FlairBit provides Senseioty (http://www.senseioty.com) a software platform to accelerate the Industrial Internet of Things Big-Data Analytics in order to provide useful insights from collected data.

First Master Thesis Proposal – IoT Platform

Main topic
IoT, Big-Data

Subtopic
Reactive Streaming (Akka), Big-Data databases (Cassandra, MongoDB), Big-Data processing (Spark)

Pre-requisites
Basic knowledge of some programming languages (e.g., Java, R, Phyton), Basic knowledge of databases

Description
The main goal of this work is to study, develop and analyze at least one cutting edge technology in order to create some innovative micro-services to extend the Senseioty platform to provide new added value services.
As an example, cutting edge reactive streaming techniques can be used for on-line data processing and filtering, Big-Data database can be used for large-scale IoT deployments and to deal with data velocity, variety and heterogeneity, advanced Big-Data processing techniques can be used to process high-volume data in real-time.

Second Master Thesis Proposal – Data Analitycs

Main topic
Data Science, IoT

Subtopic
Forecasting, clustering, predictive maintenance, fraud detection

Pre-requisites
Basic knowledge of some programming languages (e.g., Java, R, Phyton), Basic knowledge of Machine Learning techniques

Description
The main goal of this work is to study, develop and analyze at least one algorithm in order to extract useful insights from industrial data repositories. As an example, starting from collected data it could be possible to forecast performances of equipment in a production line, to detect fraud and missuses of equipment, to predict faults and downtime and to anticipate issues and problems.