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<v Speaker 1>Imagine stepping into a world where well almost everything around

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<v Speaker 1>you is talking, not just your phone, but like the

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<v Speaker 1>smart meter outside, maybe a sensor on a bridge miles away.

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<v Speaker 1>They're not just sitting there, they're active, sharing data, making

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<v Speaker 1>things smarter, our cities, our homes. There's this whole Internet

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<v Speaker 1>of Things or IoT explosion, and the growth is just

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<v Speaker 1>an incredible billions of devices already more coming online constantly.

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<v Speaker 1>Today we're doing a deep dive into a technology that's,

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<v Speaker 1>you know, quietly making a lot of this happen. NBIOT.

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<v Speaker 1>That's narrowband Internet of Things. We've pulled together insights mainly

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<v Speaker 1>from a great source LTE cellular narrow band Internet of

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<v Speaker 1>Things and BIOT practical projects for the cloud and data

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<v Speaker 1>visualization by doctor Hassum Fata. So our mission today it's

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<v Speaker 1>really to unpack what nbiot actually is and maybe more importantly,

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<v Speaker 1>why it's such a big deal. We'll look at where

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<v Speaker 1>it came from, the actual hardware involved, how these devices

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<v Speaker 1>talk to the cloud, where the data lands, and crucially,

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<v Speaker 1>how we make sense of it all visually. The goal

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<v Speaker 1>is for you to get a really clear picture, no

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<v Speaker 1>confusing jargon, just why this tech is so vital for well,

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<v Speaker 1>our increasingly connected world. Okay, let's get into it. When

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<v Speaker 1>we think cellular, yeah, we usually jump to smartphones, but

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<v Speaker 1>the tech behind it all has come such a long way, right, Oh, absolutely,

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<v Speaker 1>it's night and day from those early like two G,

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<v Speaker 1>three G systems GSM gprs, which were mostly just for

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<v Speaker 1>calls maybe basic data, to today's four GLTE and now

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<v Speaker 1>five G, which are these data powerhouses. They handle streaming, video, AI,

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<v Speaker 1>cloud stuff. It's a huge shift, it really is.

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<v Speaker 2>And what's fascinating I think is that NBIOT isn't just

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<v Speaker 2>another step in that phone focused evolution. It's a specific

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<v Speaker 2>branch purpose built, you know, for the IoT. It wasn't

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<v Speaker 2>an afterthought. Its roots are in three GPP release thirteen

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<v Speaker 2>that was sort of pre five G tech, and then

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<v Speaker 2>it got extended and released fifteen, which is more aligned

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<v Speaker 2>with five glt E specs.

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<v Speaker 1>Ye.

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<v Speaker 2>Now, release fifteen did bring in slightly higher speeds cat

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<v Speaker 2>NB two they call it, but the core idea of

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<v Speaker 2>the fundamental operation stayed the same. It's really designed for

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<v Speaker 2>what we call machine type communication MTC and these low

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<v Speaker 2>power wide area LPWA scenarios. The whole point is connecting

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<v Speaker 2>tons and tons of devices very efficiently, often need them

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<v Speaker 2>to last years on a single battery charge.

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<v Speaker 1>And when you say tons of devices, the scales almost

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<v Speaker 1>hard to grasp, isn't it. It is the source mentioned

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<v Speaker 1>projections of over five billion devices connected via nbiot by

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<v Speaker 1>twenty twenty five. That's yea yeah. They call it massive IoT,

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<v Speaker 1>massive IoT exactly, So what does this actually mean for

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<v Speaker 1>you listening? Why should you care? Will? Nbiot isn't just

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<v Speaker 1>about faster downloads on your phone. It's enabling completely new things.

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<v Speaker 1>Think smart homes, maybe controlling lights or heating super efficiently.

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<v Speaker 2>Or security systems that don't need constant battery swaps.

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<v Speaker 1>Right, and smart cities managing traffic better, monitoring air quality

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<v Speaker 1>with sensor scattered everywhere.

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<v Speaker 2>At grids, smart water meters, utilities.

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<v Speaker 1>Yeah, wearables too, for health tracking, remote sensors out in fields,

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<v Speaker 1>for farming.

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<v Speaker 2>Object tracking, for logistics, even critical control systems.

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<v Speaker 1>The key insight really is that nbiot makes it cheaper

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<v Speaker 1>and more power to connect these devices, so we can

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<v Speaker 1>put them in places and use them in ways we

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<v Speaker 1>just couldn't before. It expands where we get data from Exactly.

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<v Speaker 2>It's getting into those challenging environments, places where power or

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<v Speaker 2>cost was a barrier. That's the game changer. We're getting

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<v Speaker 2>granular data we never had before.

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<v Speaker 1>Okay, so we see the potential, huge potential, But how

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<v Speaker 1>do we actually build this? It starts with the hardware, right,

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<v Speaker 1>the actual boards it does.

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<v Speaker 2>The practical starting point is often an NBIOT hardware board.

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<v Speaker 1>And what's cool the Source highlights is that these boards

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<v Speaker 1>are often compatible with things like our adrenal software and tools.

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<v Speaker 1>That makes it way more.

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<v Speaker 2>Accessible, yeah, hugely accessible. It brings it within reach for hobbyists, students,

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<v Speaker 2>not just you know, big engineering teams. It lowers that

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<v Speaker 2>barrier to entry.

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<v Speaker 1>So what's actually on these boards? What makes them tick?

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<v Speaker 2>Okay, diving in, You've got a couple of key players.

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<v Speaker 2>First is the micro controller unit, the MCU. The source

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<v Speaker 2>mentions the microchip sam D twenty one G eighteen chipset.

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<v Speaker 2>And the key thing here isn't just any chip. It's

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<v Speaker 2>a low power but still high performance ARM Cortex M

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<v Speaker 2>zero plus based microcontroller. It's got decent specs forty eight

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<v Speaker 2>never herds, two hundred fifty six KB flash, thirty two KBSRAM.

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<v Speaker 2>But the real emphasis is low power, engineered for efficiency

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<v Speaker 2>for longevity.

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<v Speaker 1>Right, Because these devices might sit out in a field

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<v Speaker 1>for what ten years exactly.

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<v Speaker 2>Battery changes are often just not feasible at that scale.

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<v Speaker 2>Then you have the cellular modem itself. The Quicktail BG

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<v Speaker 2>ninety six is a really common one. Mentioned its strengths well.

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<v Speaker 2>It supports global frequency bands, which is crucial if you

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<v Speaker 2>want to deploy worldwide ultralow power consumption. Again, vital data

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<v Speaker 2>rates are up to three hundred and seventy five kilobits

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<v Speaker 2>per second, both down and up. Now, it does operate

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<v Speaker 2>in half duplex on LTE networks.

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<v Speaker 1>Half duplex like a walkie talkie you talk where you listen,

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<v Speaker 1>but not both at once.

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<v Speaker 2>Precisely, it sounds like a limitation, but it's actually a

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<v Speaker 2>deliberate choice to save even more power. Perfect for devices

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<v Speaker 2>that mostly just send small bits of data occasionally, and

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<v Speaker 2>a really important feature for many uses. Built in GNSS

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<v Speaker 2>Global Navigation Satellite System, so you high precision location data

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<v Speaker 2>right from the device.

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<v Speaker 1>Turns a sensor into a tracker basically exactly. Okay, so

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<v Speaker 1>besides the brain and the communicator, what other physical bits

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<v Speaker 1>are on the board, the nuts and bolts.

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<v Speaker 2>You'll typically find a nano USIM card slot, just like

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<v Speaker 2>your phone You need a SIM card, usually two USB ports,

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<v Speaker 2>one for programming the MCU, one for interacting directly with

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<v Speaker 2>the modem, which is handy for testing and configuration. And importantly,

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<v Speaker 2>separate antenna connectors, one for the LTE cellular signal and

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<v Speaker 2>one for the GNSS signal to make sure you get

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<v Speaker 2>the best possible reception for both.

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<v Speaker 1>Got it. So you've got this specialized efficient hardware. How

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<v Speaker 1>do you actually command it? How do you tell the

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<v Speaker 1>modem connect to this network or send this data.

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<v Speaker 2>That's where AT commands come in. They're essentially the language

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<v Speaker 2>you use to talk to the modem. Think of them

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<v Speaker 2>like text based instructions. You send a command, the modem

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<v Speaker 2>responds or performs an action. For instance, you might use

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<v Speaker 2>at plus q ECFG and news can't say ten three

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<v Speaker 2>zero two zero one to tell it hey prioritize searching

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<v Speaker 2>for the LTE cast NB one network first. It gives

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<v Speaker 2>you fine grain control. You can do security things like

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<v Speaker 2>at plus c K to manage locks on the simcard

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<v Speaker 2>or query information. At plus GSN gets you the device's

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<v Speaker 2>unique IMEI number, at plus QCCID gets the simcards ID,

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<v Speaker 2>and a really critical one is activating the data connection

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<v Speaker 2>the PDP context like AT plus C G D C

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<v Speaker 2>E C O, N T one I, P M two,

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<v Speaker 2>M N B sixteen, dot Com, dot T That tells

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<v Speaker 2>it how to connect to the Internet via in this

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<v Speaker 2>case AT and T's network. It shows you the level

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<v Speaker 2>of control you have to optimize things, which is super

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<v Speaker 2>important for large deployments.

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<v Speaker 1>So it's not just theoretical. Then you actually need a

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<v Speaker 1>physical simcard and a plan from a mobile operator.

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<v Speaker 2>Absolutely just like your phone operators like AT and T,

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<v Speaker 2>T Mobile, Verizon, and even specialized IoT virtual operators like Hologram.

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<v Speaker 2>They provide the actual nbiot network coverage Without that network,

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<v Speaker 2>the hardware, however, smart is just well disconnected.

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<v Speaker 1>Right, Okay, this is where it gets really interesting for me.

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<v Speaker 1>The devices collect the data, then what where does it

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<v Speaker 1>all go?

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<v Speaker 2>Straight to the cloud that's the central hub.

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<v Speaker 1>The digital brain.

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<v Speaker 2>Yeah.

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<v Speaker 1>The source material leans heavily on Amazon Web Services IoT

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<v Speaker 1>aws IoT right.

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<v Speaker 2>And setting that up involves a few key steps. Make

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<v Speaker 2>sure everything talks securely and efficiently. First, you have device management.

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<v Speaker 2>You actually register your device in AWSIOT as a thing.

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<v Speaker 2>You give it a unique name, maybe like nbiot temp

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<v Speaker 2>Sensor one twenty three, at attributes like its location. Then

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<v Speaker 2>security certificates. This is non negotiable. You generate a unique

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<v Speaker 2>certificate for the device or private key keep secret, and

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<v Speaker 2>you need a root certificate to verify aws's identity.

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<v Speaker 1>That's the digital handshake, basically, to make sure everyone is

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<v Speaker 1>who they say they are exactly.

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<v Speaker 2>It prevents eavedropping, ensures data integrity. Without it, it's not secure.

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<v Speaker 1>And you need rules. Right, you can't just let any

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<v Speaker 1>device do anything it wants connected precisely.

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<v Speaker 2>That's where policies come in. You define exactly what that

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<v Speaker 2>specific device is allowed to do. Can it publish data

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<v Speaker 2>to which specific topics? Can it subscribe to receive data about?

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<v Speaker 2>Granular control for security. And finally you set up rules

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<v Speaker 2>for data processing. These are like automated actions. An incoming

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<v Speaker 2>message comes in, say matching a pattern like select from

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<v Speaker 2>sensors building a floor three, and the rule triggers in action.

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<v Speaker 2>That action could be storing the data, sending an alert,

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<v Speaker 2>maybe triggering another cloud function. It's how raw data starts

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<v Speaker 2>becoming useful.

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<v Speaker 1>Okay, storing the data where does it typically land? In

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<v Speaker 1>this AWS setup?

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<v Speaker 2>The source points to Dynamo dB. It's a no SQL

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<v Speaker 2>key value.

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<v Speaker 1>Database, no SQL, so not like traditional databases with rigid tables.

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<v Speaker 2>Exactly. It's big advantage heirs being schemeless. You don't have

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<v Speaker 2>to define the exact structure of your data upfront. If

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<v Speaker 2>one sensor sends temperature and humidity and another sends GPS

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<v Speaker 2>and battery level, Dynamo dB handles it.

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<v Speaker 1>Easily ah flexible. That makes sense for IoT with all

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<v Speaker 1>its different device types, huge advantage.

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<v Speaker 2>Typically you'd use the device's IMEI as the main identifier,

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<v Speaker 2>the partition key, then maybe a timestamp is the sort keys.

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<v Speaker 2>You can easily query data by time time all the

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<v Speaker 2>actual sensor readings get bundled into a payload attribute.

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<v Speaker 1>Gotcha. Okay, so we have the path device like secure

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<v Speaker 1>connection IRAQ flateral's database. What are the actual languages the

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<v Speaker 1>protocols making that connection happen efficiently?

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<v Speaker 2>The big one the workhorse for the application layer in

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<v Speaker 2>nbiots MQTT message q telemetry transport. Its superpower is being

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<v Speaker 2>incredibly lightweight, perfect for these constrained devices, small memory, low

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<v Speaker 2>processing power and crucially saving battery.

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<v Speaker 1>Lightweight is key.

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<v Speaker 2>Absolutely. It uses that published subscribe model we touched.

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<v Speaker 1>On the Digital Noticeboard idea.

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<v Speaker 2>Exactly, devices published messages to a topic could be city

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<v Speaker 2>traffic sensor, main street and anything interested maybe a dashboard

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<v Speaker 2>or another system subscribes to that topic to get the

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<v Speaker 2>messages super efficient. That also has useful features like retained messages.

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<v Speaker 2>The last message on a topic can be saved for

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<v Speaker 2>new subscribers, and something called a WILL message.

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<v Speaker 1>A will message right, a last will and testament kind of.

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<v Speaker 2>If a device disconnects on and expectedly maybe it loses

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<v Speaker 2>power or crashes, the MQTT broker can automatically send out

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<v Speaker 2>a pre defined WILL message on its behalf maybe sensor

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<v Speaker 2>one twenty three offline. Really useful for alerts clever.

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<v Speaker 1>Okay, so m QTT handles the messaging. What about keeping

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<v Speaker 1>it secure?

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<v Speaker 2>That's where SSLTLS comes in secure socket layer or transport

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<v Speaker 2>layer security. It encrypts the communication between the modem and

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<v Speaker 2>the cloud. Absolutely essential. You can figure this using those

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<v Speaker 2>AT commands. Again, things like at plus qstl CFG and

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<v Speaker 2>at plus qs will open to set up the secure tunnel.

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<v Speaker 2>And while QTT is common the modems built in tcpip

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<v Speaker 2>stack means it can also do standard Internet stuff like

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<v Speaker 2>HTTP requests if needed, using commands like at plus coo,

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<v Speaker 2>at plus coys end at plus QHTTPG E t OH

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<v Speaker 2>and one more crucial thing firmware updates over the air

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<v Speaker 2>or DFOTA. These modems can receive updates remotely, usually small

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<v Speaker 2>delta updates, just the changes to fix bugs or add

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<v Speaker 2>features without having to physically touch thousands of devices DFTA.

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<v Speaker 1>Yeah, that's huge for maintenance, especially for devices way out

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<v Speaker 1>in the middle of nowhere.

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<v Speaker 2>Absolutely essential for managing large fleets long term.

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<v Speaker 1>You know, collecting all this data, sending it securely, storing it,

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<v Speaker 1>that's amazing engineering. But raw data is just well raw

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<v Speaker 1>data isn't it numbers in a database. It only really

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<v Speaker 1>comes alive when we can see it, visualize it. That

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<v Speaker 1>old saying a picture is worth a thousand words. It's

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<v Speaker 1>especially true here trying to spot trends or problems in

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<v Speaker 1>all that IoT data.

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<v Speaker 2>Could agree more. Visualization turns that flood of information into

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<v Speaker 2>something understandable, actionable.

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<v Speaker 1>So how does the data get formatted for this? What's

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<v Speaker 1>the common language for the data itself?

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<v Speaker 2>The dominant format discussed in the source and really industry

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<v Speaker 2>wide for this kind of thing is Jason JavaScript Object notation.

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<v Speaker 2>If big advantages are that it's human readable, which is

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<v Speaker 2>great for debugging, it's mature and basically every tool and

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<v Speaker 2>cloud platform under the sun understands it. So a temperature

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<v Speaker 2>sensor might send something simple like device IIDE sensor forty

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<v Speaker 2>five timestamp one six seven eight eight eight eight six

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<v Speaker 2>four hundred do temp twenty two point five unit c

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<v Speaker 2>easy to read, easy for software.

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<v Speaker 1>To parse, makes sense. Are there alternatives?

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<v Speaker 2>There is CBR Concise Binary object representation. It's a binary format,

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<v Speaker 2>so it's generally more compact than Jason. Uses less data

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<v Speaker 2>on the.

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<v Speaker 1>Wire, smaller data size. That sounds good for nbiot.

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<v Speaker 2>It can be, yeah, especially if bandwidth is really tighter.

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<v Speaker 2>Every byte of battery matters, But the trade off is

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<v Speaker 2>it's not human readable and you need specific libraries to

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<v Speaker 2>encode and decode it. So while CBR exists and has

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<v Speaker 2>its uses, Jason's ease of use and wider support often

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<v Speaker 2>make it the more practical choice.

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<v Speaker 1>Right now, okay, Jason? It is mostly so, how do

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<v Speaker 1>we turn that Jason data into say, dots on a

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<v Speaker 1>map or charts showing temperature changes for location data?

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<v Speaker 2>The Google Maps JavaScript APIs are a very common choice.

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<v Speaker 2>You can easily plot the GPS coordinate's coming from your

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<v Speaker 2>MBIOT devices right onto a familiar Google map embedded in

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<v Speaker 2>a web page or application.

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<v Speaker 1>Right so for tracking trucks or finding lost equipment.

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<v Speaker 2>Exactly, asset tracking, fleet management, navigation, tons of applications. The

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<v Speaker 2>process is straightforward. Get a Google Maps apikey, use some

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<v Speaker 2>JavaScript to initialize a map, read the latest latitude and

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<v Speaker 2>longitude from your database for a device, and plank a

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<v Speaker 2>marker on the map. You see your stuff moving in

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<v Speaker 2>near real time.

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<v Speaker 1>And for other sensor data like that temperature reading.

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<v Speaker 2>For that, libraries like chart dot js are really popular.

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<v Speaker 2>It's an open source JavaScript library that makes it easy

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<v Speaker 2>to create nice looking interactive charts, bar charts, line charts, etc.

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<v Speaker 2>Write in a web browser using HTML five canvas. So

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<v Speaker 2>you could easily pull temperature readings from Dynamo dB and

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<v Speaker 2>plot them on a line chart against time instantly see

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<v Speaker 2>the daily temperature cycle, spot unusual spikes or dips. It

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<v Speaker 2>makes patterns jump out.

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<v Speaker 1>Yeah, much better than staring at a spreadsheet full of numbers.

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<v Speaker 2>Definitely. It brings the data to life.

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<v Speaker 1>This is where it all comes together, isn't it. This

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<v Speaker 1>isn't just theory or textbecs anymore. Nbiot is actually out

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<v Speaker 1>there making real changes. That's the exciting part.

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<v Speaker 2>It really is seeing the applications make the underlying tech meaningful.

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<v Speaker 1>Like in the smart home we mentioned lighting, heating, security,

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<v Speaker 1>but also things like elder care sensors detecting falls maybe

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<v Speaker 1>or tracking devices for kids or pets that can last

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<v Speaker 1>ages on one.

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<v Speaker 2>Charge bis peace of mind.

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<v Speaker 1>Totally, and smart transportation traffic control that adapts, smart parking

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<v Speaker 1>telling you where spots are, smooth toll collection, logistics tracking

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<v Speaker 1>for delivery companies.

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<v Speaker 2>Even vehicle safety systems talking to each other.

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<v Speaker 1>Are the infrastructure and smart farming measuring soil conditions, humidity, rainfall,

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<v Speaker 1>detecting pests, automating irrigation, helping farmers grow more with less waste.

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<v Speaker 1>It's pretty amazing. The breath of it.

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<v Speaker 2>It truly is diverse, and it raises the question how

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<v Speaker 2>does this look when a whole city embraces it? How

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<v Speaker 2>does it scale up? The city of Coral Gables, Florida

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<v Speaker 2>is a really interesting case study here. They're often cited

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<v Speaker 2>as a leader in building a comprehensive smart city ecosystem.

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<v Speaker 1>Oh yeah, what are they doing? Specifically?

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<v Speaker 2>They've deployed a really wide array of sensors and actuators.

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<v Speaker 2>Environment sensors monitoring everything from temperature and humidity to water levels,

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<v Speaker 2>air quality, even noise pollution. They have smart parking, smart

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<v Speaker 2>street lighting. They use drones, GPS for managing city vehicles,

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<v Speaker 2>RF sensors to understand traffic flow.

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<v Speaker 1>Wow, okay, so data on everything pretty much.

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<v Speaker 2>Public safety uses CCTV and smart policing tools connected to

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<v Speaker 2>the network. They have digital kiosks. They monitor the structural

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<v Speaker 2>health of bridges and buildings, and they're integrating connected vehicles.

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<v Speaker 2>It's a whole interconnected web that sounds like.

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<v Speaker 1>An ocean of data. How do they possibly manage that

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<v Speaker 1>and make sense of it?

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<v Speaker 2>They have what they call a smart city hub. The

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<v Speaker 2>source calls it a digital supermarket, which I quite like.

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<v Speaker 2>It's a central platform that gathers all this diverse data,

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<v Speaker 2>standardizes it and analyzes it. And this provides actionable insights.

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<v Speaker 2>It's not just data for data's sake. Traffic engineers use

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<v Speaker 2>it to design safer roads or tweak signal timings. Urgan

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<v Speaker 2>planners can see the actual impact of new developments. Businesses

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<v Speaker 2>can even look at anonymaled foot traffic data. Public safety

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<v Speaker 2>gets better situational awareness for emergencies.

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<v Speaker 1>So it actually helps them run the city better.

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<v Speaker 2>That's the goal. They use a horizontal integration model, basically

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<v Speaker 2>a central cloud platform where everything connects and shares data

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<v Speaker 2>feeding into city dashboards. And what's really cool is that

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<v Speaker 2>a lot of this is public. You can actually go

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<v Speaker 2>to www. Dot Coral Gables dot com, forward slash smart

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<v Speaker 2>City and see some of the data and platforms. It

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<v Speaker 2>shows how this tech can create more responsive, transparent communities.

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<v Speaker 1>That's fantastic, a real world example of it all working together. Okay,

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<v Speaker 1>So that brings us towards the end of our deep dive. Today.

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<v Speaker 1>We've gone from the basics of nbiot why it's different,

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<v Speaker 1>looked at the hardware, the journey to the cloud, the protocol, storage,

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<v Speaker 1>the visualization right, making sense of it all visually, and

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<v Speaker 1>finally seeing how it's making a real impact in everything

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<v Speaker 1>from our homes to entire cities like Coral Gables. It

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<v Speaker 1>leaves you thinking, though, as nbiot keeps connecting billions more devices,

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<v Speaker 1>bringing in this constant stream of real time data from

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<v Speaker 1>well everywhere, what new questions does That raise questions about

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<v Speaker 1>how much we rely on this data, about the ethics

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<v Speaker 1>of managing all this information, maybe even what it means

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<v Speaker 1>to be informed when literally everything around US is generating data,

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<v Speaker 1>something to ponder,