Welcome!

@ThingsExpo Authors: Yeshim Deniz, Elizabeth White, Zakia Bouachraoui, Liz McMillan, William Schmarzo

Related Topics: @ThingsExpo, Machine Learning , @DXWorldExpo

@ThingsExpo: Blog Post

Are You Thinking About Big Data When Doing IoT? – You Should Be | @ThingsExpo #ML #IoT #M2M #BigData

Based on all estimates by industry analysts and current trends, the IoT is growing at an incredible rate and is here to stay

Are You Thinking About Big Data When Doing IoT? - You Should Be

There is no denying the Internet of Things (IoT) is a hot topic. Gartner positions IoT as being at the peak of the ‘hype cycle.' From a size perspective, these ‘Things' can be anything, from a small sensor to a large appliance, and everything in between. The data transmitted by these devices, for the most part, tends to be small - tiny packets of information destined for consumption and analysis, bringing value to the business.

Is there hype? Yes. As with any new technology, there is always a level of hype involved. Are the data packets involved small? For the most part, yes (there are always exceptions). While both may be true, The Internet of Things is growing at breakneck speed. No matter which analyst you read, the growth predictions are staggering. Gartner predicts that we will hit over 20 billion (with a B) devices by 2020. IHS predicts even larger numbers, with 30 billion by 2020, and over 75 billion devices by 2025. No matter what, that's a lot of devices, and no matter how small the packets, multiplied by the number of devices, that's a lot of data.

It's not the things, it's the data
What I find interesting is that many times the focus of discussion when talking IoT are the devices, the sensors, the hardware itself. The latest Fitbit or smartwatch. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). Yes, those technologies are interesting (okay, fascinating, I will admit, my inner geek loves getting down into the actual technologies), but when we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing?

What I am about to say may sound like heresy to many. IoT is not about the devices. The devices are not the end goal. The devices are tools, mechanisms, conduits, conduits of information. They provide (and consume) information. Massive amounts of information. A former colleague of mine for years was always fond of saying, ‘Ed, It's all about the data.' In the burgeoning world of IoT that statement identifies the true business value of IoT. Information.

Watching out for potholes
Recently, Ford announced they were testing a pothole detector and alert system for cars. Living in New England, let me tell you, potholes are the bane of a car driver's existence. Many a car ends up in the repair shop during pothole season. Given that, the concept is intriguing. The manufacturer has cameras mounted on the vehicles. The cameras scan the roadway around the vehicle looking for signs of potholes. Image recognition allows it to make this determination. If a pothole is detected, the system will allow the car to avoid hitting the pothole, and thus potential damage to the vehicle.

Now some would say, ‘what does that have to do with big data?' The system is self-contained within the vehicle. To be useful, the system needs to react in near real-time to the situation. It doesn't have time to send all the data back to the cloud for analysis to determine if there is a pothole. Also, what if it loses network connection? All valid points. Let's take a step back, and look at the bigger picture.

  • How does the system recognize a pothole? Image recognition. What does image recognition need? Lots of data about what potholes look like. Machine learning algorithms help it determine if its seeing a pothole, and those algorithms need data to do that.
  • What will be the source of those pothole images? Wouldn't it be useful if images of any potholes the system encounters become part of the source data for the image recognition system to improve its detection? Wouldn't it be useful to provide that back to a central location to improve the algorithms and detection software, which could then be sent back to all the other vehicles to improve their capability?
  • What about all the cars without the system? Wouldn't it be nice if the pothole locations were flagged to the various GPS applications people use so they are aware of the pothole and its location?
  • What about the local public works department? Wouldn't it be nice if they were automatically notified about the new pothole identified so it could be repaired?

Ingestion considerations
Given the importance of the data to the success of any IoT implementation, ingesting that information is critical to the successful implementation.

  • Data Quality - In the world of data, quality has always been an important consideration. Data cleansing and scrubbing is standard practice already in many organizations. It has become critical for IoT implementations. Ingesting dirty data into even the best IoT implementation will bring it to a grinding halt.
  • Data Volume - As I have mentioned already, many times the data packets for an individual device/sensor are small. That being said, multiplied by the sheer number of devices, the volume can quickly overwhelm a network or storage environment if not planned for appropriately. These considerations also must take into account location
  • Data Timeliness - Besides volume, new and timely data is also a consideration. In the pothole example, if the last update was weeks ago, how valid is the location anymore?
  • Data Pedigree - Where did the data come from? Is it a valid source? The pedigree is less important when using internal systems, as the source is well known, but IoT systems, by their nature, frequently will be getting their data from devices and sources outside the normal perimeter. This requires extra effort to ensure you trust the information being consumed.

No technology negates the need for good design and planning
Based on all estimates by industry analysts and current trends, the Internet of Things is growing at an incredible rate and is here to stay. There is a big radar blip of data outside your data center that is not going anywhere. That data provides great value, but also many challenges that need to be taken into consideration. If you are doing IoT and are not looking at Big Data, you are missing an opportunity and business value. As many of my readers have heard me say frequently, no technology negates the need for good design and planning. The Internet of Things and the accompanying Big Data demands it if you are to be successful.

More Stories By Ed Featherston

Ed Featherston is VP, Principal Architect at Cloud Technology Partners. He brings 35 years of technology experience in designing, building, and implementing large complex solutions. He has significant expertise in systems integration, Internet/intranet, and cloud technologies. He has delivered projects in various industries, including financial services, pharmacy, government and retail.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


IoT & Smart Cities Stories
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Nicolas Fierro is CEO of MIMIR Blockchain Solutions. He is a programmer, technologist, and operations dev who has worked with Ethereum and blockchain since 2014. His knowledge in blockchain dates to when he performed dev ops services to the Ethereum Foundation as one the privileged few developers to work with the original core team in Switzerland.
Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a mul...
Whenever a new technology hits the high points of hype, everyone starts talking about it like it will solve all their business problems. Blockchain is one of those technologies. According to Gartner's latest report on the hype cycle of emerging technologies, blockchain has just passed the peak of their hype cycle curve. If you read the news articles about it, one would think it has taken over the technology world. No disruptive technology is without its challenges and potential impediments t...
If a machine can invent, does this mean the end of the patent system as we know it? The patent system, both in the US and Europe, allows companies to protect their inventions and helps foster innovation. However, Artificial Intelligence (AI) could be set to disrupt the patent system as we know it. This talk will examine how AI may change the patent landscape in the years to come. Furthermore, ways in which companies can best protect their AI related inventions will be examined from both a US and...
In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
Bill Schmarzo, Tech Chair of "Big Data | Analytics" of upcoming CloudEXPO | DXWorldEXPO New York (November 12-13, 2018, New York City) today announced the outline and schedule of the track. "The track has been designed in experience/degree order," said Schmarzo. "So, that folks who attend the entire track can leave the conference with some of the skills necessary to get their work done when they get back to their offices. It actually ties back to some work that I'm doing at the University of San...
When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...
Bill Schmarzo, author of "Big Data: Understanding How Data Powers Big Business" and "Big Data MBA: Driving Business Strategies with Data Science," is responsible for setting the strategy and defining the Big Data service offerings and capabilities for EMC Global Services Big Data Practice. As the CTO for the Big Data Practice, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He's written several white papers, is an avid blogge...
Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Building the Future of Monitoring with Artificial Intelligence. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more busine...