Lantronix is incorporating Google Analytics, rich in customizable analytics, modeling, and reporting, into its PremierWave and xSenso product families. At Embeddded World 2014, the company stressed that it wasn’t enough to look at technical specs of products -- but how the products improve life (and, I imagine, productivity). The combo provides a simple analytics engine on every machine.
The products that are in the process of being married to Google Analytics capabilities include:
PremierWave XC-HSPA+, a 3.5G cellular solution that offers network redundancy, mission-critical app security, time-sensitive event tracking, and M2M connectivity.
PremierWave XC (2G), which delivers Ethernet or GSM/GPRS cellular connectivity for remote access and network control, and management of machines and equipment over a network.
PremierWave XN: multi-port application server that delivers high performance Ethernet or WiFi for remote access and machine management.
PremierWave EN: Industrial-ready ARM 9 system on Module for high-performance WiFi M2M applications.
xSenso: Compact DIN-rail and wall mount solution enabling analog sensors to send real-time data to any node on the Internet or to cloud-based apps.
xSenso Controller: Designed for use in rugged, harsh environments -- industrial automation, process control, manufacturing, chemicals, etc.
So, what will this really provide? Usable and targeted data is much needed in the burgeoning industrial IoT arena, where data abounds, but the ability to customize and analyze is slower to catch up. At Embedded World, it's the firmware to add Google Analytics to its product lineup that was demonstrated. The goal is that this type of meaningful and real-time data will continue to drive M2M adoption. Probably right.
Not clear how this works on real process or metrology tool.
Does this device capture streaming sensor data and analyze it then send summary stats or graphs to engineering database?
Does it help stream raw data to central DB?
Not clear how its used for example by a process tool vendor to help tool owners analyze machine-level data from sensors, and since there are many sensors streaming data form modern tools, does this do multivariate analysis on groups of sensors?
Or does it send signals to other modules or tools that a step has started or finished? Some case studies would be interesting. Internet of Things is still vague.
David Patterson, known for his pioneering research that led to RAID, clusters and more, is part of a team at UC Berkeley that recently made its RISC-V processor architecture an open source hardware offering. We talk with Patterson and one of his colleagues behind the effort about the opportunities they see, what new kinds of designs they hope to enable and what it means for today’s commercial processor giants such as Intel, ARM and Imagination Technologies.