Big data concepts theories and applications pdf Data is expected to have a large impact on Smart Farming and involves the whole supply chain. Smart sensors and devices produce big amounts of data that provide unprecedented decision-making capabilities. Big Data is expected to cause major shifts in roles and power relations among traditional and non-traditional players. Smart Farming is a development that emphasizes the use of information and communication technology in the cyber-physical farm management cycle.
New technologies such as the Internet of Things and Cloud Computing are expected to leverage this development and introduce more robots and artificial intelligence in farming. This is encompassed by the phenomenon of Big Data, massive volumes of data with a wide variety that can be captured, analysed and used for decision-making. This review aims to gain insight into the state-of-the-art of Big Data applications in Smart Farming and identify the related socio-economic challenges to be addressed. Following a structured approach, a conceptual framework for analysis was developed that can also be used for future studies on this topic. Big data are being used to provide predictive insights in farming operations, drive real-time operational decisions, and redesign business processes for game-changing business models.
Several authors therefore suggest that Big Data will cause major shifts in roles and power relations among different players in current food supply chain networks. The landscape of stakeholders exhibits an interesting game between powerful tech companies, venture capitalists and often small start-ups and new entrants. At the same time there are several public institutions that publish open data, under the condition that the privacy of persons must be guaranteed. From a socio-economic perspective, the authors propose to give research priority to organizational issues concerning governance issues and suitable business models for data sharing in different supply chain scenarios. Theories guide the enterprise of finding facts rather than of reaching goals, and are neutral concerning alternatives among values. To theorize is to develop this body of knowledge. These two things are related but can be independent, because it is possible to research health and sickness without curing specific patients, and it is possible to cure a patient without knowing how the cure worked.
The word has been in use in English since at least the late 16th century. Pythagoras emphasized subduing emotions and bodily desires to help the intellect function at the higher plane of theory. Thus it was Pythagoras who gave the word “theory” the specific meaning that led to the classical and modern concept of a distinction between theory as uninvolved, neutral thinking, and practice. For Aristotle, both practice and theory involve thinking, but the aims are different. However, the truth of any one of these statements is always relative to the whole theory. Therefore, the same statement may be true with respect to one theory, and not true with respect to another.