Not only Police Officers need in-vehicle communications…

Imagine a traffic stop, in the middle of the night.  The officer gets out of their car and approaches.  When they get closer, they see a distressed looking Mom, with her two kids in the back seat.  She has just made a right hand turn when they were not permitted.  I think all parents have been there…kids crying, you’re lost.  The officer thinks, "I should give her a break...she's having a tough day."

Wouldn't it be great to know that the woman just kidnapped the kids at gunpoint?  Would he approach the situation a bit differently?

I think everyone can understand the value of a police officer having such information, but I'm not sure why we don’t see value in many other remote workers having it as well. When you have more information, you make better decisions, regardless of what your profession is.

There are three parts to a potential in-vehicle communications offering:

1. Getting information to your remote workers

There are many ways to do this, actually.  Most workers carry some sort of smartphone, so you can always text or email them, and many have a laptop or tablet so they can visit the nearest Starbucks to get WiFi access…

However, for many organizations, it make sense to have some sort of screen allowing real-time access to/from the vehicle.  Giving them warnings via a real-time experience is vital for many, as is being able to use the screen for dispatching.

2. Getting information from the vehicle

In this case, the remote worker is not involved at all, actually.  This solution involves retrieving key information for the dispatcher about what is going on with the vehicle, and potentially with the driver.  Is the worker driving recklessly? Did they leave a security door open?  Did they press a panic button while being attacked?  Are they out of their area?  Whatever the reason, knowing what is going on can be vital to the safety and productivity of your remote staff.

3. Giving Internet access to the passengers

Let’s face it, riding the bus is not a choice that many people make willingly.  Sure, some do, but most people would prefer to use another mode of transportation.  Many forward-thinking municipalities are using WiFi on-board to encourage ridership.  As well, some taxis are now offering on-board WiFi as a way to fight the influx of Uber into their space.

The Bottom Line

The great thing about these solutions is that all three offerings are available at the same time, or you can purchase individual solutions for any of them.  This allows you to better keep your fleet of workers moving, which is good for your bottom line and their safety.

If you are interested in hearing more about how IoT solutions can help Transportation companies, click here for a link to our webinar...

The Trump Effect: What else might Big Data get wrong?

Trump Effect

I remember reading about how poorly a Windows 95 trial group was doing with their early copy.  It seemed that they could not figure out why computers were crashing so badly and why users were complaining so much.  It turns out, it was a difference in the assumption of how it would be used vs. how it was actually being used.

The engineers who had designed the product had made the assumption that since they always followed the same procedure of properly shutting down the PC that all users would.  Users, on the other hand, had just gotten used to turning things off, like how they turned off their TV.

In this case, the assumptions used were incorrect, producing wildly different results.  In a way, this is sort of the same thing that badly missed forecasting a Trump victory….all big data calculations have some assumptions built into it, and when the underlying assumptions are wrong, things can be a lot different than forecasted.

In the case of IoT, this can be a huge issue

One of the things that most people who like numbers (like me) find appealing is the relative predictability.  The numbers are always the same as are the formulas.  However, two people may look at the same thing, say an investment based on numbers, and come up with a totally different prediction.  While the underlying math does not change, what does change is the assumptions…..will the market be hotter than expected, might their be a change in the economy, stuff like that.  When you take those things into account, it makes sense that there is a huge possibility for differences in opinion and a wide variance in potential outcomes.

Take a traffic system….The traffic patterns of a city often have a relative consistency to them.  So, at 8 am each weekday morning, the traffic picks up, so the traffic lights will stay green a bit longer in one direction to better handle the traffic and at 9 am, they go back to normal.  Under regular conditions, this pattern works well…but what happens when an unexpected variable happens?

What if there is a water main burst, forcing traffic in another direction?  What if a school changes its start time, forcing hundreds of cars into an earlier time slot?  What if construction changes the pattern by slowing down drivers up the road?  Some of these changes are short term but others may have a longer impact…

When you add these things in, your first assumptions may be wildly off, or they may not make a noticeable difference.  This is the problem with Big Data…..we can be perfectly precise when the data has no variables, but little in life is like that. 

This is the case with Trump’s win….models were based on traditional levels of turnout by certain demographics, but in this case, Trump’s supporters turned out much more than expected and Clinton’s turned out slightly less.  When you factor those numbers in, the models would have likely had the race correctly, but that is only in hindsight.

The Bottom Line

What does this all mean?  It means that while Big Data has had some incredible impacts that have helped our day to day life, it is not perfect.  Life simply has too many assumptions that have to be made and too many variables that can happen for things to totally be run on Big Data.  In the case of an election, emotion and passion cannot be properly calculated, and it was a variable that likely might have changed things altogether.  With the correct variables, Clinton may have spent more effort in Michigan/Wisconsin, but since she relied on the models, she fatally did not…

Where CAT M may make new inroads like no technology before…

hypergrowth

As mentioned in another blog post, the world of IoT is about to truly see the hyper-growth phase that we’ve all been hearing about with the upcoming launch of CAT M.

Ok, you may ask, that is wonderful, but where might we see this growth?  What areas are going to see their adoption rate of cellular data skyrocket?  What new customers may come to the forefront that have skipped previous cellular technologies?  How do I prepare my customers / my business for this game-changing technology?

Well, I really don’t have a crystal ball, but I do have some ideas as to some of those answers…

In order to answer this, you have to look at some of the reasons why companies held back on the use of cellular data in the first place…

Expensive hardware and/or airtime  If you are Chevrolet building a car with a cost of goods in the tens of thousands of dollars, the cost of a cellular module and some airtime was not a prohibiting factor.  However for many lower costs products, it was.  While there will still be customer’s products that cannot justify the cost of CAT M, there will be many more that now can.

Too much power draw  Again, for devices that have consistent, plug in the wall power, the power usage for cellular modules was not much of an issue.  However, for battery-operated solutions, it was.  CAT M has a much lower power draw, so it may not affect the battery draw so much as to make it prohibitive…..are you listening, Apple Watch engineers??

Easier to use short-haul networks  For many companies, the idea of having full control over their short-haul networks – whether WiFi or private radio – is too compelling for change.  However, many customers opted for these networks out of the desire to reduce cost, not for the control aspect.  For these customers, the lower cost of CAT M hardware combined with the expected reduction in data charges will often outweigh the benefits of running your own network.

Four possible areas of growth

1. Large Appliances 
I have written in the past about how companies are adding WiFi to their larger appliances, mainly as a way of doing software updates and gathering information.   However, one of the issues is the fact that the end customers has to spend the time to put the device onto their home network (which many do not like or know how to do) and their ability to communicate with the device requires this device to stay on that Wifi network.  By using cellular data, the manufacturer is free to do over the air updates, gather technical usage data and better reduce issues from escalating.

2. Industrial Equipment 
To date, cellular connectivity is used in a wide variety of industrial equipment, ranging from large medical machines to printing presses to heavy digging equipment.  I see this trend continuing, namely due to two previous barriers to entry.  The first was the cost…sure, on a $300K piece of equipment, the cost was insignificant, but not so on one that sells for $600.  The reduced upfront and on-going costs of CAT M will greatly accelerate this growth.  As well, many of these devices run on battery, so the decreased power needs of CAT M make it more feasible to operate without affecting usage.

3. Personal Health / PERS (Personal Emergency Reporting Systems) 
The growth of wearables, along with personal health devices has been explosive.  For the most part, these devices have chosen to use Bluetooth or WiFi as their main communication methods.  Simply, the cost of traditional cellular and the battery draw was just too much (just look at Apple’s decision to not add cellular to the new Watch).  Sure, some devices that had to have it, such as personal trackers, do have cellular connectivity, but not nearly as many as we expect once we bring down those two barriers.

4. Current Private Short-haul Networks 
One such customer is the power and water utilities. While power companies are large users of cellular data networks, they do much more of their inter-machine communication using Bluetooth, ZigBee and other technologies.  This requires them to manage their own networks, but the decision to do so was made easy by the higher costs of cellular technology.  The introduction of CAT M, and further more with future technologies, will make the decision to stop running their own networks an easy one.  I suspect that this will be the same for municipalities, energy companies and environmental companies.

The Bottom Line

The reality is that many other industries will be quick to jump on-board the CAT M bandwagon when they understand the power and flexibility that it brings.  Our goal at Novotech is to help customers determine their future needs/plans and show them how IoT solutions can improve their business.  Let us know how we can help you!