The Internet of Things (IoT) is here. Already, there are hundreds of millions, even billions of IoT devices out in the world. Despite their ubiquity, many people are still confused about what IoT is. It’s basically any device that is connected to the internet via a wifi or Bluetooth connection for the primary purpose of gathering data. Most people will think of smartwatches or Fitbits that mostly track health data. However, the IoT is made of much, much more than that. IoT devices can include anything from a connected refrigerator to a drill that lets you monitor its battery life from your phone, to a big tractor harvesting crops in the massive industrial farms out in the plain states. These kinds of internet-connected devices will only continue to proliferate in the years to come. One may wonder why they are becoming increasingly common. Why are companies so focused on making them and why do people want to spend their money to get them?
The reason companies are busily cranking these things out is simple, they recognize that data has value and are trying to collect as much of it as possible. What will they do with all of that data? In a lot of cases, they don’t even know. Indeed, this is part of a much larger problem. But we’ll get back to that.
For the people on the other end of it, the individuals shelling out their shekels for these widgets, there are several different motivations. One of course is just having the new thing, which for some reason still motivates a lot of people. More practically, the connectivity has various uses. The many different health trackers for example keep track of basic information like heart rate, blood pressure, amount of physical activity, how much you sleep and so forth. Having that kind of information constantly tracked and recorded can be a very effective tool when it comes to improving your health. With an IoT fitness tracker you can see what the effects of a change to your diet or exercise routine are and see that very quickly, allowing you to evaluate and modify those changes.
In more mundane matters, your IoT toaster can let you know when your Pop-Tarts are done if you wandered outside after putting them in. Or your fridge can let you know that it’s time to buy new eggs, or throw out the ones you bought two months ago because it turns out you don’t like making eggs for breakfast that much.
What about that problem we had to get back to? Too often, people think that just recording and hoarding data is all that needs to happen. That somehow if you just have a constant stream of information coming in, that will help you make better decisions. But having servers full of ones and zeroes helps no one. That data needs to be processed and sorted. That means you are going to need some algorithms to help you do that. Where companies fall short is thinking that the algorithm is always accurate. In reality, it is based on various assumptions that may or may not be true. Sure, you can track the results of decisions made based on the information those algorithms provide to see if they are in fact accurate. However, that might be very time consuming and costly. Why not go to the source? What not get to the ‘why’ behind the data? That will help you validate your algorithms faster and even develop better ones in the first place.
The TARTLE data marketplace provides companies with the ability to do exactly that. By signing up as a buyer, companies can get in direct contact with the audience they want to reach and learn from them why they made the decisions they made. It also works as the world’s most effective and reactive suggestion box, allowing customers to give their feedback directly to a company to help build better products and services. In the end, that benefits both the companies and the customers. One gets a better product and the other gets a better bottom line.
What’s your data worth? Sign up and join the TARTLE Marketplace with this link here.
t’s basically any device that is connected to the internet via a wifi or Bluetooth connection for the primary purpose of gathering data. Most people will think of smartwatches or Fitbits that mostly track health data.
Speaker 1 (00:07):
Welcome to TARTLE Cast, with your hosts Alexander McCaig and Jason Rigby, where humanity steps into the future and source data defines the path.
Alexander McCaig (00:24):
Well, happy Monday. Welcome back to TARTLE Cast here, talk about the daily news. Let's talk about something obvious that this CEO was talking about. I guess he was sounding intelligent on something that's a very linear thing of cause and effect here, but yeah, go for it. Let's talk about IOT devices.
Jason Rigby (00:40):
Alex. Alex, I'm so excited about IOTs. They are my favorite things.
Alexander McCaig (00:45):
Yeah, IOTs.
Jason Rigby (00:45):
Yeah. IOT's.
Alexander McCaig (00:46):
IOT, IOT.
Jason Rigby (00:47):
And you have it up on Wikipedia here. Internet of things. It they're very simple.
Alexander McCaig (00:51):
Yeah. It's a physical thing that can either be on you or on other items. Other widgets that actually links them up to the internet through Bluetooth connection or a wireless card.
Jason Rigby (01:04):
And we will see more of these IOT devices. Pretty much anything, any appliance or anything that you have, not just wearables. We always think of Fitbit and stuff like that, but you're going to have a refrigerator is telling you that you normally purchase this. You purchase these eggs and you run through them every week you go through six eggs a day. So in turn, all this data is going to be processed and then it's going to automatically order them through whatever.
Alexander McCaig (01:32):
Yeah. The difference now is it's going to be behavior that's not analyzed through online systems. It's going to be behavior that's analyzed through digital interactions with your everyday things.
Jason Rigby (01:43):
Yeah. Which I love, because I think it's going to create... IOT devices to me in a positive way, or it's going to create efficiency.
Alexander McCaig (01:51):
Oh, it's going to create a lot of [crosstalk 00:01:53].
Jason Rigby (01:53):
Because it's going to be able to pattern our movements. I mean, just think of it with the refrigerator, how much food does, especially in first world countries. How much food is being thrown away because, Oh, I think I want that. And then you decide you don't want it.
Alexander McCaig (02:06):
Right.
Jason Rigby (02:06):
We pretty much eat the same things over and over.
Alexander McCaig (02:08):
What if it could just tell you ahead of time, don't buy that because you never eat it all the way.
Jason Rigby (02:11):
Yeah.
Alexander McCaig (02:12):
Or buy less of it.
Jason Rigby (02:13):
Yeah, exactly. Why are you putting this in your pantry? Because six months from now, you're going to get rid of it.
Alexander McCaig (02:17):
Yeah, The simplicity of analyzed behaviors will be increased because now you have the ability to pull data from everything that you interact with rather than just going on the computer and interacting with systems, which is a somewhat limited world.
Alexander McCaig (02:28):
And now when you expand it beyond the computer and you put it towards everything, even if there was an IOT device on this microphone, or there's an IOT device on my Ember coffee mug. What temperature do I like to keep it at? Well, that sends it off the Embers. They can track averages to see that people really like it at this or do they want it warm? How long are they drinking their coffee for? Things of that nature.
Jason Rigby (02:46):
Yeah. And, it's only going to help us, not just with efficiency, but like food supply chains, all that.
Alexander McCaig (02:55):
Yeah.
Jason Rigby (02:55):
I mean, and then once we incorporate which, I mean, it's a big, huge web, but once we incorporate blockchain into that. Once we have blockchain with IOT devices. Now we're going to see these eternal, if you want to use the word, eternal ledgers.
Alexander McCaig (03:10):
Of learning.
Jason Rigby (03:10):
Yes.
Alexander McCaig (03:11):
Which is super cool.
Jason Rigby (03:12):
Yeah.
Alexander McCaig (03:12):
So any machine learning, deep learning algorithm, anything that goes in there, we'll be able to analyze the entire chain. The provenance of that data to say, wow, look at these behaviors. Look who it really came from. It was not manipulated, something interesting is actually happening in here.
Jason Rigby (03:27):
Yeah. Because like you said, you're evolving it from a computer screen, a TV screen. You're moving beyond the screen.
Alexander McCaig (03:36):
Now you're moving it more towards the person in an observational sense and their interactions. But the one thing that IOT hasn't touched yet is your thoughts.
Jason Rigby (03:44):
Yeah. You know, Musk is working on that.
Alexander McCaig (03:47):
Just because, yeah. Well observing it, right?
Jason Rigby (03:49):
Yeah.
Alexander McCaig (03:50):
I can put my hand into the fridge and do all these things and it can analyze it. But until I specifically say why I am doing that and explain that emotional state, there's only so much IOT can observe and record.
Jason Rigby (04:03):
Well, that's where TARTLE marketing comes in.
Alexander McCaig (04:04):
And that's where TARTLE comes into this. And it said, Oh, with the data package.
Jason Rigby (04:08):
Oh, we've noticed that 11 o'clock at night, you always grab something sweet, why?
Alexander McCaig (04:12):
Yeah, why are you doing that?
Jason Rigby (04:13):
Oh, you work nine hours today. So when you work seven hours and you get eight hours of sleep, you don't reach for things that are sweet. Or you don't grab that alcohol.
Alexander McCaig (04:22):
That's precisely correct. The cool part of a TARTLE marketplace and this Eseye. I don't even know what their brand name means, but if you're looking at the TARTLE marketplace, yes, you collect all that IOT data, right. You can pull that down, all the devices and stuff you interact with. And then you can pair that too, with things of an emotional state. Things of the cognitive explanations of your state. Why are you doing things, those thoughts, and now you have a really firm rooted picture about what's going on. So if we talk about advancements in healthcare. So I can observe the biological markers on a person and also understand the choices they are making that are driving these biological markers.
Jason Rigby (05:04):
Yes.
Alexander McCaig (05:05):
And then beyond that, why is there pollution in a river in India? Yes, I'm seeing the interaction of trash going in here, but now I need to ask why. So it's one thing to observe, and then it's another thing to understand. Observe first, understand second, but they both have to come together so you can be wise about what you're doing. We can relate that research.
Jason Rigby (05:24):
Yeah, and you know as well as I do Alex, the observing part is we've gotten good at, observing data. The passive aggressive hunches that we're dumping into our machine learning is where we're bad at understanding the why.
Alexander McCaig (05:40):
We're so bad at asking questions.
Jason Rigby (05:42):
That were off.
Alexander McCaig (05:43):
Yeah.
Jason Rigby (05:43):
I mean, you can see it, and I'm not picking on anybody. But the Republican Party was way off this year.
Alexander McCaig (05:49):
Yeah.
Jason Rigby (05:50):
In their whole idea. Whether you look at Trump or not, 2016 was perfect. You had a disruption, you had this guy that was kind of mesmerizing, reality TV show guy, whatever, super narcissistic, looked like he was a business guy. I think we're tired of the same old, same old. So let's move in this direction.
Jason Rigby (06:09):
Then you come on this scene now, and that party is just so out of touch with the truth of reality. And so old school, both of them are to be honest, but it's like, you guys need better data.
Alexander McCaig (06:23):
Hard mail polling and Nielsen reports for people watching TV does not tell you what's going on.
Jason Rigby (06:28):
No, let me give you a 50 dollar bill.
Alexander McCaig (06:29):
Because when you're observing, it's still telling you that your algorithms suck.
Jason Rigby (06:32):
Yes, yes.
Alexander McCaig (06:33):
Because you haven't figured it out.
Jason Rigby (06:34):
Yes.
Alexander McCaig (06:34):
So let's get the other part of the picture. So it can actually check your algorithm.
Jason Rigby (06:37):
Yeah. You need, and he gets into this.
Alexander McCaig (06:40):
Who's he, what's the guy's name? We'll give him a shout out to his first step of logic on that.
Jason Rigby (06:44):
Yeah, it is. Let me make sure it's E-S-E-Y-E is the company, and then this just says editorial team.
Alexander McCaig (06:53):
[inaudible 00:06:53].
Jason Rigby (06:53):
Editorial team.
Alexander McCaig (06:53):
There's a quote, what's the quote in there? See the quote? It says, blah, blah, blah, see-
Jason Rigby (06:57):
Nick Earl CEO of Eseye.
Alexander McCaig (06:59):
All right. Thanks, Nick Earl.
Jason Rigby (07:01):
Yeah. IOT companies that see the potential, not just in the devices, but also data collected will be the big winners.
Alexander McCaig (07:06):
All he cares about is data collection.
Jason Rigby (07:07):
Yeah.
Alexander McCaig (07:08):
Whatever buddy, the big winners are not going to be people that collect more data. The big winners will be the people that take data and use it to effectuate on things that are important, like the big seven. Big winners are not the people that hoard more resources. Big winners are the ones that take action to help humanity. So what's this guy's name, Nick?
Jason Rigby (07:28):
Yes.
Alexander McCaig (07:28):
Yeah. Get your thoughts straight, that's not straight.
Jason Rigby (07:30):
Yeah. If you're not taking the responsibility, one, to the person that's giving you that data, because if you're taking it out of their free will, that's wrong. But if you're not taking that responsibility of all the billions and billions of bytes of data that you have, and you're not saying, how can we use this responsibly to help humanity?
Alexander McCaig (07:55):
You're doing something wrong. He's only thinking in quoting in the economic sense, lame.
Jason Rigby (07:59):
Such short term mentality.
Alexander McCaig (08:01):
We have bigger problems than your profits. Yeah. [inaudible 00:08:09] out of here.
Speaker 1 (08:18):
Thank you for listening to TARTLE cast with your hosts, Alexander McCaig and Jason Rigby. Where humanity steps into the future, and source data defines the path. What's your data worth?
