InteliSpark client Wicked Device, LLC. has been awarded a Phase II Small Business Innovative Research (SBIR) grant worth $742,550 from the National Science Foundation. The grant is for the SBIR project “A STEM toolkit enabling global air quality experiments.”
Wicked Device, LLC. seeks to develop an internet-of-things (IoT) data collection and analysis platform for collaborative STEM (science, technology, engineering, and math) and big data research and education, that enables collaborative, geographically dispersed collection of data from internet enabled scientific instruments.
This project fulfills the requests of the federal government and leading-edge STEM educators that both secondary and post-secondary institutions teach science in a way that engages students with real-world problems. The expectation is that this project will make big data accessible, while providing rewarding and appealing hands-on learning opportunities that will increase data literacy; increase scientific collaboration in education across geographic and interdisciplinary lines; and increase scientific literacy and interest across demographics, thus increasing the likelihood that students will continue to pursue scientific careers.
The proposed technology will be the first collaborative educational IoT STEM platform to be developed, and is innovative in the field of Educational Technology, which has yet to adopt web-connected sensors that generate big data on a global scale. Right now, there is no mechanism for schools to collect and share real data between classrooms and schools in an organized way. The proposed innovation allows users to communicate via a global network and is capable of being paired with an unlimited variety of scientific instruments and data sources, to support versatile, engaging, coordinated, multi-school experiments and data sharing.
In Phase 1, feasibility of approach was firmly established. Phase II objectives will be to expand the educational platform developed in Phase I to optimize national/global impact and support applicability to big data research as well as a range of sensors. Goals include to expand tools to view and analyze data, refine and expand curriculum, develop an Application Programming Interface and create software tools to manipulate and share data/curriculum.