Why PLM need a better search for IoT data?

I’m learning a lot these days about IoT. The amount of connected devices around us is growing and it raises lot of questions – how to store data produced by devices, what is the value of the information captured from variety of sensors and machines as well as how to make sense of this information. Google is part of Oxford dictionary. The last two decades of web taught us that good search is one of the fundamental elements of getting well with large amount of data.

My attention caught by GigaOM article Thingful upgrades its search engine for the internet of things. Thingful – a company that trying to make IoT searchable exactly in the way Google allows us to search web today. You can navigate to Thingful website and check by yourself.

Below you can see some of my experiments with browsing and searching things in Boston, MA as well as in my neighborhood.

So, why PLM vendors should care? Search is clearly part of modern user experience in every system. IoT brings many new challenges such as gigantic data corpus, frequency of updates and new user experience challenges. It will probably requires more analytic approach rather than just “search experience”. I can imagine designer ability to research existing product behavior or requirements coming directly from products in the field.

In my previous posts I discussed the potential IoT data will blow up traditional PLM databases. The ability to search for a huge IoT data corpus is part of that. However, one of the biggest opportunity in the intersection of IoT and PLM is to extend product lifecycle management from engineering and manufacturing stages into the field of physical products.

What is my conclusion? We are getting in a very interesting phase when PLM has a potential to connect physical objects with virtual models. It changes the way we manage product lifecycle by extending reach and ability to handle more data. It will require better data management and search technologies. Just my thoughts…

Best, Oleg