can easily cultivate any crop without a lot of the crop growth information and expert knowledge.
KeywordsUbiquitous agriculture Agricultural cloud Smart service Knowledge-based
This work was supported by the Industrial Strategic technology development program, 10040125, Development of the Integrated Environment Control S/W Platform for Constructing an Urbanized Vertical Farm funded by the Ministry of Knowledge Economy (MKE, Korea). And this research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) founded by the Ministry of Education. Science and Technology (2011-0014742).
- 2.Zhou Y, Yang X, Guo X, Zhou M, Wang L (2007) A design of greenhouse monitoring and control system based on ZigBee wireless sensor network. In: international conference on wireless communications, networking and mobile computing, WiCom 2007, pp 2563–2567, Sept 2007Google Scholar
- 4.Ayday C, Safak S (2009) Application of wireless sensor networks with GIS on the soil moisture distribution mapping. In: Symposium GIS Ostrava 2009—seamless geoinformation technologies, Ostrava, Czech RepublicGoogle Scholar
- 5.Kumar H, Park P (2010) Know-ont: a knowledge ontology for an enterprise in an industrial domain. IJDTA 3(1):23–32Google Scholar
- 6.Kawasar F, Shaikh M, Park J, Mitsuru I, Nakajima T (2008) Augmenting user interaction in a smart home applying commonsense knowledge. IJSH 2(4):17–31Google Scholar
- 7.Qwaider W (2011) Integrated of knowledge management and e-learning system. IJHIT 4(4):59–70Google Scholar
- 8.Caytiles R, Lee S, Park B (2012) Cloud computing: the next computing paradigm. IJMUE 7(2):297–302Google Scholar
- 9.Cho Y, Cho K, Shin C, Park J, Lee E (2012) An agricultural expert cloud for a smart farm. FutureTech 164:657–662Google Scholar