It seems like the next phase of this effort needs to be driven by suggestions from users on the right set of compare fields. The MCU fields are just not very helpful. I will be sending in my suggestions and I hope others will too.
I guess in this case it would have to be the datasheet from which 'normalized' data was taken. I should have made that clear...I guess I was also looking for some place to archive the originals or variations.
hi bcarso: thanks for the kudos. I like where you're going with that last comment. Someday... Just need a few more datapoints for our maximum likelihood counterfeit prediction algorithm. Have you had counterfeit issues yourself?
Good idea, and promising initial implementation it sounds like.
I feel like kidding a bit here as I know these things are outside the scope, but wouldn't it be nice to see "likelihood the part you buy is counterfeit", as well as a "predicted longevity in standard distribution" parameter?
But seriously, nice to see the effort and something more than the usual batch grab for google rank.
I applaud the efforts as well. However, it would be good to cache the original datasheets in whatever form in addition to the normalized ones. You know the originals of older stuff are getting harder to find as manufacturers take them out of their lineup.
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.