Junko, the business model of Sensor Platforms (SP) is basically 'fix it in software' to deal with sensor out put challenges -noise, lack of linearity, combining and correlating sensed outputs between sensors (sensor fusion), etc. If I have to borrow a lexicon from the Cloud Computing space, what SP offers is a virtualized sensor. How ever, many multi-DOF (degrees of freedom) sensor vendors have been embedding program codes and/or offering free / open source versions -a direct threat to SP's business model.
More over, fixing it in software may not be the most optimum and energy efficient way to do things. But SP's advantage is one can build systems with sensors from multiple vendors and use SP's API to tie them together. How ever, iOS already has API's do this (don't know if that is better or worse than SP's); I imagine Android may have similar API's too.
SP's site still lists Ian Chen as one of the exec's.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.