Spica Technology is developing a Health solution called CLARITY to help women take control of their health with access to a digital consilium of doctors experienced in obstetrics and gynaecology.
Browse the tech-driven or digital innovations from previous BOOST cohorts.
Spica Technology is developing a Health solution called CLARITY to help women take control of their health with access to a digital consilium of doctors experienced in obstetrics and gynaecology.
LLC New algorithm is developing a digital skills learning platform to empower and unlock opportunities for girls and women in Tajikistan.
The goal of WIN's project is to develop, test, and disseminate a practice-oriented, ICT-based pilot system to support women entrepreneurs by automatically matching identified skills with needed competencies related to remote and distance jobs or business creation.
The project consistes of interpreting air quality data for the city of Minsk with isofix (heat) map using machine learning technologies and analytics. It is a continuation of the PCF project and involves the installation of 16 outdoor sensors in Minsk.
Transfer and adapt modern ways of planning and executing disinsection plans in the pilot health centers and hospitals in Ukraine that address needs on the ground.
A smart waste bin that tackles the challenges of safe waste disposal and waste management in public indoor places.
A machine learning-powered chatbot that allows anyone with Internet access to learn programming for free in the form of a natural conversation.
De Facto will create a new digital service that will contribute to the development of the low touch economy in Montenegro. It will help transform the data collection industry, which was deeply impacted by the pandemic, to use digital and innovative systems.
Floods have large consequences for communities and individuals. Better flood forecasting would lead to better real time warnings and planning, which would mean enhanced social sustainability in the region. The proposed project merges the potential of Earth Observation data with Computer Vision and Machine Learning technologies, to create improved flood forecasting and mitigation.