Skip to main content Skip to Footer

BLOG


October 08, 2015
Analytics and the Internet of Things
By: Ops Rules Team
Bad News - the scale is threatening to cut off our access to the fridge

The Internet of Things (IoT) is a hot topic. As Wired phrases it:

The Internet of Things revolves around increased machine-to-machine communication; it’s built on cloud computing and networks of data-gathering sensors; it’s mobile, virtual, and instantaneous connection; and they say it’s going to make everything in our lives from streetlights to seaports “smart.”

IoT is expected to revolutionize many industries from home automation, healthcare, driving and of course manufacturing. In this area applications include: asset tracking, production monitoring and improved ability to detect and predict errors for equipment maintenance.



The capabilities of IoT are more powerful than ever but control systems that are very similar in concept have been around for a long time. My first civilian job in Israel was working on a system that collected status information from telecomm equipment in order to identify failure. This involved polling the equipment for status and sorting the information to deliver problems to the next level and from there to a computer that could fix the problems or alert technicians.

I later learned that these types of systems are called SCADA for Supervisory Control and Data Acquisition, which means the ability to retrieve key pieces of information from remote devices in order to take action on these locations through the use of various controls and mechanisms.

This sounds a lot like IoT except the medium is now the internet and the sensors are more readily available. This can accelerate SCADA capabilities through several areas of progress that have changed so many other industries:

  • Cheaper and more standardized sensors
  • Cheaper computing power
  • Standardization of the platform through the internet
  • Advances in Analytics – in particular, predictive and prescriptive

While the first three reasons have received a lot of attention and produced excitement about the IoT, advancement in analytics has received less attention as it related to IoT because it is much harder to define and standardize. Every system is different and the amount of data to contend with is huge and poses its only challenges and new processing requirements.

Here is an example we are working on with a client:

Problem: How do we detect and improve machine uptime in a production plant?

Our approach: includes implementation of machine learning and optimization techniques as follows:

  • Specify the relevant data to identify value before failure in real-time. An important aspect of this is to understand the necessary aggregation level n order to process the data effectively.

  • Identify the right combination of Machine Learning techniques that can use existing operating parameters to predict machine failure. Example techniques to explore include Linear Regression, Regression Trees, Random Forest, Bagging, Boosting, K-nearest neighbor, etc.

  • Define the problematic conditions and possible corrective actions

  • Implement learning algorithms that will improve as more data is fed

  • Automatically decide on the best course of action using optimization

The exciting opportunities provided by combining IoT with advanced analytics in this example is that, rather than simply reacting to problems that have already occurred, we can monitor continuously and predict problems before they happen. This then allows us to decide the best course of action (using optimization) to mitigate or avoid the problem entirely. Also, because these algorithms can leverage large data sets, they can improve over time as more data is fed to the algorithms. A virtuous cycle is created that enables continual improvement.


The problems companies face with equipment such as maintenance and visibility are not new. But the combination of new sensor technology, computing power and the internet provide a shift in the way we approach these challenges - as the Internet of Things. A key part of this are new analytics techniques that will enable the 'smart' portion of the vision.


About Accenture

Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions—underpinned by the world's largest delivery network—Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With approximately 373,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at www.accenture.com.

Accenture Digital, comprised of Accenture Analytics, Accenture Interactive and Accenture Mobility, offers a comprehensive portfolio of business and technology services across digital marketing, mobility and analytics. From developing digital strategies to implementing digital technologies and running digital processes on their behalf, Accenture Digital helps clients leverage connected and mobile devices; extract insights from data using analytics; and enrich end-customer experiences and interactions, delivering tangible results from the virtual world and driving growth. Learn more about Accenture Digital at www.accenture.com/digital.

 

About Accenture Analytics

Accenture Analytics, part of Accenture Digital, delivers insight-driven outcomes at scale to help organizations improve their performance. With deep industry, functional, business process and technical experience, Accenture Analytics develops innovative consulting and outsourcing services for clients to help ensure they receive returns on their analytics investments. For more information follow us @ISpeakAnalytics and visit www.accenture.com/analytics.

This document makes descriptive reference to trademarks that may be owned by others. The use of such trademarks herein is not an assertion of ownership of such trademarks by Accenture and is not intended to represent or imply the existence of an association between Accenture and the lawful owners of such trademarks.

This blogpost is produced by consultants at Accenture as general guidance. It is not intended to provide specific advice on your circumstances. If you require advice or further details on any matters referred to, please contact your Accenture representative.

Popular Tags

    More blogs on this topic

      Archive