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Blockchain and IoT Optimization
Published in Sanjeev J. Wagh, Manisha Sunil Bhende, Anuradha D. Thakare, Energy Optimization Protocol Design for Sensor Networks in IoT Domains, 2023
Sanjeev J. Wagh, Manisha Sunil Bhende, Anuradha D. Thakare
The Blockchain easily merges big data in support chain use cases with necessary consequences suggestion, supply checking enables digitally-led and process-centric. Big data is facing three genuine challenges i.e. control, data authority, and data monetization. Blockchain technology supports control to govern multi-party structure, reliability, trustworthiness, and ownership of the data transformation process in the universal data marketplace. The quality assurance components can provide services, improvements, satisfactions and guarantee as quality of services as shown in Figure 9.18.
Artificial Intelligence for Blockchain I
Published in Naveen Chilamkurti, T. Poongodi, Balamurugan Balusamy, Blockchain, Internet of Things, and Artificial Intelligence, 2021
Joy Gupta, Ishita Singh, K. P. Arjun
Data monetization helps to raise revenue. Successful companies like Google, Amazon, and Facebook, have adopted data monetization and made it an essential part of their strategy. Monetization of data can be done in two ways as shown in Figure 6.14.
Traceability and ownership claim of data on big data marketplace using blockchain technology
Published in Journal of Information and Telecommunication, 2021
Recent years have witnessed a dramatic increase in the generation of big data due to adoption of new technologies. Most of the enterprises now-a-days consider big data as a most significant resource and harness its power as a driving force to their business growth. This evergrowing demands of big data in rapidly changing competitive environment offers a new paradigm which encourages enterprises to adopt data monetization and initiates the establishment of large number of start-ups companies who sell and purchase our personal data on a daily basis. Few, among many others, include Datacamp, Datawallet, Dawex, etc. 1 There are many other situations where data monetization is an integral and indispensable part of a system in the form of data-as-a-service model (Terzo et al., 2013). Some interesting fields spawned and co-existing with the use of big data are machine learning, deep learning, artificial intelligence, data-science, etc., which may demand training dataset in a pay-per-use fashion. In this context, examples like census data collection shows its relevancy, where the task is outsourced to a large number of organizations in a hierarchical fashion to collect data locally at individual-levels and then to combine them together towards the higher levels, covering data-collection over a large geographical areas.
Spatial data trusts: an emerging governance framework for sharing spatial data
Published in International Journal of Digital Earth, 2023
Nenad Radosevic, Matt Duckham, Mohammad Saiedur Rahaman, Serene Ho, Katherine Williams, Tanzima Hashem, Yaguang Tao
As data valuation frameworks are usually application-specific, a general-purpose solution can be challenging to build. A big data value chain framework for end-to-end data monetization is presented in Faroukhi et al. (2020). Deloitte presented a data valuation framework (Deloitte 2020) with four key components: (i) identifying current data assets, (ii) identifying attributes from current data assets, (iii) identifying use cases and corresponding data value exploration, and (iv) exploring alternative or future use cases if the current use cases and valuation are not satisfactory (Figure 10).