Automotive
This project in the area of Telematics, Automotive and Advanced Data Analytics has been commissioned by one of Europe's largest insurance companies. The objective was to analyze users behaviour while driving using only data coming from smartphone sensors, with a smart, intelligent and user-centered approach.
The project was commissioned by IV electrics with the goal of creating a Vehicle Management System for their electric motorcycles. Social Thingum was in charge of all the stages of this project. The final output was an electronic board installed on the vehicles with the following features:
- Data collection from on vehicle sensors through CAN-bus;
- Conversion of the collected data in usable information;
- Creation of a dashboard to provide the driver with useful information;
- Creation of a platform where engineers could access (in real time) information regarding the vehicle (i.e. the status of the battery and Its temperature);
- Sending information to the cloud in order to perform analysis for predictive maintenance on the battery and other components.
Home Insurance
In the fields of Telematics, Automotive and Advanced Data Analytics, this project was commissioned by one the major European insurance companies.
It was mainly aimed at analysing the individuals behaviour in their own house.
Project realized in partnership with TreeSolutions, a startup incubated in PoliHub whose main focus is the development of smart heating systems and solutions. This partnership led to the creation of algorithms based on machine learning techniques for the reduction of energy consumption and of a board that could be integrated in their product.
NETT
NETT is a project funded by the European Commission, Enterprise and Industry DG, with the aim of creating a social network to improve the teaching of entrepreneurship in the European education system. The platform supports a social community where educators involved in entrepreneurship education and training can confront each other and find concrete help in the training of young people.
SandS
Social&Smart (SandS) is a European research project that started in November 2012. The aim is to build a physical and computational infrastructure that allows networked appliances to best meet the needs of their owners. The social network processes the information provided by users who refine and share usage behavior with other people who have the same intelligent equipment or other models. Thanks to the constant flow of data, the network can manage smart appliances in a sophisticated way and keep the software constantly updated according to current best practices.
Elliot
ELLIOT is a European research project whose objective is the development of an experiential platform based on the Internet of Things that allows the direct involvement of users (customers and citizens) in the co-creation, exploration and testing of new ideas, concepts and technological artifacts related to IoT applications and services. The project stimulates greater diffusion and adoption of intelligent solutions and increases the potential for collaborative innovation capable of bridging the technological gap between users.
Marketing and Telematics - Medical Evidence
We developed the ICT MMAS (Micro Marketing Analysis System) and KubettONE systems for the company Marketing & Telematica. We also created CME refresher courses for different types of healthcare professionals in collaboration with Medical Evidence, the Marketing and Telematics business unit, which has been dealing with medical-scientific information and training since 1998. The learning management system was developed for the following courses.
DietSmartFit
The project will develop infrastructure and services for health monitoring and rehabilitation management, with a particular focus on the fight against obesity, within an ecosystem consisting of:
- Conventional and intelligent body sensors;
- FI-WARE cloud-based ICT infrastructure for data collection and processing;
- Mobile app to take advantage of related health services;
Services also include self-monitoring by the user, such as the collection and analysis of parameters related to obesity: heart rate, weight, step count and calories burned in view of the target "weight loss". The user will receive personalized just-in-time advice and valuable tips from experts for their own well-being. Thanks to the intelligence of the network, optimized healthier life models can be achieved.
3D Printing
3D Printing is a modeling and slicing service for inexperienced 3D printer owners that guides the user through the printing of simple objects on their home printer through an intelligent social network. The service offers a constantly expanding catalog of objects. Each object is accompanied by a series of parameters to modify the shape to your liking. Once a satisfactory form is reached, the service sends the user the print code of the object. Social_Makers is the community of inexperienced users born from this project and hosted on the Open Innovation platform.
The project aims at involving the whole ecosystem composed of printer manufacturers, their owners, their users, and finally the facilitators to their use. Vendors could be the first promoters of the service, while detecting the real needs of users and creating the connection between demand and supply of the service. 3D modelers will be able to optimize their models according to the service they want to offer, for example by improving the scalability of certain parameters.
KubettOne
Realization of the KubettOne system for Marketing & Telematics. GeoMarketing platform that uses georeferenced information to the territory. Web-based and intuitive tool, multi-access with customized configuration. The platform allows to select the preferred territory, apply filters of selection and aggregation, create qualitative and quantitative indexes to understand the real placement of dealing phenomena on the market both dimensional and cluster.
Medical Evidence Project
Realization of LMS and ECM courses for professionals in the field of medicine for Medical Evidence, which has been involved in scientific and medical learning since 1998; the LMS has been created for this courses. It consists of continuous courses of high-profile learning and scientific contents aimed at doctors, nurses, physiotherapists… The courses are structured on main learning models ECM: remote learning, in person and blended learning (E-learning + in person).
CardoAI - Sentiment analysis
Realization of LMS and ECM courses for professionals in the field of medicine for Medical Evidence, which has been involved in scientific and medical learning since 1998; the LMS has been created for this courses. It consists of continuous courses of high-profile learning and scientific contents aimed at doctors, nurses, physiotherapists… The courses are structured on main learning models ECM: remote learning, in person and blended learning (E-learning + in person).
- INPUT: 5 profiles and the last n posts with comments
- OUTPUT: For each post, a sentiment value extracted via NLP algorithms is provided, in order to provide the company with feedback on its posts on the social network.
TECHNOLOGIES AND METHODOLOGIES USED: Python and libraries, linkedin API (Phantom), NLP algorithms, cloud platforms.
APPLICATION AREA: NLP, Sentiment analysis, data gathering.
INSALATY
OBJECTIVE: You want to transform an e-commerce into a digital platform on which a customer can compose his or her own salad by setting a number of requirements such as kcal, allergy, intolerances, special diets and specific health goals.
- INPUT: User profile and preferences
- OUTPUT: Recommendations of possible salad compositions.
TECHNOLOGIES AND METHODOLOGIES USED: python and libraries, html, react native, FireBase.
APPLICATION AREA: Machine Learning, Deep Learning, web programming.
SENIOR
OBJECTIVE: To reduce cognitive impairment by people of advanced age
- This project is based on an android application.
- This application releases a sequence of exercises. A watch is used to monitor the patient.
- The data collected are analysed by experts in psychology.
TECHNOLOGIES AND METHODOLOGIES USED: Andr Studio, Java and XML
APPLICATION FIELD: Medical-psychological field
OBJECTIVE: To predict given a text a value that indicates its accident hazard, so as to help an insurance company make an estimate of a possible claim.
- INPUT: Text describing an event
- OUTPUT: Numerical value giving the probability that it is of an accident.
TECHNOLOGIES AND METHODOLOGIES USED: Python and libraries, neural networks.
APPLICATION AREA: Artificial Intelligence, NLP.