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Startup Uses Sensor Networks To Debug Science Experiments (xconomy.com)
gthuang88 writes: Environmental factors like temperature, humidity, or lighting often derail life science experiments. Now Elemental Machines, a startup from the founders of Misfit Wearables, is trying to help scientists debug experiments using distributed sensors and machine-learning software to detect anomalies. The product is in beta testing with academic labs and biotech companies. The goal is to help speed up things like biology research and drug development. Wiring up experiments is part of a broader effort to create "smart labs" that automate some of the scientific process.
This sort of thing has always been available for pharmaceutical manufacturing, but has been long overlooked on the research side. I've been at a few science research based engineering companies that collect this kind of data already, but don't do anything to analyse it unless something catastrophic happens. A software tool that could enable visualization of this data across experiments will extremely valuable as we remove technician to technician variation (via robotics) and a synthetic biology becomes more common place, and could prove as invaluable as well plate edge effect analysis already included in major bio-analysis software packages such as spotfire.