ARTICONF addresses issues of trust, time-criticality and democratisation for a new generation of federated infrastructure, to fulfil the privacy, robustness, and autonomy related promises that proprietary social media platforms have failed to deliver so far
Transparent, decentralised infrastructure
Simplify the configuration, creation and maintenance of custom blockchain networks by providing a cloud-agnostic Blockchain as a Service (BaaS) toolkit offering permissioned blockchain services for agile decentralised social media platforms.
Improved and trusted participation
ARTICONF creates a network of trusted social media users with an opportunity to generate, share, propagate and verify high-quality content while ensuring no ownership violation.
Democratic and tokenized decision-making
ARTICONF provides personalized recommendations to social media users and enables them to collectively recommend and generate content, flag misinformation and earn rewards in return.
Elastic resource provisioning
Improving efficiency for automating Cloud services, optimizing QoS (Quality of service) performance metrics, controlling the P2P infrastructure, and ensuring fast recovery for decentralized applications.
Cognitive analytics for collaborative economy
Trusted decentralized social network #ARTICONF provides a tokenized decision-making process and improves users' engagement rate and return on collaboration over incentivized and sharing economy through interactive and intelligent analytics.
Challenges: validate crowdsourced news, find precise and trustworthy crowd-participants and provision time-critical infrastructure resources closer to news location for faster access to breaking news.
Challenges: low public awareness of shared mobility and issues relating to precise planning, optimising business costs, person-to-person lending and collaborative consumption.
Challenges: Contextualised and thematic search of audio-visual metadata in a large video library, and the security and privacy of a scalable business model that rewards users for their interactions.
Challenges: identify the behavioural convergence of the prosumer decisions over a specific smart appliance, and lack of efficient data management to keep track of the amount of energy produced by users.