Remotely-operated vehicles (ROVs) utilize vision-based systems—cameras—for providing user feedback. But vision-based systems are inherently limited underwater simply by the distance that light can travel; light backscatters in water, creating hot spots and otherwise noisy images. The alternative solution for many of these problems is sonar, which provides clear 3D images of the seafloor, allowing ROV operators much more detailed and larger maps. However, sonar can be prohibitively expensive, costing up to ten times more than cameras.
The WolfTracks team is developing a mid-range solution between cameras and sonar. WolfTracks uses Light Detection and Radiation (LiDAR), a laser-based system, to map the underwater terrain in real-time. Wolftracks will cost less and have a larger scanning distance and lower power output than traditional low-end sonar solutions, dramatically expanding the range of uses and expanding the market for scanning, mapping, search and rescue, and other applications.
Each year, nearly 600,000 women die worldwide as a result of complications arising from pregnancy and childbirth. In South Asia, barely 50% of women have access to antenatal care, and as a result millions of women over the years have died avoidable deaths.
This team is developing a kit consisting of rapid and cost-effective point-of-care tests to screen expectant mothers for various readily treatable diseases and health problems that can lead to complications during pregnancy. The kit contains different marker pens pre-filled with reagents and a special booklet. A simple mark on a piece of paper by the test pen creates a dipstick for urine, and results in an easily read color change, telling the healthcare worker if action is needed. The kit provides a 10 to 100 fold cost reduction in the cost of tests and longer shelf life for reagents in challenging environments.
The team is partnered with Jhpiego, a leading global NGO in maternal/child healthcare, which will provide access to test populations and marketing strategy development assistance.
Masssachusetts Institute of Technology, 2010 - $16,650
In order to meet the needs of local communities in developing countries, NGOs, designers, governments, academics, and policy makers need comprehensive, accurate data. But existing data collection processes are time-intensive, costly, and ultimately extract information from communities without engaging the community members themselves in the analysis.
This team is developing mSurvey, a simple, accessible technology that uses text-messaging technology to survey communities through mobile phones in developing countries. The technology captures data in real-time from anyone with a mobile phone and pays each respondent with mobile funds. The survey’s model enables communities to reflect on the disseminated data results from each question asked, a unique feature absent from current survey methodologies in developing countries.
The team has already performed two pilot projects in Kibera, Kenya, one of the largest slums in Africa for another team at MIT (Sustainable Vision grantees Sanergy). mSurvey reached out to over 360 community members in 2.5 hours, who texted their input to 25 questions about housing conditions, sanitation, and other demographic information.