|By Srinivasan Sundara Rajan||
|February 3, 2014 09:00 AM EST||
Internet of Things known as IoT is expected to gain momentum in the year 2014 and will continue to find a mainstream adoption in the coming years. From a definition perspective, IoT is about the integration of more devices that are already prevalent using the RFID and other kinds of machine-generated messages, and to ensure that these devices are given the appropriate intelligence to guide themselves without human intervention.
The main reason for the increased realization of IoT is the proliferation of cloud and Big Data as part of our ecosystem, so that the massive quantities of data that these devices generate can be sourced and processed and intelligence can be derived out of them. The adoption of IoT will increase in-line with the adoption of cloud and Big Data.
Yet another reason for the imminent realization of IoT is the growth of semantic technologies as part of Big Data that not only identify events from the devices but also add intelligence to them based on the context. This context-aware intelligence plays a vital role in machine-generated messages turned into intelligence.
IoT in Enterprise IT
Initial documentation and materials floating around IoT are predominantly oriented toward consumers and citizens such that the concepts like SmartCity and SmartHome will become a reality soon with the proper adoption of IoT. But traditional enterprises in the areas of manufacturing, healthcare, and retail will face a complete transformation of their IT operations once the IoT becomes a reality. To the extent we could even coin the word IoT = (Traditional) IT obsolete. Again there is nothing to feel bad about it, when we started the cloud revolution five years ago, it threatened the enterprise IT but now it turns out to be a better value proposition for IT to concentrate more on the innovation than on day-to-day provisioning of IT compute and storage. In the same way IoT will transform the way enterprises do their job which will turn change the IT to enable the Event Intelligence for IoT enabled Enterprise. The following small case study of a Manufacturing Enterprise will help to analyze how IoT will transform the traditional IT.
IoT for Manufacturing Enterprises
The following table explains about typical applications in an automobile manufacturing enterprise and how the traditional IT handled them so far and how the IoT will transform the same.
Traditional IT Usage
IoT Enabled Usage
Bill Of Material Applications
Bill of Material known as BOM defines the hierarchy of parts and assemblies that require to build a complete product.
Traditionally ERP packages have extensive options for entering the master detail relationship between various parts and tie them together.
Assuming RFID enabled parts and assemblies identify themselves, such that a complete BOM of a finished product can be automatically derived from a proto type build of the product made during product development and the trained model can automatically be used during the plant floor production, much of the traditional work of the current IT systems will be moved to IoT.
Gross Vehicle Mass Analysis Applications
The Gross Vehicle Weight Rating (GVWR) is the maximum weight of the vehicle and plays a very important role in fuel efficiency and safety of the vehicle. Several data entry systems play a role in calculation of GVWR as per Vehicle specifications.
Already several applications that are concerned with GVWR utilizes RFID and sensor information to calculate them. IoT will expand the scenarios at the production floor, where by GVWR calculations are done without manual entry.
Vehicle Emission Calculations
Emission related reporting is the biggest regulatory requirement for vehicles. Most OEMs now have extensive systems to track the vehicle emissions and provide the reporting to government agencies like EPA (Environmental Protection Agency).
Automatic calculation of vehicle emissions and reporting is identified as one of the major use cases for IoT and hence will make the traditional systems obsolete in this regard.
Infact IoT will not just help to calculate emission levels, but will also help to reduce them with the intelligence acquired and vehicles can become smarter to reduce the emission levels.
Substance Composition For Recycling Regulatory Requirements
Modelling of Vehicles and Assemblies towards chemical substance level is a legal requirement to track the SOC (Substance Of Concern) and to ensure recyclability of products and components. This is another system which has lot of manual data entry associated with it.
There are many pilot projects in Europe to track the Recyclable elements that have SOC in them. IoT will integrate the intelligence of Vehicles about themselves with the semantic linking to the Chemical's Material Data Sheet and Other Safety guide lines to automatically provide reporting on the legal criteria.
Production Monitoring & Plant Floor
Already great level of machine generated automation plays a role in tracking of production and assembly line operations. However the lack of self-aware components and associated intelligence, several of quality operations and tests are done using manual means.
IoT can reduce the HMI (Human Machine Interface) in the Plant floor systems, by semantic linking of Vehicle Production Process data with Other Quality information.
These use cases can be expanded in detail by a Manufacturing Specialist in Automobile Domain. Already Machine to Human & Human to Machine interactions take place in a big way in automobile manufacturing. However the lack of Semantic linking of events from machines with other intelligence and the lack of ability to process massive quantities of event data towards actions prevents a complete Machine to Machine interaction in manufacturing organizations. With the emergence of IoT such possibility is becoming real and this will change the way traditional IT systems worked in the past and hence we can think of IoT as (Traditional) IT Obsolete.
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