Learning IoT and Losant

Nugeen Aftab: Hi. Thank you for joining the Deeper Dive webinar. It's now 1:02 Eastern, so we're going to go ahead and get started. My name is Nugeen Aftab and I’m the Partnerships Growth Manager at Losant. Today, we have Losant Education Lead, Taron Foxworth, who will speak about how learning IoT is similar to learning Losant. Myself and Brandon Cannaday, our Chief Product Officer will also be here to answer questions at the end. Before we get started, I want to address a couple of housekeeping items. This webinar is being recorded and the replay will be made available to you in a few ways. After this webinar, we'll send you an email with the link to the replay and the webinar will also be made available on Losant's YouTube page as well as on our Deeper Dive webpage. Throughout the webinar, you may have questions that you'd like to ask. If you do, I would like to point out a couple of key features in the Zoom conference. You can use the Q&A feature or the chat function to post questions and I’ll be monitoring those throughout the call. At the end of the call, I’ll moderate a Q&A session with the posted questions with Taron and Brandon. If you have to leave early, no worries. The Q&A will be posted as a pdf alongside the replay link. To start, let's do a quick review of Losant in our enterprise IoT platform. Losant is an application enablement platform. What that means is that Losant provides enterprises with the building blocks to create their own IoT applications. Our platform consists of five key components to help customers achieve that. Edge Compute, Devices and Data Sources, Data Visualization, our Visual Workflow Engine, and End-user Experiences. Our customers and partners utilize these tools to create the robust IoT applications they put in front of their end-users. Losant is a leader in the industrial, telecommunications, and smart environment spaces and we've offered this platform for all sorts of customers ranging from startups to companies in the Fortune 100. If you're interested in learning more, please reach out and we'd be happy to set up some time for a much more in-depth conversation. While Losant provides a software foundation for IoT, there are many other components that have to come together to create an IoT application. We've surrounded ourselves with a great ecosystem of partners. This includes strategic partners with whom we share sales and go-to-market strategies, solutions partners who work with clients to develop end-to-end IoT applications, and lastly, technology partners that can provide hardware, connectivity, and other services to complete an IoT solution. Today, we'll be discussing the IoT technology stack as a whole and where Losant fits into that. Here to walk you through that is Taron Foxworth. He'll teach you how to use this framework to build your application in the world of IoT and in the world of Losant. So, at this time, I’ll let him share his screen and get started.

Taron Foxworth: Thank you, Nugeen. Just to soundcheck first, how do I sound?

Nugeen: You sound great, Taron.

Taron: Awesome. Sharing my screen now. Sweet. How's that?

Nugeen: Looks good.

Taron: Awesome. Thank you all so much for joining with me today. This presentation is very personal to me. Years ago, when I joined Losant, I was handed a microcontroller as a part of my onboarding and that set me on the journey to learn about IoT and technology that I’m super excited to share with you today. Really, after countless webinars that I’ve given and listened to from the team, workshops trainings and even going through Losant University, I think now we have a really good framework to help you understand IoT and help you understand Losant as well. I like this process because this is our proof-of-concept process. So, our customers who work with our solutions team, they go through this process and this allows them to come out on the other end, successful. Today, we're going to be focused on the divine and develop part because when we're talking about learning IoT and learning Losant, this is where we're focus. To kind of get your head wrapped around what we're fitting in the process, that's where we are today. If you've seen any IHE presentation within the last three years, you've probably already seen the study. It's very commonly quoted. Cisco did the study. What they found was that 3/4 of all IoT projects are failing. The entire purpose of the study was to figure out what was those key factors that caused the failing. Three of the things they pulled out were some things that we already know and love. For example, collaboration between IT and OT or just the technology behind IoT itself. But it's this third point that I found very interesting. It was IoT expertise. 48% of the factors were around IoT expertise and that's huge. Though this study was from such a long time ago, I still think we see this today. This is a huge problem in the success of an IoT project. I think by learning these things and by developing this IoT expertise from a foundational level, we can really accomplish some cool things. The three things I hope you take away from this presentation. First is, I hope you get a nice solid IoT foundation that you can use to talk about IoT not only to your customers, colleagues and clients. Next, is the ability to ask the right questions. Every time we approach a project or we see a project or we get this new information, we ask ourselves very similar questions and my hope is to give you that foundation today. Lastly, the hope is to gain that IoT expertise. So, not only do you have that within a partner in Losant but you also have that internally within yourself and you come together again, to make some pretty cool things. Why this is all important? Personally, I have the lucky opportunity to meet with all of our wonderful customers and partners to learn about their use cases and what they're doing in the world of IoT. Really, this presentation is me giving the information back to you. What you'll notice is that this is the same tools that I use to actually train our team members here within Losant. This Deeper Dive, the Deeper Dive, this is insight into how we're gearing up to educate you as our customers and partners. Along my journey, I found out one key thing and this was the best realization ever. As we learned about IoT, my knowledge of Losant increased and as I learned more about Losant, my knowledge of IoT increased. On the surface level, this is pretty obvious because we're a platform dedicated for IoT but going through that process, I really felt like it was valid for me to point that out because all the IoT concepts that I was learning, whether in news or through use cases, all helped gain my knowledge about Losant and the features that we offer and why, and vice versa. They tell a great story when you think about them together. To begin our conversation, we're going to start at the Define stage. In here, let's start from the absolute very beginning, the definition of IoT itself. In this case, here's a tweet from our Chief Product Officer, Brandon Cannaday. He tweets wonderful things about IoT all the time. Highly recommend you go and follow him. But in this case, he was talking about the definition of Losant. Here, what Brandon is describing is that IoT is not really a thing, it's more of a of a concept. When I saw this, I loved it. I thought this was totally the right direction and a very common missing piece in people's IoT knowledge. So, I built on it a little bit. For me, IoT is more of a view of the technology stack. So, typically, in Saas based applications, there's just a wealth of tools and libraries but you're not doing hardware in those use cases. When it comes to typical hardware-based applications, there is software involved but it's nowhere near the ecosystem as we have in the software world. IoT is what happens when you have to look at this stack all at the same time for your application. That's anywhere from hardware, software, networking, data science, program security, web applications. IoT is what happens when you look at all of these things for your application at the same time. I love this stack because it really helped me frame where the different components are in IoT and when looking at use cases and application, where the proper resources needed to be had. In this case, when we first came up with the stack, I thought that this was going to be the key knowledge points of an IoT engineer and that's actually how this presentation started. But after the presentation, the content developed, what we found was that this is not really the knowledge point of an IoT engineer. This is the different components of your application and while you're building your application, what you actually do as a builder perspective, is you augment these stacks with three things — people, technology and ecosystem. Depending on your in-house expertise, you may have individuals who are disciplined in any part of the stack. Because as you may know, each of these are different disciplines and generally, different people within organizations. And then when people aren't there, now we have the opportunity because IoT and the vast ecosystem, we have we have access to new technology tools like Losant for example, and we can tap into ecosystem like partners for example. What you'll find is, as we talk throughout this presentation, is that as we talk about these stacks, a lot of the things and a lot of decisions we've made in Losant are going to come clear and make a lot more sense. Starting off with this question, here's what we always need to start. What are we building? IoT is huge. The ecosystem is vast and the tool sets now give us the opportunity to solve really different types of problems. So, we have to start with, what are we building? The first question I’d like to ask there is — okay, why? Why do we even buy IoT in general? Why is this even important? We found that amongst the tons of reasons why IoT becomes beneficial for me, despite the fact that it's just darn cool, we buy it because it allows us to create those new products for our customers and obviously lead to increased revenue. We buy it because it allows us to either make our existing products better or more efficient from our learning from the data which also ultimately, lead to decreasing costs. The third one is — I like this one because this one's the most obvious one — mitigating risk. Now, once we monitor things, we're able to manage our risk on an entirely different level and IoT give us the tools to do that. But understanding why we buy is the first step. The second step is let's talk about some use cases. IoT, since it's this vast ecosystem, it's a concept, right. We can't understand concepts without having anchors. Throughout this presentation, if you need use cases to anchor on, either think about this in context of your use case or here are three use cases that we're going to go through that serves as anchors for you to use as you're thinking about IoT throughout the presentation. The three we're going to talk about are asset tracking, huddle room monitoring and industrial equipment monitoring. The cool thing about Losant is that since the platform is generally horizontal, we talk to a lot of customers in a lot of use cases that are really different from this. But I like these three because A, they're really easy to understand but B, these are three valuable use cases within IoT that translate very well to this discussion. Starting with asset tracking. What is asset tracking? We have an asset. It's on the map and now we can watch that asset moving on the map from point A to point B, and, in a lot of these use cases too, we're also overlaying other data points with that as well. But why do we build asset tracking? A, that key thing, risk mitigation. Now that we have this asset on a map and it's going from point A to point B, that's information and a level of insight we didn't have before. Next, is increased productivity. Not only can we get, if this asset is on the map, but we can, in the world of IoT, we can build this application so whereas not only is the GPS values but maybe this asset is on the truck with things inside of the truck like in cold chain monitoring for example. So, now I need the GPS values and the temperature values. That gives our employees or our customers looking at this information, which will lead to increased productivity from a employee's standpoint and then from a customer standpoint, we're talking about that improved service. Now, they have a level of insight and data into this application in terms of asset that they never had before. Next, industrial equipment monitoring. I like this example because in this space, we typically work with the OEM, the company who actually makes the machine. In this case, this example customer in the screenshot you see here would make a generator. In this world, we would sell this generator and that was the end of our customer engagement. But now, with the new tools that we have, this new stack, we can not only sell that generator but offer new value-added services on top of that. In this case, what that may look like is a subscription service for the OEM's customers to monitor the telemetry data of the devices that they're purchasing. That's a huge value-add for them in that space. Increased productivity. Once we now have these machines and now, we have the telemetry data of the machines and the history of that data, all that information can go back into making technicians more productive. Lastly, now that we have this information, the cool thing here is once we build up historical information of something like a machine like this, we're able to do predictive maintenance. We're able to say — well, when this machine goes down just automatically go and send an alert. This makes customers happy and as we all know, happy customers mean they stick around long. And they stick around long, that means we increase the value about of the relationship between us and that customer. Lastly, smart environment. This one is my personal favorite mostly because it's so darn cool. I like the smart environment because it's all about — how do we measure the environments that we're in? This environment could be anywhere from a meeting room in your office to the floor of the office to the multiple floors, so you have the building or all the way up to the campus, right. This smart environment is just understanding that space. The image you see here in this example, the diagram is of the floor plan and there's three huddle rooms and we can see if the huddle room is available or not. But the key benefits of smart environment really starts with space utilization. How can we understand this space so hopefully, we can make it more valuable? I like it because this is for two reasons and two reasons, employee productivity and employee satisfaction and also, visitor satisfaction as well. Some of our customers have invested millions into modernizing their spaces mostly as a hiring incentive. In the real world, what this look like is ping pong tables in a corner but for an enterprise, are they being used? Can we make that space more valuable? Answering those questions offer a new level of insight to operations teams that they just simply didn't have before and now, it can empower us to make whole new decisions that A, lead to employee productivity and employee satisfaction, in this case, visitor satisfaction as well. Those are the three use cases that I want you to keep in mind. But as you think about your applications and your use cases, don't limit yourself to these three. Here are some good ways to frame your thinking about identifying where use cases may be. If you're monitoring something, well, what kind of monitoring are you doing? What more can you do with the monitoring? Can you eventually start to predict things from there? Asset tracking. Well, what are you tracking? We talked about not only do you have that asset but the asset may be say, an expensive piece of equipment that has entire use cases around there. Or we mentioned the example of cold chain monitoring where this asset is a truck and this truck may have other sensors on it like temperature sensor. And then the last one, this is my favorite — I need data about. I think IoT has found its home with data. Anywhere where there's, okay, here's something within your environment and we can grab data off of it, there's some value to be learned there. Just to take a pause, let's take a step back. The questions to ask yourself at this stage. One, keep the stack in mind and two, keep your definition in mind. Because that starts with — do we all have the same definition of IoT? Later in the presentation, I’ll tell you about a nice age-old battle we've been having internally and I think I have an answer to who won and I would like to share that with you all today. But I think having the same definition of IoT really sets the stage for how we talk about these problems. Next, what are the key benefits of our solution? Well, once we understand the key benefits, now, we can understand — well, this technology stack, since it can be applied in so many different ways, well, let's talk about the best way to get the benefits that we want? Lastly, by looking at this stack, it's very clear where we need to augment knowledge. For example, when I joined Losant, I was very strong in the web application space security and programming but the hardware and networking were areas that I quickly did a lot of research and learned on. Having a stack like this would have helped me identify that that's what my focus area should be a long time ago. Now, let's talk about developing. Whenever I begin these conversations with customers, I love this question. This is one of the best questions to ask yourself when you're thinking about any IoT use case even from the start. Where does the data come from? What I find is that since a lot of these use cases are so cool and they're so easy to dream up, it's very hard to come back down to — "Okay, well at the end of the day, there needs to be some hardware here tracking or some sensor or some data point that we can use to answer our question to get the benefits that we want in the first place. We really have to focus hard on — where does the data come from itself. Looking back at our three use cases, we can start to answer this question. For example, in the asset tracking world, I need GPS data. I probably need a piece of hardware that I can attach to something to get that GPS data. The huddle room monitoring example, we talked about these being meeting rooms. Well, I need some sensor in the room to tell me if there's someone in there or not. And then an industrial equipment monitoring example, I love this one because the hardware is pretty obvious, it's the generator in this case. But again, answering that question where the data come from is super important because, okay, the data is here in the generator. All right, how do we get that to the cloud? When I’m in my develop stage, I like to repeat this sentence to myself. What I find is that these three things commonly get overlapped and misunderstood. Your hardware sends data using a protocol over a network. This helps me frame where like hardware sits in the picture, where protocol sits in the picture and where my network sits in the picture. But during our develop stage, we have to understand all three together in one sentence to really move through this stage successfully. In this case, let's start off with hardware. To talk about hardware in the world of IoT, I love the smart environment because we look at use cases even as simple as, you walk into a room and the room comes alive because it knows that you're in the room. That's a pretty sophisticated use case that involves many pieces of hardware and many pieces of data points. In this case, if we kind of work our way through this graph, we get this awesome line here. I need to find a space for a meeting room. Well, that's one piece of hardware because now, this device needs to get that information. Then we have over here, where in the room, we need motion sensors to actually determine which rooms are free. That's another piece of hardware. And then you have to ask yourself how did that data go from the motion sensor, eventually to the cloud at some point. And then we have this, a whole other level of interactivity kind of tying these two pieces together, where we can — A, get notifications when the room is available, maybe the waypoints to that room. And now, those sensors that are in the room can now know that there's someone in here. This use case covers data and hardware from a bunch of different angles. Let's break that down a little bit. Whenever I am engaging in a conversation about Losant or teaching Losant and now, starting today, teaching IoT, I’m going to start with this graph. This is a really awesome way to understand — well, okay once we identify where the data comes from, okay, this helps me find the path to getting that data to the cloud. And just because we know IoT reflects Losant, the story is very similar to how data gets to Losant as well. The easiest to comprehend is the standalone device. This device is directly connected and as you see the line going from the device directly to the cloud in this case, which is Losant. In the consumer world, this is devices like your Google Home or Alexa but these devices have cloud connectivity. Next is, I like to call it the API route. In a lot of different IoT use cases, we're not actually talking to the end device itself. We're talking to some API or service that is talking to on behalf of a physical device. A great example here if you've ever been to the Losant walkthrough, the walkthrough takes you through an application where you pull data from a weather API into Losant to display on the dashboard. Well, in that use case, we never talk to a physical device but I’m sure somewhere on the other end of our weather station, there is a standalone device measuring weather but we don't have access to that. The value here is really for maintenance purposes. We get a nice clean API and we don't have to worry about the end devices. The third route, and this route is pretty fun because this gives us access to a whole nother level of power within the world of IoT, and this is where Edge comes in. In the industrial space we talked about that generator, that machine. Well, typically, those general machines have PLC's and those PLCs expose their logic in some way shape or form. In this case, we have Modbus, TCP, OPC UA, Serial. Those are some examples of what those protocols may look like but what we know about those protocols is that they're not cloud connected. We need a gateway. What this gateway allows us to do is, our machines and devices here locally to talk to this gateway and the gateway forwards those messages to the cloud on behalf of the device. This is an industrial example. But to give you a real easy consumer example is think about your Apple Airpods. They're a Bluetooth device, your phone is a gateway and it gets to the cloud. I guarantee you, you can take any IoT use case and map it into one of the three paths of the clouds that you see here. It may be either one of these three or combination of them. Your hardware sends data using a protocol over a network. Now, I know it's pretty obvious that we skipped a protocol here but since it's protocol over a network, we got to talk about the network first. English didn't let me be great there. To talk about the network, I want to talk about the asset tracking use case because the network in this use case is very easy to kind of wrap your mind around. We're talking about something like an asset that's measuring a piece of equipment or truck or data point from going from point A to point B. What we're doing there is we need a way to actually track this device from going from point A to point B and from a network perspective, we don't have much option. If you look at this dashboard that you see here, we can see this device going from the Edge of California all the way to what looks like, Central, like somewhere in the middle of America. Can't even see what that dot is. But the cool part here is that there's only one network available that we can use — cellular. In this case, this is from a customer example. The customer is NimbeLink. They make awesome cellular-based GPS devices that they give to their customers and their customers attach those assets to something that's valuable to them. What NimbeLink provides is an awesome way using Losant, to see that information about those devices. Coming back to our use case, in this use case that I just shown, what NimbeLink is doing is they have the GPS tracker, which is the image you saw before. They're reporting to their own service which their data actually forwards to Losant cloud, what then eventually goes and powers their end-user Experiences. But as we know now by looking at this path, that's only one way that this could work. Say for example, we were to get ourselves one of those GPS devices. There's nothing stopping us from taking that device, connecting it directly to the cloud and using that to prepare our Experiences. When you think about networks, it's really easy to get lost in this space. There's a lot of different networks, a lot of different buzzwords. I would like to encourage you to think about them as tools in your toolbox not necessarily things you need to go and learn and dive deep in. The cool thing about IoT is that we have access to all of these different networks. It's one layer of our stack. So, there, depending on the use case and depending on other factors, we can pick and choose what networks work best especially when we're thinking about how do we create the best IoT solution. There are three factors that I use to determine networks for the use case. The first one is really around availability. As we talked about for asset tracking, cellular was the obvious case there because if we're talking about going across the United States, it's available. Another high factor is cost. We're looking at networks like wi-fi, your cost may not be in the network itself but your ISP. If we look at use cases maybe that involves a private 5G, well, to take that cellular base station and have it on premises, there's costs associated with it or to actually maintain and manage a low power wide area network like LoRa or Z-Wave, there's cost associated with that. And bandwidth, as we all know, we are not going to use certain networks of stream video just due to bandwidth purposes. The reason why we have different even cellular networks like NB-IoT and different 5G is because of those application different bandwidth requirements. As you think about networks and as you look at networks, they're just tools in your toolbox. What's really important is well, what's available, what is cost effective for their solution and does it allow us to transmit the data that we need. Answering those questions are the best first step ever amongst the long list of things that you would need to evaluate doing the network. Now, protocols. To help me explain protocols, what I want to do is talk a little bit about the industrial equipment monitoring example, mostly because that used Edge. In this case, in that example, there was a generator and that generator, say, let's say had a Modbus PLC and that PLC was communicating with the Losant Edge agent and talking back to the cloud. When we look at this map and we look at the protocols, every arrow that you see here, these three arrows in this diagram represents MQTT, are HTTP. But in the world of IoT, we have access to other protocols as well even to get data to the cloud. In this case, through Edge, we get access to protocols like Modbus, TCP, OPC UA, Serial. And then for smart environment use cases, that may look like wi-fi, Bluetooth, UDP, LoRa, ZigBee. When we're looking at our solution in our use case and evaluating protocols, what I found was that there are three things to really keep in mind. A — use case-dependent. Protocols are typically defined by the use case, the selected hardware or the preferred network. For example, for Serial, we're going to use Serial to actually have two devices communicate with each other over hard wire but in the realm of MQTT or HTTP, that's obviously going from a device to an internet device or devices connected to each other over the internet. So, protocol is typically use case-dependent. Next, is availability. Protocols are purpose-built generally. So, depending on the purpose or use case, the ecosystem that you're going into may already have defined protocols. The best example that I have here is in the smart environment, low-power wide-area network networks are very popular. So, LoRa, ZigBee, Z-wave are popular protocol choices in the smart environment space. In industrial, we see Modbus, OPC UA, Raw TCP and those are the protocols that that community has standardized on. But here's my favorite general rule of thumb because where the protocols are, how the data gets to Losant can get really confusing in this space. However, here's the rule of thumb I like to mention. If the device can connect to the cloud using MQTT or HTTP, you can 100% send data to Losant. If you're talking about the translation of other protocols to one of these two, that's where things like the Edge agents in or some other translation protocols can come in. But generally, if we can get data to the cloud or MQTT and HTTP, that's a great way to know if you can send that data to Losant itself. Your hardware sends data using a protocol over the network. As you think about these things, keep the sentence in mind to kind of wrap your head around where you are in that develop stage. This leads to a very good question, — how do I get started? In this case, if you want to get started on the embedded device side, here are two devices I highly recommend to — A, have download flash and use to start playing around with — okay, what hardware networks and protocols. This is the Arduino MKR WIFI 1010. It's really good and this is Particle's Photon. Both of these devices, we see them being used a lot in the hacker and maker space but also enterprises using them because of their low cost point and awesome communities as a way to prototype early solutions. And, on the Edge side, if you're looking to experiment with Edge and Edge networks, honestly, the best piece of hardware is a Raspberry Pi. It's super low cost, very easy to use, the community is awesome and it supports the low Edge agent. So, it's a really good way to start digging into some of these tool sets. So, just to re-evaluate our three methods to the cloud. We have our Edge method, we have standalone directly to the cloud and we also have through a third-party service. Now that we have our application and we have this stack, let's take a step back. We've defined IoT. We have started to figure out, okay, what are the benefits, what are the key value points you're trying to get out of this? Next, where does the data come from and how does it get to the cloud? We're now equipped for answering that question and now, it gets us back to our stack. For your use case, the next thing to look at is, all right, here's my stack. Where do we need help, where do we need to augment either people technology or ecosystem in this stack? Here is where I find it super interesting. A long time ago when we made the decision to separate Losant into components, it seemed like a crazy idea at the time because well, here's this platform that has all these different features, why are we going to segment them into components? But I really like that this is a helpful way of explaining it because as you can see is, is that our components map to these layers of the stack. For Edge, you've got hardware. For devices and data sources, I can make the case for networking. Dashboarding and notebooks in Losant are data science tools. Software, that's our workflow engine and web application layers Experiences. When we talk about that stack and augmenting it with people, with technology and ecosystem, I think that's a real value of where Losant fits in that picture, is because our components are key pieces of those stack. Again, as I said, as I learn more about Losant, I learned more about IoT. What was interesting for me was that since I knew that all the stacks had different expertise, well, it was pretty easy to say that well, end-user Experiences, if you have web application Experiences, you're going to be really successful there. It's going to make a lot of sense in that realm. For the visual workflow engine, if you have software or general programming Experience, you're going to be very successful in the workflow engine. For data analytics specifically here, let's talk about Losant notebooks, which is our batch processing tool. If you're familiar with data science and Jupyter Notebooks, that realm is going to feel like home. Our components reflect this stack greatly. And with our components aren't there, I think that's where the Losant partner ecosystem comes in to fill in those other areas of the stack that your use case may not have. Now that we're in a Losant realm, I want to talk about, all right, what is the path to learning Losant. This is a slide we had on every single Deeper Dive that we've had in the past. Recently, we decided to update it and the order changed as well. As you look at this, this is the order you should go about learning Losant, at least the recommended path we recommend. First, let's start with the Losant documentation. Once you get there, the resources that are available to you look like — What is Losant? This is a high-level document about all the components and the value they provide to you. The Losant walkthrough. If you need a quick way to jump into the platform just to understand or something to send your team to get their mind around it, the walkthrough is perfect there. The Workflow Lab. The Workflow Lab is an awesome tool to start to learn and build within the workflow engine. The lab is separated into suites. Each suite covers a different topic and it allows you to practice using the workflow engine. It's all based on web hooks and triggering workflows. So, by learning how to use the Workflow Lab, you learn a little bit more about workflows too. It's super simple. You come in here, you press play and the Workflow Lab will trigger your workflow with a set of inputs and expect a certain result output. It's a nice and easy way to learn how to use the workflow engine. In this case, as you can see, all of my tests are failing. So, I should probably go back and fix this webhook and do some work on my Workflow Lab. Next, is Losant University. Losant University is obviously a very one important to my heart. But the Losant University as you go through, I like it because it's separated into the courses. Each course has its own set of videos that you can use to learn about that specific component. In this case, you can see courses on like, What is Losant, Data Visualization and Losant Experiences. Losant University is a great way to hop into Losant and understand those components from a fundamental level and grow your Experience there. Once you get done with Losant University, you can get your certificate of completion. All of you here today, if you get your certificate and let us know in the forums, I’ll be sure to send you something special. Next, is really hands-on tutorials. Brandon, our Chief Product Officer has recently published this tutorial called Analyzing IoT Image Data Using Losant and the Google Vision API. Our blog is filled with tutorials in this light. They are a key learning tool for you as you go about Losant for one or two reasons. A, there might be an example of what you're building there already or B, we talked about the stack and understanding the stack. Well, these tutorials allow you to expand your uses as well. Lastly, the Losant forums. Along your journey and along your help, we are, I think the most important part is we're augmenting that stack with technology ecosystem and most importantly, people. And, Losant, we got your back. As you are going through your process and you have questions, feel free to reach out on the forums and we'll be happy to help. There's one last thing I want to leave you with and I want to go back to our use case to talk about that a little bit. We have these use cases and now that we have this stack, the one thing I want you to keep in mind is that as you're building in one domain within IoT, it makes it really easy to build in the other domains of IoT. For example, in the industrial equipment monitoring space here, we have a generator. That generator is sending data to a platform. However, that generator is also in a space, a space that can be tracked, which kind of blurs the line between smart environment and this huddle room use case because this could easily be where the generator is within the floor plan along with the telemetry data. Once we actually take IoT and we zoom out and we look at this stack, the reason why we say, "Start with a small problem," is because once you're able to solve a problem with this stack, it makes it really easy to translate that problem across different domains. As you're thinking about your use cases within IoT, even if you are in one of these verticals, I encourage you to think about what other verticals and value-adds because we're now looking at the stack, could you easily build into your current existing application or to extend the capabilities of your current application. Because now, this is the end of my presentation, I want to go back here because this is my take away. If you want to go and learn about Losant and IoT, I highly recommend this five-step process. This should guide your learning hopefully, to building some really awesome things in the world of IoT. Just remember as always, as you learn more about IoT, a lot of stuff in Losant is going to make a lot more sense and as you appreciate the knowledge of Losant, your concepts in the world of IoT are going to make a lot more sense too as well. I really appreciate you listening and now I’m going to kick it back over to Nugeen, so we can hop into some Q&A.

Nugeen: Great. Thank you, Taron. We do have a couple of questions that have come through and I’ll get to them in just a second after one last note. Let me pull this up. Great. Hopefully you all can see my screen. Okay, so we do have another webinar coming up, so please save the date for that. Adam Daniel, who is our VP of Solutions we'll be discussing a contact tracing application we've built in the wake of the Covid pandemic. He'll be diving into how companies are approaching getting back to business, looking to implement IoT in very new and different ways. You can register for that at losant.com/deeperdive. Then a couple questions that have come up. I have a question here that is asking, is access to Losant University free? Yes, it is but, Taron, if you want to delve deeper into the resources and how the access for those works.

Taron: Yeah. The best place to go is university.losant.com. That will take you right to our LMS, our learning management system. From there, it actually, if you're logged into Losant, you should hop right in and be able to take all the courses. We wanted to make sure that they were free for everyone using Losant within our community.

Nugeen: Great. I have another question here that's actually asking if it's possible to show an industrial equipment monitoring application and the dashboard for that? The answer to that, a great resource that Taron pointed out was the Deeper Dive Webinars. We do have an example of an industrial equipment monitoring application that is available for you to view on there. Additionally, if you go into Losant, have a Sandbox account and create an application template, you can actually download the industrial equipment monitoring application, the exact one that Taron showed today.

Taron: I can actually show a preview right there of it really quick, Nugeen. I have my computer set up.

Nugeen: Sure. Yeah, absolutely. I believe you have the ability to share.

Taron: Just to give you a quick preview of what Nugeen was mentioning. The cool thing about all the use cases that we talked about is that within Losant, they're all backed by a template. Also, the cool thing here as well is all of these templates, the asset tracker the Huddle room monitor, and industrial equipment monitor all have Deeper Dives taking you through the template and everything that's involved so you can see what's included there. But in this case, I already have the industrial equipment monitor application set up. Within this application, and the cool thing about templates is that they always come with the read-me, that read-me gives you all the information that you need to know to kind of get started. But the templates come with devices dashboards and workflows but most importantly that Experience that you saw the screenshot of it, that's a real Experience that comes with the template. Each template comes with a data simulator. So, all the data here is simulated, it's not coming from a real device but the templates are meant to feel real and be good examples of those use cases. In this case, we have that overview dashboard. So, we can see me as a customer, all of my generators. And then I can click that generator to drill in down deeper on this telemetry data, see its status, it's running, and all the different information about it. And when you start from this template, this is what you get.

Nugeen: Great. The next question that we have is, Taron, you mentioned some good steps on learning Losant. Are there any good paths or resources for going further into specific use cases with IoT?

Taron: Yes. My resources there will be mostly around — I prepared this slide because I knew I was going to talk about it — is social fodder. When we talk about all these different use cases, the best way is to just expose yourself and then engage in the same question, the same process that we've gone through throughout this slide. That's the way to really start to get a keen sense of what all the different use cases look like in IoT. If you need specific recommendations, here are some of the places where I go for my information to learn more about the use cases. The one that's not mentioned here is Stacy on IoT. That's probably my number one resource that I would add to this list that you see here on my screen.

Nugeen: To add on to this, we have another question that's asking — I’ve completed Losant University. What should be my next steps if I want to learn more about Losant and IoT in general?

Taron: Yeah, that's a great question and that takes me back down to my five-step process. A, I would recommend the workflow lab in the documentation but now as you go into Losant University, now, it's time to start digging into those use case-specific items and building within Losant. The Deeper Dive series are great because in this case, we're talking about learning IoT and Losant but the Deeper Dives that we have available really go in to Losant and building and use cases and pro tips while you're doing so and then the next step is going to be those hands-on tutorials. All the tutorials that you see in our blogs, I highly recommend go and pull a tutorial and going through it and trying it. Those are the things to really kind of sharpen your skills there. Here, really, the tutorial is building your use cases, right, and building your story into your application. There's a lot of learning there. Those are my two next recommendations based off of this path.

Nugeen: I do have another question that might be good for either Taron or for Brandon. What is the best resource to find hardware that is capable of running the Losant Edge agent? Is there a catalog of certified hardware? Certainly, I can talk about partnerships but if Taron or Brandon, if you want to take this first?

Taron: Yeah. This one, I really like this answer. On my screen, we talked about the Pi. The Pi is just one example. The cool thing about the Edge agent is that the Edge agent is shipped using Docker. If you're not familiar with Docker, Docker is a Unix containerization technology. What it allows us to do is shift the Edge agent to you in one container and not have to install any other dependencies. Because we leverage Docker and the ecosystem behind Docker, we get a lot of flexibility there. The Edge agent can be installed on any Linux capable gateway, that's generally what we say. But we've seen use cases where like on Windows operating systems, the Edge agent can be installed and for testing as well, you can install the Edges on your Mac if you wanted to just do some quick testing. But the piece of hardware that I recommend the most, the quickest to get started is 100% the Pi.

Nugeen: I’d like to add on to that as well. As you are looking at any type of production application or solution, we have built out many partnerships with hardware connectivity vendors. Part of that process is understanding that our software is compatible with their services as well. So, if that is something you're interested in, I’d encourage you to take a look at our partners page, it's losant.com/partners. Or you can always engage with someone here at the company within Losant to help you understand better what options do exist. That is a lot of the work that our solutions team does today. Last question that I have today... Oh, actually, two more. If I need to use the Losant Edge agent for a local protocol, how is that deployed or installed on my gateway? I know you answered that with the Docker container but is there documentation that you can point to, Taron?

Taron: Yes. In the docs, there are two pieces of documentation when it comes to the Edge agent that I would totally recommend and that's the Edge agent usage and Edge agent installation docs. They walk you through setting up the Edge agent and how to use it. So, in this case, how we actually run the Edge agent with a configuration file, which is the recommended way. Here's that example command here. If you have any questions, as Nugeen mentioned, don't hesitate to reach out in the Losant forums or to us. These are totally problems that we're happy to help you get on board with when it comes to Losant.

Nugeen: Great. The very last question I have. When building in Losant, how can I be proactive in learning more features and learning more as I scale my application?

Taron: Oh, continue to watch the Deeper Dives. I think not only the Deeper Dives and as I mentioned before, the Deeper Dives hands-on tutorials, as you go about learning through Losant, I think we're going to continue to produce these Deeper Dives and tell great stories about IoT. They're probably, in my opinion, the best way to continue this conversation.

Nugeen: Okay. I think that's it for questions. Thank you so much, Taron, for going through this. I appreciate everyone hopping on and watching our Deeper Dive this month. I’m looking forward to seeing you on the next one. If you have any more questions that haven't been answered, please feel free to reach out to someone on our team and we will make sure to get you an answer as soon as possible through our contact page or whatever it is. Thank you.