Download The Future of Digital Business Innovation: Trends and by Vincenzo Morabito PDF
By Vincenzo Morabito
This ebook identifies and discusses the most demanding situations dealing with electronic enterprise innovation and the rising traits and practices that would outline its destiny. The ebook is split into 3 sections overlaying tendencies in electronic platforms, electronic administration, and electronic innovation. the outlet chapters reflect on the problems linked to desktop intelligence, wearable know-how, electronic currencies, and allotted ledgers as their relevance for enterprise grows. moreover, the strategic function of information visualization and traits in electronic safety are widely mentioned. the next part on electronic administration makes a speciality of the impression of neuroscience at the administration of knowledge structures, the position of IT ambidexterity in coping with electronic transformation, and how within which IT alignment is being reconfigured by means of electronic company. eventually, examples of electronic innovation in perform on the worldwide point are provided and reviewed.
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What is new, however, is the ability to combine cheaper and smaller components in powerful and internet-enabled devices . As far as buyers are concerned, smartwatches are not living up to their name. The widespread perception is that smartwatches are just activity trackers that tell the time. There is however the potential for wearable devices to overtake smartphones in terms of closer relationship between people and technology with innovations such as smartwatches, fitness armbands and data glasses that are generally used in conjunction with a smartphone .
Expert Syst Appl 35:1611–1619 References 21 50. Milley A (2000) Healthcare and data mining. Health Manag Technol 21:44–45 51. Bravo C, Castro JA, Saputelli L, Rı´os A, Aguilar-Martin J, Rivas F (2011) An implementation of a distributed artificial intelligence architecture to the integrated production management. J Nat Gas Sci Eng 3:735–747 52. Renzi C, Leali F, Cavazzuti M, Andrisano AO (2014) A review on artificial intelligence applications to the optimal design of dedicated and reconfigurable manufacturing systems.
Then, it uses AI’s processes and techniques such as Random Initialization and Forward and Back Propagation to achieve the accuracy required to predict the PUE as well as the cold water required from the cooling towers in different work environments and conditions in the DC. Such machine learning enhanced model offers opportunities for significant cost and carbon savings. Additionally, this architecture provides methods to simulate various configurations for the DC in order to be able to deal with future changes and demands .