Key wearables use cases

Key use cases for wearables

I want to talk a bit about some of the benefits and key use cases solved by deploying wearables, especially smart glasses, into the field force environment.

Right now, I’m working across a multitude of industries, including Oil and Gas, Resources, Mining, and Aerospace, and I’m consistently seeing the same use cases crop up.

Primarily, these use cases relate to building a more efficient and effective workforce.

Today, workers in the field depend on either paper instructions, which can be easily lost or damaged, or digitized instructions, which require the worker to take their eyes and hands off of their work.

Smart glasses are changing this by providing the ability for workers to access comprehensive work instructions in a hands free way.

The main use cases I’m seeing are
Over the shoulder coaching
Providing remote expert capability, where a worker in the field can call an expert across the world and show exactly what the problem is by using the device’s video camera. By tightening the feedback loop, field force workers can do more by leveraging expert resources

Visual work instructions
Guiding workers through complex tasks by providing a means to navigate complex instructions leveraging text, pictures, movies, and 3d models. By enabling a lessor skilled worker to do more advanced tasks, companies can save big money while still improving work force effectiveness.

Procedural checklists
Imagine being able to not only view checklists in a digital medium, but also automatically update backend systems with completion information, photos, and annotated information. Smart glasses are providing the means to ensure tasks are completed, and create a level of accountability by recording all the necessary information. Gone will be the days of lost/neglected paper forms.
In a later blog, we’ll talk about how AR and VR are starting to play a big part in these solutions

Hololens Everywhere!

A Look at Microsoft Hololens

Microsoft’s Hololens is the newest device on the block in the Augmented/Virtual reality space. We were lucky enough to not only get our hands on one device, but 3 devices, allowing us to play in sync with the world around each of us.

 

Dave Arendash (@thatvrguy) joins me as we talk a bit about how groundbreaking this device it. Dave has over a decade of experience in AR and VR work, and has seen and used practically every device on the market, so I trust him when he says “WOW, in the last 24 hours my job just completely changed.”

Truth of the matter is, I’ve always been skeptical at AR and VR solutions. They seemed clunky, and difficult to deploy, especially at scale, but with the Hololens, all of that seems to be changing. In a matter of minutes, we were able to stand up almost all of the key wearables use cases, without writing a line of code.

Alright, enough of me talking, let’s watch.

 

Enterprise wearables

Enterprise considerations for deploying wearables

Enterprise considerations for deploying wearables

Wearables are following closely behind the trend of mobile devices, and starting to make it’s way into the enterprise environment. Since the mobile device market has matured, and things like smart phones, tablets, and BYOD initiatives are becoming common place, companies are well poised for the surge of wearables.
Or are they?

Truth is, wearable devices such as fitness trackers, smart watches, and smart glasses, pose a slew of new risks to enterprises.

Now, mobile device management is more about protecting the companies sensitive information on an employees cell phone. But now, companies also need to consider protecting the employees information from misuse!

Let’s stick to 4 main areas of concern for now

– Information leaks – Smart glasses in particular, all carry cameras built in to the device. Yes mobile phones also have cameras, but it’s pretty easy to tell when someone is taking a photo with their phone, or have employees drop their phone off before entering secure areas. Smart glasses on the other hand…. There really isn’t any physical means of telling when someone is discretely recording on the device, and if the worker is using a pair for their job, then you can’t really just take the device away. All of the available recording capabilities enable wearables to secretly collect information, and from there, who know’s who’s hands it will get into.
– Security attacks – Many new smart devices lack the ability to do multi-factor authentication. In fact, most of these devices are supported by major MDM providers either. That means, in order to provide network access to these devices, you security measures NEED to be lowered. It only takes one device to become compromised and start leaking the data mentioned above.

– Loss of Personally identifiable information (PII) – The National Institute of Standards and Technology (NIST) defines PII “as any information about an individual maintained by an agency.” Say wearables are being leveraged in the hospital setting. Patient information being stored on a device that is lost immediately puts the patient at risk of being exposed. Or, another example would be an employee losing their smart watch which is unlocked, exposing things such as emails and calendar entries.

– Violation of privacy – With the ability to collect all sorts of statistics about the health and even activities of employees and customers, it’s tempting to start running analytics and coming up with all sorts of metrics that can be used to base decisions on. Not only can this lead to a slew ethical issues, but the National Labor Act actually requires that any data being collected on employees and used for performance decisions be completely transparent with the work force. That means no secret snooping.
So whats the salient point here. Wearable technology poses new risks, and if your company is looking to start deploying these devices to the workforce, you should spend the time necessary to ensure the right policies, procedures, and governance is in place.

But, with any emerging technology, though not to be taken lightly, these risks should not prevent enterprises from pushing forward and figuring out innovative ways these devices can be used to improve business processes.
This material originally appeared as part of a whitepaper created by Brent Blum, and can be found at
https://www.accenture.com/us-en/blogs/blogs-are-your-wearables-safe-from-cyber-security-threats

Until next time, keep on experimenting.

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The Enterprise Internet of Things Journey

We’ve heard a lot about how IOT is changing the landscape of business, but typically, we don’t talk about HOW IOT is providing value

[Transcript]

IOT isn’t just a drop in solution, here you go, here’s IOT.
It’s a multi-phase journey, which leads enterprise to all sorts of differentiated opportunities.

For me, there are 4 key steps to the IOT journey
Monitor
Control
Automate
Predict

So let’s break these down
Monitor – Gathering, logging, and reporting real-time, or at least near real time data from different people, equipment, assets, etc, enables enterprises to get a clear, comprehensive view of the status of various operations.

Control – This is one of the concepts that always excited me, being able to remotely activate various pieces of equipment, control assets, and essentially use technology existing in the virtual world to control the physical one.

Automate – Creating rules and processes around the data, and being able to use these rules to remove the human element from the workflow process. Machines that can control machines

Predict – This is where it gets interesting. Now we’re into machine learning, where complex algorithms begin looking at large data sets, figuring out paterns and markers which we may not even know to look at (for example, sensing a vibration on a engine along with a minor spike in temprature may predict an impending failure). Now we have machines thinking about how the world works
The challenges here are many. But some of the key challenges are around identifying the right value levers, and being able to create robust cost benefit models for an IOT solution. It’s very complex, and a hard pill to swallow for companies looking to roll out these types of solutions.

In a later blog, we’ll talk about how IOT and Wearables play together to create a holistic enterprise solution.

IndustrialInternetWordle

Industrial Internet Primer

Industrial Internet Primer

During my time in St. Charles last week, I had the opportunity to network with both new and experienced Accenture team members. While having conversations with both analysts and leadership, I noticed a trend when speaking about Internet of Things, many people have heard the term, but a large number of them were mostly unsure about what it means.

So I’d like to take a step back from the technical details, and get in to some quick basics about Industrial Internet of Things.

Converging technologies

The term Internet of Things actually spans multiple technical disciplines. These technologies include things like analytics, big data storage, wireless networks, proprietary hardware sensors and gateways, API layers, dashboards, and more.

 

Leveraging data

One of the premises behind IoT is to automate the process of collecting of data and pool this information into systems which can speak to each other. Where information was previously collected by disjointed systems, sometimes involving manual recording, or simply not collecting data, IoT pushes towards near real time data collection in an environment where multiple data sources, once not related, can be combined and analyzed for patterns.

Extracting Value

The goals of IoT include

–          Helping move companies from being reactive (in the case where something breaks and now it needs to be fixed), to being proactive (for example, relationships can be found between data points which can trigger maintenance tasks before downtime is realized)

–          Creating new revenue streams by productizing the data through new service offerings, for example, rather than selling machinery as a one-time product purchase, companies may begin to offer machinery for free, and then sell subscription services to maintain and ensure efficiency of the machinery.

This move towards Products as a Service has the potential to trade upfront sales for sustained revenue, which over time can result in higher ROI than by single sales alone.

Looking forward

As more and more levels of infrastructure are becoming connected, the importance of the collected information and the value that can be extracted from this data grows immensely. When we talk about Internet of Things, we talk about equipping infrastructures, companies, and services with more up time, lower cost of operations, and new opportunities for recurring revenue streams.

This has been a very quick, high level look at the Industrial Internet of Things. I’m sure you can tell, the concepts can get extremely technical, and cross many different technologies. If you are working on proposing an IoT style project, be sure to consider the fact that it is unlikely to find a single individual equipped with all the skills required for a successful deployment.

BeagleBoard Modular Gadget Angled Shot

The resurgence of the at home gadget hacker

The resurgence of the at home gadget hacker

A really cool thing happened to me the other day. On a chilly weekend, I decided to warm myself up by going inside a nearby mall, which if you read in to my history, you’ll know I have a long relationship with malls, and while there, I ventured in to a RadioShack.

Sadly, over my relatively short lifespan, RadioShack has been facing a bit of an… Identity problem. I remember when I used to go in to RadioShack for help with my robots, and the techs would go over the circuits with me, resistor by resistor, identify the problem, and together we would fix it. Now, they push more cell phones then solar cells.

But, to my immense happiness, I came across something wonderful, a whole isle dedicated to Raspberry Pi and Arduino starter kits, and much more in terms of robotics kits, books , and sensors.

It’s finally come, the resurgence of the at home gadget hacker.

But something is different. 10 years of technology advancement has brought technology previously unobtainable (without paying a hefty price), down to the hands of an 8 year old. Now, kids, and kids at heart, can play IoT – The home version!

With the cost of device hitting laughably low prices, you can get a fully functional micro-computer, with WiFi, for about $40. It’s becoming more feasible to connect everything in your house.

Have an old TV? Attach a smart system to it!

Want your coffee made in the morning? Attach a smart system to it!

Have a leaking pipe? Call a plumber!

I decided it was time for me to get back in the home brewing game as well, and went over to Adafruit to pick up the latest Raspberry Pi B+ kit.

Over the next couple weeks, I’m hoping to come up with some new project which I’ll be sharing right here, perhaps even during one of the brown bag sessions.

Stay tuned, and share some of your own homebrew creations!

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Driving analytics from IoT signal Exhaust

Driving analytics from IoT signal exhaust

Introduction

This is going to be a short exploration in to the world of data collection and “signal pollution”. The goal of this article is to provide real world examples of using passive signal scanners to collect and derive information from the gadgets and devices people are already wearing.

What is [I]IoT

IoT stands for Internet of Things (IIoT being Industrial Internet of Things), and involves deploying internet connected devices and sensors to people, products, equipment, etc., with the intent of having these devices report data back to a central location. This data is then used for driving decisions, for example, a temperature sensor can send real time temperature information to a server, which then can trigger alerts, or even reduce heating elements without requiring user interaction.

What is signal exhaust?

Pollution, typically speaking, is easy to see. A truck drives by, and you see the smog coming out of the exhaust pipe.

Radio operators, and network engineers, will be familiar with term signal pollution, the invisible noise that comes from connected devices, microwaves, cordless phones, and other broadcasting devices. This signal pollution, or signal exhaust, comes from many types of devices, and the number is growing with more and more devices becoming ‘internet aware.’

Just like smog fills the atmosphere, signal exhaust fills the surrounding area with noise, which, with the right equipment, can be collected, and harnessed.

How to leverage

Today, consumers are loading themselves up with an ever increasing number of wireless devices. These devices are all broadcasting, and although the literal information may be encrypted, you can still pull some important data from all of the noise.

Using specially tailored listening devices (which can easily be an open source router, or a specially purposed Raspberry Pi), you can pick up these stray signals, and uncover certain device specific information such as hardware ID, software information, maybe even what the device is. From this information, we can start analyzing trends such as device density and location, how many times a device reappears after leaving, proportion of people using a specific technology, and much more.

Use case

I can think of several use cases for this type of information, but the one that really stands out is consumer identification in the retail industry.

Retail chains are making a big push to be able to somehow link online consumers to brick and mortar consumers. Lots of different methods are being deployed, including collecting email address, linking rewards cards, etc.

But this requires the shopper to provide additional information, and doesn’t help figure out who is looking in the store, and then shopping online.

Perhaps this information could be better inferred by passively tagging consumers by their device.

For example:

Let’s say a customer comes in and makes a purchase. You can pick up their unique cell phone identity, and link this information to the purchase. Chances are, you’ll also pick up a few people around your target customer, so the data is not completely accurate on the first go around.

Some time later, the customer comes in and makes another purchase at another store. Suddenly, you have two data points, again there will be some unwanted information from other customers, but, by cross referencing similar information between both events, and you’ve suddenly targeted a unique customer.

What can you do with this information?

Lots! Special offers at the counter, tracking repeat customers, even track the customer behaviors through the store!

I would call this ‘soft data’, because the information is being inferred through deduction, rather than coming from a rock solid event.

Black hat

Privacy, Privacy, Privacy, Privacy!

I hear the screams coming from every direction, and it’s definitely a major concern.

Back when I ran a chain of retail stores and deployed this type of passive data collection, we made sure to never collect personally identifiable information, unless that was voluntarily offered to us through captive portals (another topic all together). Incoming data was securely stored by our vendor who only provided us with a non-identifying, unique customer key, which information about repeat visits, durations, and sales conversions.

But the line is thin, and you need to be careful about what data you collect, and how you are using it.

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Operationalize your IoT development

Operationalize your IoT development

Regardless of the hype you are hearing about the new wave of Internet of Things, one fact remains true, the staggering variety of different use cases and hardware required for implementing a full fledged IoT solution presents a large challenge.

As a result, a significant amount of effort ends up going to new code development, and one off solutions. Let’s face it, there isn’t a chance that in the near future, all these different technologies are going to be standardized. And because of this, development and integration costs will remain a large factor in the cost of IoT solutions, reducing competitive edge, and keeping prices high.

But what if you could change that…

During Philly Tech Week, I was fortunate to catch a talk with Bulogics about these exact challenges.

The two key points to take away are

Create modular code

This isn’t a new idea, by far. Development shops have been creating libraries of existing code bases for years. But, as embedded programming, the type that runs IoT solutions, becomes more mainstream, SI’s can benefit from taking the concepts of modern development practices, and integrating them in to their own processes.

Modular coding requires breaking the entire program into smaller, independent, routines. These routines can they be used, and reused, something common in Object Oriented Programming, but not so much in embedded.

Now add documentation, and store in a code library, and all of a sudden, you have a set of reusable, function specific, code. Code that doesn’t need to be redeveloped, only customized.

Automate your embedded testing

This is something I’m most excited about. For the past several years, we’ve seen an explosion of testing frameworks for front end web development, enterprise applications, mobile development such as Android and iOS, etc. By borrowing some of these higher level language concepts, we can further automate our embedded solution development.

Some points to keep in consideration about embedded platforms,

  • They are memory constrained
  • They are usually single function devices

This result is, it’s very difficult to load your tests in software on a device. But there is hope! Specific testing frameworks, such as Unity and Ceedling allow you to detach code from the hardware, and perform tests without continually re-flashing the device. In fact, you can test code without the device at all. Once successfully tested, this code can be loaded on a multitude of hardware platforms with minimal changes.

To sum things up

By building a code base, and automating testing, SI’s are more able to create better hardware solutions, requiring less effort, and turning around deliverables in a shorter time-frame. The automation of testing ensures better quality (assuming the tests are written correctly), and can help bring solutions to market faster, cheaper, and respond quickly to market demands.

Now go operationalize your efforts and stop reinventing the wheel!

 

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Transforming field force with wearables

Field force resources represent a massive cost to infrastructure providers. Not only are the out of pocket expenses for sending experts into the field high, but after adding in the time it takes to mobilize, travel, and repair issues, the lost revenue resulting for service interruptions could be massive.

The term field force refers to the experts and technicians that go out and perform both routine and emergency maintenance on equipment in the, you guess it, field. Logistically, you can’t always predict when and where experts will be needed, and many times, it is not cost effective to keep SME’s on hold.

Oil and gas companies have it especially difficult. Out at sea, oil rigs may be staffed with as few as a couple dozen people at any given time. When something goes wrong, really wrong, and the rig is shut down, experts need to be flown in, sometimes resulting in costs upwards of $60,000 a day!

This is where field force optimization comes into play. Enterprises are already equipping resources with tablets and applications which improve ticket issuing and resolution, but this is only one step towards the goal of achieving a Zero Labor Model. What if, you didn’t need to send experts to the field? What if you could guide less experienced technicians through more complicated tasks.

Here is where the power of wearable technology comes in. Smart glasses, such as Google Glass, are uniquely equipped to solve the key challenges facing today’s field force

  • Ticket issuing
  • Guided procedures
  • Over the shoulder coaching

Using platforms such as APX Labs Skylight, enterprises can easily locate and issue support tickets to the nearest technician, providing step by step instructions for completing the task, as well as enable the technician to video call an expert for advice in real time.

By creating these quick feedback loops, technicians can get more done, in less time, at a significantly lower cost than sending SME’s on-site to make the repair. Wearable technology is here to stay, and we are seeing the industry shift towards rugged, field ready, enterprise grade devices.Enabling the field force to do more with less, is a huge leap towards our goal of Zero Labor, one that should not be taking lightly, but at the same time, can provide an enormous return on investment.

If your company is managing a large field force, maybe it’s time to start thinking about ways to optimize your processes and maximize the returns on your field force resources.

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Security:The Ugly Side of IoT

A few weeks ago, we watched as two hackers took control of a Jeep Cherokee remotely through the wireless info-tainment center. Not only could they control the radio, but the door locks, steering, brakes, and practically every other system fell powerless under their commands.

Between connected devices, and automation systems which depend on accurate data, there are numerous points of vulnerability where a malicious attack could take place.

IoT presents a unique challenge, with multiple standards in all layers of the IoT stack, simply addressing this issue in a single layer, say gateway to gateway communication (think MQTT), there is still the possibility of attacking other layers, say sensor to gateway communication, which many times rely on simple electrical signals communication with an edge device.

In this article from Windriver (http://www.windriver.com/whitepapers/security-in-the-internet-of-things/wr_security-in-the-internet-of-things.pdf), we are taken through various layers of the IoT architecture, and presented with the different key concerns facing enterprises (and all companies implementing connected solutions), as well as some of the way’s these vulnerabilities are being addressed.

The bottom line is, security should be on the forefront of any IoT project plan. Even in a proof of concept, critical information can be leaked, whether it is personally identifiable information, protected information, or even proprietary data (re: mixing procedures during chemical fusion processes).

The Jeep Cherokee hack won’t be the last, and it definitely wasn’t the first, just do a Google search for unsecured web-cams and you’ll get a taste for just how lax we are with securing our devices. If your company is embarking on an IoT project, or already has one in place, it’s most likely time for a good physical and network security audit.

 

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