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The Internet of Things empowers citizens to interconnect their devices, such as smart phones, into large-scale participatory decentralized networks, which they can use to make real-time collective measurements as public good, for instance, crowd-sourcing the monitoring of traffic in a city. This approach is an alternative to big data analytics systems that are often expensive to access, privacy-intrusive...
The feasibility of large-scale decentralized networks for local computations, as an alternative to big data systems that are often privacy-intrusive, expensive and serve exclusively corporate interests, is usually questioned by network dynamics such as node leaves, failures and rejoins in the network. This is especially the case when decentralized computations performed in a network, such as the estimation...
The pervasiveness of Internet of Things devices in techno-socio-economic domains such as Smart Cities and Smart Grids results in a massive scale of data about our society. Decision-making by system operators or policy-makers requires a sophisticated understanding of these data with real-time data analytics methods. However, common data analytics methods often serve exclusively corporate and commercial...
Participation in social sensing applications is challenged by privacy threats. Large-scale access to citizens’ data allow surveillance and discriminatory actions that may result in segregation phenomena in society. On the contrary are the benefits of accurate computing analytics required for more informed decision-making, more effective policies and regulation of techno-socio-economic systems supported...
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