Dynamic Intelligent Aggregation Service

Real-time data analytics, highly adaptive, truly decentralized. Made by citizens for citizens.

Dynamic

as it can operate in unreliable environments with rapidly changing input data.

Intelligent

thanks to an intelligent memory system that guarantees accurate measurements.

Aggregation

concerns the computation of several large-scale collective measurements.

Service

as it can be used by different techno-socio-economic applications.

Truly Decentralized Big Data Analytics

Adaptation

Make accurate computations over streams of dynamically changing input data flowing in dynamic and distributed networks.

Privacy

Self-determination of information sharing, use of obfuscation and differential privacy techniques.

Services

By design support of several aggregation functions for collective measurements.

Applications

A generic service supporting several distributed applications.

How it Works

Choose what information to stream into the DIAS network.

Receive back collective information about all participating users.

Increase awareness, adapt your input information and influence the world.

Application Example

1. Connect your smart meter that monitors the energy consumption to the DIAS network.

2. Receive back real-time information about the total load in the Smart Grid.

3. Adjust the energy consumption and contribute to the prevention of a blackout or to higher use of renewable resources.

An alternative to the surveillance, discriminatory and highly commercialized practices of current Big Data analytics.

Features

Data Streaming Analytics

One algorithm, one system, several collective measurements such as summation, average, standard deviation, maximum, minimum, top-k, and other.

Real-time adaptation

Analytics can be accurately computed in real-time even under rapid changes in the input data thanks to a distributed and intelligent memory system.

Privacy-by-design

Efficient and privacy-preserving local storage of input data. Whatever is local, stays local.

Participatory crowd-sourced computations

No need for a mainframe computing, data center or a cloud infrastructure. It works with users’ computational resources such as a personal computer.

Applications & Services

Prediction of rare and extreme events in Smart Cities, coordination of regulatory actions in Smart Grids, spread of opinion dynamics, electronic voting and other applications of environmental monitoring, social sensing and infrastructural sensing.