{"id":1023,"date":"2013-10-24T09:00:00","date_gmt":"2013-10-24T09:00:00","guid":{"rendered":"https:\/\/blogs.msdn.microsoft.com\/msr_er\/2013\/10\/24\/students-develop-analytics-engine-for-the-lab-of-things\/"},"modified":"2016-07-20T07:31:07","modified_gmt":"2016-07-20T14:31:07","slug":"students-develop-analytics-engine-for-the-lab-of-things","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/research\/blog\/students-develop-analytics-engine-for-the-lab-of-things\/","title":{"rendered":"Students develop analytics engine for the Lab of Things"},"content":{"rendered":"

\"LabThe Lab of Things (LoT) may sound like something you’d find in a sci-fi movie, but it is a lot<\/em> more practical than that: it’s a research platform that makes it easy to deploy interconnected devices in multiple homes, then share your individual research data with other investigators, turning it all into a large-scale study. The LoT thus enhances field studies in such diverse disciplines as healthcare, energy management, and home automation. It not only makes deployment and monitoring easier—it also simplifies the analysis of experimental data and promotes sharing of data, code, and study participants, further lowering the barrier to evaluating ideas in a diverse set of environments where people live, work, or play.<\/span><\/p>\n

One key to the success of the LoT is the involvement of the academic research community in developing extensions to the LoT infrastructure. These extensions can be in the form of drivers, applications, and cloud components such as analytics.<\/span><\/p>\n

Shortly after we released the LoT in July of this year, a group of students from University College London (UCL) started poking around the code and got inspired: they’ve developed an analytics engine to scrutinize data collected from experiments and research applications running on the LoT. And this is no slouch of an engine, either. Among other things, it:<\/span><\/p>\n