 All right, this week's Ion MPI is from Ublox. Ublox, one of our favorite GPS and Bluetooth module companies. Special thanks to Digi-Key for helping with these segments every single week. This is where we will show you where to get the Ion MPI, the new product introduction. So what is it this week? Okay. So I check this out on, I go to digi-key.com slash new and I check out what's new. I kind of read every blurb and I decide what I think is the niftiest new technology of the week. And also I try to make sure it's in stock so people can actually buy it, which is a new challenge that we're living with. So this week we are going to look at the Ublox angle of attack, the AOA1 dev kit. This is, there's two dev kits. There's the AOA1 and the AOA2. The AOA1 is less expensive and it has one transmitter that's the thing on the right and then one tag that's the thing on the left. And these are used to implement the new feature of Bluetooth Low Energy 5.1. A lot of people think of Bluetooth like 4.0 is Bluetooth Low Energy, but 5 and 5.1 added a new capability called angle of attack analysis and angle of departure analysis. And basically what this is for is it allows you to solve in what I call an age-old, well-trodden problem or challenge in electrical engineering and industrial design where you want to track something indoors and you want to know where it is in 3D space. And this is a, it's not shocking to people who've tried to do it, but for beginners they don't realize that's how incredibly hard this problem is. It's really, really hard to know where something is in 3D space. So, you know, a lot of times when people think about, okay, I want to find something in a room they think of like using a vision system. I thought this, I saw this cool image from Wikipedia from the IBO dogs. We were talking about IBO vision recognition at dinner a couple of nights ago. And you know, there's a robot dog and it has a camera and it can recognize this pink ball. And the ball has to be pink and it has to be round. And the vision system can recognize where it is in the room and it can use some triangulation to kind of tell how far away it is and what direction it's at. And this is what, you know, this is the closest approximation to very basic organic life vision recognition systems, right? There's, if you watch nature shows, there's shrimp and they're like, they can detect where the sun is or where the moon is, right? And that's the most basic kind of vision recognition. And if you want to do more object detection, some more complicated stuff, you can use stuff like open CV or TensorFlow. Again, it's a vision system. You do have to have really good lighting. The thing has to be recognized within your system. But you can kind of detect where it is in a room and you can also, again, you can use some mathematical analysis to determine kind of where it is in the room. But both of these really depend on having the object be fully visible and it has to be a recognizable shape and, you know, having very good lighting. If it's obscured, it won't work. And that's the challenge, right? A lot of people have object detection recognition systems that use vision. But if that thing is, you know, if that, you know, bowl is behind the computer obscured by the computer, the computer, the vision system won't recognize it. When people think a lot about, you know, detection of where something is, location detection of objects. A lot of people think about GNSS or GPS positioning systems that use satellites. This is our, you know, very popular GPS module. And these are really great, but they're only really great when you're outdoors. GPS does not work indoors, which is kind of a surprise. Not a surprise, but like a lot of people forget that. They're like, oh, why don't I just use GPS indoors? And the answer is, you can't. You can't use GPS indoors. It has to be outdoors and you need to have it be able to get a good fix. And even then, because of the way GPS works, you're not going to get precision or accuracy better than about 10 meters. If you want to get better accuracy, you can use something called RTK, which we covered also U-blocks. They're, you know, they have premier RTK hardware and designs that you can use. Check out this video which we did last year around this time about the RTK ZF9P GNSS RTK modules. These are also to be used outdoors, I think they can be used semi-outdoors, semi-indoors. And they do a cool thing that combines time of flight and GPS to get you centimeter level location detection. But again, really good for outdoor things like drones or robots that are outdoor or robotic cars. Those sorts of things use RTK. Again, not going to be good for indoor object recognition. All right, so you're like, well, what can you use for indoor object recognition? Well, you know, one of the things that is used now, and I'm not going to talk about time of flight because time of flight is still, for, you know, Wi-Fi is still under development. We haven't really seen anyone use it yet, although I know it's being developed and worked on. But traditionally, how you would do indoor recognition even now is you'd use something like a Bluetooth beacon. So people who know, you know, you have a tile or you have like the Apple eye tag, whatever. Those use beacons. And one of the things that you can do is you can use, you know, sometimes I say like, something that's a side effect is also something you can sense. So the farther you get away from a two wireless devices get farther away from each other, the signal strength drops. And that's bad because, you know, if you're a couple hundred meters away from a Wi-Fi hotspot, you're not going to get, you know, good data transfer, you're going to drop a lot of packets. You want to be really close to your Wi-Fi router to get good signal and you want to have a direct line of sight. Well, you can take advantage of that property and use it for detecting where something is in space. So you see here in the middle, you know, you've got a beacon. And if you have three transmitters that are transmitting or receiving the beacon data, they can kind of use the signal strength to kind of sort of triangulate where the object is. Only good for like a couple meters. I think it says here three to four meters. Also suffers from signals bouncing off of each other and off of walls. It's not great, but it's kind of what people use now. The good news is it's really cheap to implement. It's very easy. RSSI is built into like every radio chip. You don't need anything special. You can, you know, you can use a variety of different chip sets to do RSSI targeting, but you're only going to get that three to four meters. So what's interesting about this new Bluetooth 5.1 capability is, and this is something interesting that, you know, as I, as I was reading about it, it doesn't do RSSI like distance detection or time of flight distance detection. That's something different. It does angle detection. It'll tell you the angle of where the object is. But if you have multiple angles, like you can use that again with, if you have fixed points and you know where they are and you do the angle calculations, you can use it to detect where something is in 3D space. So you would put, you know, one of these, you know, detector transmitters in each of the four corners of your room, like in, you know, this, this, you know, mock up here and each one knows the angle and then you combine that data together. Boom. You have the location in 3D space of your object. You know, there's some math behind it, but the math isn't so bad. You know, you do need to have these kind of special funky, you know, transmitter base stations and I'll show it on the overhead because this is kind of what you're paying for. So yeah, so this is kind of interesting. So this is, you know, it's got a, you know, Bluetooth 5.1 module here. It's got some buttons and it's got like an Arduino kind of shield sort of shape and debug and everything. And the thing that's really interesting about it is this intense antenna array. It's got one, two, three, four, five antennas and it's got like this cross shape, which is also, I guess, part of it or no, sorry, that's the indicator, pardon me, that's the LED indicator, but it uses these antennas to determine the angle of attack, the angle of where it is. And one thing that I thought was kind of interesting is they're like, yeah, it's not distance and yes, you can use it to determine distance by again doing this triangulation. But there are some situations where you might actually really just want the angle. You want to know where somebody is coming at towards you or, you know, show the video where an object is with respect to a camera. Okay. This is available on DigiGee. Yeah. So the AO1, the XPLR AO1 Explorer, AO1 Angle Attack gives you one tag and the tag is, you know, you can make your own tag. The tag is really just an, there's nothing super special about it. It's just an NRF 51, sorry, NRF 52, 833, but the thing that you really want is this thing and then there's the AO2 kit, which is the same part number but AO2 and that one has four of each. So that's where you want to do real multiple devices detection within space. This would be really great for just angle of attack where is something in relation to this, you know, transceiver. All right. Okay. So we have a little bit of video, there's no audio, so you want to do a little bit of audio. Yeah. This is, you know, this is a really cute demo and they have a blog post that, you know, will link to, you can see this engineer showing off. There's a pan tilt module and there's a camera and she's holding or they're holding a tag and as they move through space, again, it doesn't know how far the person is but it knows the angle they're at in respect to the base of the camera. So the camera can pan around to find them and I think it shows that you don't need to have, you know, three transceivers, you can really get away with a lot of, there's a lot of applications where you can probably get away with just one. All right. Okay. And that's this week's IonMPI. Check it out. It's in stock now. IonMPI.