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Posted by Rob Knies
Many people talk to their plants. But what if those plants were able to talk back?That’s the premise behind Botanicalls, a project to enable communications between plants and people. A sensor network provides the flora the ability to call and text people to request assistance, such as “I need water,” or “Not sure if it was you, but someone gave me a drink—I feel great!”It’s a fascinating, precocious venture, one featured on the TODAY show on May 7 as part of a discussion about home technologies. It’s also a window into the work of Kati London, one of the driving forces behind Botanicalls and the newest member of FUSE Labs at Microsoft Research.
Steve Hodges and his colleagues in the Sensors and Devices group at Microsoft Research Cambridge spend their time pursuing novel sensing technologies and new devices that make it easier for people to interact with computer systems and digital content.
The team’s successes have been many, and among the most notable have been SenseCam—a wearable camera that takes photos automatically, thereby enabling users to review a series of snapshots and recall events as they transpired—and .NET Gadgeteer, a rapid prototyping platform for small electronic gadgets and embedded hardware devices.
Now, these creative researchers have unveiled their latest concept via a note titled An Interactive Belt-worn Badge with a Retractable String-based Input Mechanism during the Association for Computing Machinery’s 2013 SIGCHI Conference on Human Factors in Computing Systems, being held in Paris through May 2.
For several years, researchers from Microsoft Research India’s Technology for Emerging Markets (TEM) group have been studying how to design applications for economically poor communities such as those found in India.
In particular, Indrani Medhi, a researcher at the India lab, has been focusing on user interfaces for low-literate and novice technology users. Medhi, who is completing her Ph.D. at the Industrial Design Centre at the Indian Institute of Technology Bombay, has co-written a paper accepted for the Association for Computing Machinery’s 2013 SIGCHI Conference on Human Factors in Computing Systems (CHI). The paper is titled Some Evidence for the Impact of Limited Education on Hierarchical User Interface Navigation and was written with Meera Lakshmanan, a translator and research assistant; Kentaro Toyama, a former head of TEM and now a researcher at the University of California, Berkeley and a fellow of the Dalai Lama Center for Ethics and Transformative Values at the Massachusetts Institute of Technology; and Edward Cutrell, Toyama’s successor as senior research manager of TEM.
The paper examines one factor in application design for poor communities: the fact that users with little or no education have a diminished capacity to navigate a hierarchical user interface. Medhi’s work has explored ways that UIs can be designed for low-literate people by using text-free iconography that such users can recognize, but the challenge continues.
Posted by Eric Horvitz and Munmun De Choudhury
At Microsoft Research, we’ve been exploring the use of data analysis and machine learning to gain insights about health and well-being—and to enhance the quality of health care. Our efforts in this area include research on using data stored in electronic health records to construct predictive models that can provide physicians with advance warning about patient outcomes.We’ve worked with colleagues to develop systems that can predict the likelihood that a patient will contract an infection while in the hospital or that a patient being discharged will be readmitted to the hospital within a short time. Some of these models have been deployed and are in use at hospitals throughout the world, providing demonstrated value to patients and physicians.Beyond examining data from medical health records about hospitalized patients, we have been interested in the prospects of developing new methods that can transform anonymized data about the search and communications activities of people into a large-scale sensor network for public health. As an example of directions and opportunities in this realm, we recently showed how we can detect previously unknown drug interactions via analysis of anonymized web-search logs. We identified useful signals via analysis of tens of millions of queries sent to search engines by millions of users who had consented to share their search activities with Microsoft for research purposes.
The Microsoft Research Machine Learning Summit 2013 concluded with a plenary panel discussion titled Data Challenges and Opportunities in the Next Decade. Chaired by Jeannette Wing, Microsoft vice president and head of Microsoft Research International, the discussion included Eric Horvitz, Microsoft distinguished scientist and managing co-director of Microsoft Research Redmond; Michel Cosnard, president of Inria; Iain Buchan of the University of Manchester; and Lionel Tarassenko of the University of Oxford.My previous post ended with Hermann Hauser, co-founder of Amadeus Capital Partners, stating that machine learning would have a profound effect on the future of health care. That was interesting, because I had planned for the final post from the summit to focus on that very subject.Buchan is quite aware of that potential. A clinical professor of Public Health Informatics at the University of Manchester and director of the MRC Health eResearch Centre, his research interests lie in building effective models of health and in connecting patients and health professionals with more potent health information.