The State-of-the-Art of Knowledge-Intensive Agriculture: A Review on Applied Sensing Systems and Data Analytics

Table 3

The state-of-the-art of big data applications in smart farming and key issues (Wolfert et al. [8]).

Stages of the data chain	State of the art	Key issues
Data capture	Sensors, open data, unmanned aerial vehicles (UAV), biometric sensing, genotype information, reciprocal data	Availability, quality, formats
Data storage	Cloud-based platform, Hadoop Distributed File System (HDFS), hybrid storage systems, cloud-based data warehouse	Quick and safe access to data
Data transfer	Wireless, cloud-based platform, Linked Open Data	Safety, agreements on responsibilities and liabilities
Data transformation	Machine learning algorithms, normalization, visualization and anonymization	Heterogeneity of data sources, automation of data cleansing and preparation
Data analytics	Yield models, planting instructions, benchmarking, decision ontologies, cognitive computing	Semantic heterogeneity, real-time analytics, scalability
Data marketing	Data visualization	Ownership, privacy, new business models