Juniper AIOps and Location

0:11 so indoor location has been one of these

0:13 passions there for 20 years the mission

0:15 to make indoor location on par

0:19 make a must have in the industry right

0:20 some i've been working on since my

0:21 aerospace adventure and what we're doing

0:24 here right now we're starting to make

0:26 marvelous

0:27 location aware and why is that important

0:30 it's important for things like coverage

0:33 right we want marvis to be started aware

0:34 of what happens when people start to

0:37 move their access points right and what

0:40 we're announcing today is really

0:43 the beginnings of identifying ap

0:46 location right

0:47 and this really brings in two pieces

0:49 into the marvelous adventure i mean

0:51 right now when you take the missed

0:52 network and deploy it if you look at the

0:54 problems we have with location one of

0:56 them is really getting the whole

0:58 deployment process easier now we made

0:59 that easier with taking echo how designs

1:02 make it very easier to port these

1:04 designs

1:05 into miss marvis that's part of the

1:07 deployment process

1:09 you know we made it easier when

1:10 deployers are actually deploying these

1:12 access points right with the mobile app

1:14 making sure they actually take pictures

1:16 locate where these aps are getting

1:18 deployed where we're taking the next

1:20 step is really bringing

1:22 auto ap placement to the party right

1:24 this is verifying that aps are actually

1:27 where they are supposed to be positioned

1:30 so this is probably the next big

1:31 announcement is really this is all based

1:34 on the fine time measurement of locating

1:36 making sure these access points are

1:37 relatively located where they're

1:38 supposed to be and why is this important

1:40 to marvis well i'm just interruption

1:42 there it's fine time measurement plus a

1:44 lot of aiml happening in the back end

1:47 and that's probably the you know the

1:49 other the other algorithm i talked about

1:51 is this

1:52 graph algorithm

1:54 is making sure we can actually locate

1:56 these ap's really so there's a

1:58 quadrilateral chain algorithm that

2:00 actually once you know the relative

2:01 location to the aps

2:03 there's a bunch of fancy map to make

2:05 sure those aps fit that data

2:08 right you can kind of visualize right

2:10 once i know the relative

2:12 distance between aps

2:14 the question is how do you make sure you

2:15 find the right geometry of where those

2:18 ap codes and that's the magic

2:21 just a simple question

2:24 is this so that if i if my installer

2:26 puts the ap

2:27 at a location that's not

2:29 where it is on the map it's going to

2:31 adjust the map or is it going to tell

2:34 the installer you need to move this one

2:36 three meters south because we'll get

2:38 better results

2:40 it it is going to tell

2:42 that to solve the problem of where ap is

2:44 lying about their location so where the

2:47 placement is on the map is right the

2:50 data doesn't match right so yeah so

2:51 keith let's it's basically the the plan

2:53 versus the actual right the age-old

2:55 problem so

2:56 we take we already make it easy because

2:58 we ingest that map with ap placements

3:00 today in the missed portal right

3:02 but that plan says oh mr installer put

3:04 the ap here and the installer goes

3:06 inside

3:08 says ah it's here or here it doesn't

3:09 matter or in some cases i've heard it's

3:11 opposite the building also right so

3:13 that's where they install and we've had

3:15 multiple customers report hey i'm

3:17 troubled shooting a wireless issue it's

3:19 on this ap 12 but this ap 12 is not

3:22 where it's on the map it's somewhere

3:23 else can you help me fix that right

3:24 different floors different areas so just

3:26 a quick one on on the analysis of what's

3:28 behind the scenes to make this happen

3:31 yeah so this is basically fine time

3:33 management all we all know about doll 11

3:35 mc this is basically leveraging the fine

3:37 time management it has never become an

3:38 industry standard in our clients you

3:40 know we are working with

3:42 customers like zebra that support it

3:44 it's usually not supported most of our

3:46 phones but really leveraging that to

3:47 actually find the distance between these

3:49 access points and that's and with the ai

3:51 magic that's what let's locate these aps

3:54 accurately

3:55 uh the other thing we're starting to

3:56 bring latin long into location and this

3:58 is two reasons for doing this one is for

4:00 connectivity for marvis another is for

4:03 our indoor location services

4:05 with that i think when you actually see

4:07 the demo you'll start to see the magic

4:09 of this of making sure these aps

4:11 actually get put where they belong

4:13 there's probably the guest star the big

4:15 retail customer that basically had the

4:16 problem of

4:17 complaining about coverage there was an

4:19 access point on the map when he went to

4:21 the back room the access point wasn't

4:23 there right these are the type of

4:24 problems you deal with in

4:26 real deployments and the the two key

4:28 things i want to talk about right where

4:29 does ai come into play so you heard

4:31 about rtt you know find uh finding

4:33 measurement yes we are definitely

4:34 adopting that but that doesn't help

4:36 solve non-linear side problems and i

4:38 have to solve in a healthcare deployment

4:40 in a school network in a university i

4:43 have to be able to solve for

4:46 verifying the location of an ap install

4:48 which is not line of sight and that's

4:50 where the ai ml engine comes into play

4:51 to say okay what can i do in terms of in

4:53 addition to rtt finding measurement

4:57 where can i solve for the nylon sides

4:58 that's number one number two we want to

5:00 solve this not just for greenfield

5:02 deployment or installer going on site

5:03 and putting an ap and how they can

5:04 automatically place apis on a floor plan

5:07 we also want to solve this for

5:08 brownfield deployments for customers

5:10 who've been deployed with us for the

5:11 last two or three or four years we want

5:13 to give them the benefit to get a view

5:15 of the actual install versus what was

5:18 the plan installed on the icahoe import

5:20 and our takeaway from here is

5:23 that fine time measurement thing

5:25 and probably the other thing is there's

5:27 two

5:28 key algorithms here one is getting the

5:29 eps placed correctly the other key

5:32 algorithm is dealing with none line of

5:33 sight

5:34 you know the good thing about fine time

5:36 management it works great line of sight

5:38 questions how do you handle none line of

5:40 sight and that's the problem the problem

5:41 you can deal with

5:43 a question with the ap placement

5:45 is there an assumption that all the aps

5:47 will be ceiling mounted or what if you

5:49 like mount aps on a wall or set it on a

5:51 table or a cabinet would that have any

5:53 impact initially we're looking at the

5:55 ceiling that's 90 percent of the

5:56 population and then we'll involve this

5:58 with the antenna model to also look at

5:59 tilt as well as as xyz height and

6:02 probably the other key thing i didn't

6:03 mention is this also takes care of

6:05 rotation

6:06 in addition to ap it's actually

6:08 doing the directionality making sure the

6:10 ap is pointed in the right direction

6:12 that's for a virtual ble

6:14 location use case

6:16 could you tell this vertical then yes

6:18 yeah we have the vba arrays for that

6:20 exactly

6:21 yeah so really quickly from a a

6:23 demonstration perspective

6:25 for brownfield right what you'll see

6:28 here is these are ap's on a map customer

6:30 goes and clicks and this is going to

6:32 show up in the next couple of months on

6:33 your dashboards customer goes and clicks

6:36 auto locate auto place the back end

6:38 system run this magic and automatically

6:40 will then place the aps in the right

6:42 placements on the floor plan so urine

6:44 will do anything except say auto locate

6:46 auto place right and now let's get to so

6:49 i just add absolutely on the so on the

6:51 orientation troy um it doesn't actually

6:54 so much matter right we have a

6:56 we have a accelerometer in the ap so we

6:58 know the orientation of the aps but it

7:00 doesn't so much matter the orientation

7:02 for refine time measurement

7:04 for connectivity or for locating them

7:07 it's more for location not for

7:08 connectivity correct yeah from a

7:10 from a ap

7:12 placement it doesn't so much matter

7:14 so you saw the magic we do for

7:16 brownfield right so imagine you heard

7:17 about our large customers and they all

7:19 want to get a better visibility of hey i

7:22 know i gave a plan i know the installer

7:24 is a good installer but we know it

7:26 should happen

7:27 the brownfield mechanism no anchors

7:29 needed we would auto detect anchors we

7:31 will then place the grid for you and

7:33 place the aps in the maps again marv is

7:35 coming into play order remediation all

7:37 you say is authorize the action

7:39 marvelous takes care of the rest now

7:41 comes the green field i'm deploying

7:43 large networks today multi-floor

7:45 buildings huge campuses or thousands of

7:48 branch locations what can i do to save

7:50 time during the install process right

7:53 today

7:54 uh installer goes in the maps already in

7:57 the system

7:59 they either have the ap placements as

8:01 per the ikaho import or they haven't

8:03 done that import installers are going in

8:05 and pulling ap's from the sidebar and

8:07 placing them on the map three ap s4ap is

8:09 not a big deal just start talking about

8:11 10 20 30 ap you have to do four or five

8:13 sites a night that becomes a nightmare

8:15 so what can we do from a green field

8:18 install perspective to save the

8:19 installers time and therefore the end

8:21 customer money because it's much faster

8:24 now to get the network set up and get

8:26 the real

8:28 location of apes on the map again

8:30 no need for any adjacent technology

8:32 we're leveraging what we already have

8:33 and our ai location engine to deliver

8:36 this so as the installer goes about

8:38 their work they essentially give us the

8:40 measurement of just the first word

8:41 they've deployed anywhere in the ceiling

8:43 that they have and then that's it once

8:46 the installer gives us the measurement

8:48 for because we need some source of truth

8:50 and while the installer is doing their

8:51 job you're gonna give us hey here's the

8:53 x y for this location by just putting it

8:55 on the floor plan that's it once they're

8:58 done that they go again and say auto

9:00 just like you do rm optimize now you now

9:02 go and do auto place auto locate

9:05 and there you see it

9:07 you take the action the ai engine in the

9:09 back end then runs its calculations gets

9:11 all the information about all the aps

9:14 and

9:14 magic happens literally

9:17 there you go

9:19 it's as easy as that how much time do

9:21 you need can you do it as soon as you're

9:23 done installing the last ap that is

9:25 correct the the goal that we have in the

9:27 testing you've done so far is within 10

9:28 to 20 minutes it should be all done so

9:30 the goal is to like when the install is

9:32 done make sure that they're click on

9:33 auto place and it happens and then they

9:35 can go home yeah

9:37 you don't have to come back the next day

9:38 you don't have to do a you know a site

9:40 survey to validate

9:41 ai is doing the job for you yes or well

9:44 after you do that auto

9:47 placement do you provide

9:49 a deviation

9:50 say

9:51 i did upload a map using echo how

9:54 and i have the ap placements there

9:56 but when you run this and it's all

9:58 changed will you give me that deviation

10:00 so in the brown field we will be giving

10:02 you a view also of this is where the ap

10:05 actually so right now you saw marvis

10:06 take care of it and just move the aps

10:08 but we're also looking at again is to

10:10 give you the evidence to say and let you

10:12 authorize that change because you may

10:13 say no let the aps be where they're at

10:16 don't accept the change or you may say

10:19 let me send a tech on site to make that

10:20 change happen right so that the reality

10:22 matches what has been built we will be

10:25 able to give you a view of here's the ap

10:27 placement that the location engine found

10:29 which is where this is where the ap is

10:31 at as per the plan would you like to

10:33 accept the new placement or do you like

10:35 to trigger a tech workflow to go and

10:37 move the ap okay

10:39 is this ga today no this is in the works

10:42 we're going to be getting into betas i

10:44 was in the next couple of months and you

10:45 but you will see this in the i would say

10:47 early for time but we are super excited

10:49 about this we've we've been quiet about

10:51 this because we've been running our own

10:53 simulation validations large networks

10:55 small networks domes multi-floor you all

10:58 know about our nvidia deployment uh

11:00 we've actually tried this out there done

11:02 simulations to see how good we are we

11:04 are now confident we can ship this very

11:06 soon so yes still include in the

11:09 marvelous license

11:10 this would be part wi-fi storage part

11:12 marvelous correct

11:14 once you have this data you also then

11:17 use the ai information to

11:20 say you need another ap here

11:22 bingo so you talk you heard bob talk

11:25 about the coverage whole aspect now that

11:27 we'll get the actuality placements mars

11:30 and already know there's a coverage

11:31 whole problem but it'll show you based

11:33 on what was imported that coverage whole

11:35 efficacy becomes much higher now because

11:37 we have the actual location of the ap so

11:38 absolutely yes short answer yes yes

11:43 um so the workflow flow for that is the

11:45 um is it auto placing them um

11:48 directly or do you have to place those

11:50 aps on the floor first and then auto

11:52 placement occurs auto placement directly

11:57 into the organization i hit auto place

11:59 and they're on the floor there you go

12:01 perfect yeah yes sir as a follow-up

12:03 keith's question instead of adding aps

12:05 could it suggest moving aps for better

12:07 placement

12:08 of those on the map so that we already

12:10 do as part of our coverage hole where we

12:12 will say assume that the reality matches

12:14 what was the plan and our current marvin

12:17 uh marvis coverage whole action will

12:18 tell you if an ap placement is

12:20 recommended or an ad is recommended that

12:22 that is taking care of today

12:24 so i know i'm over time thank you so

12:26 much okay one last question just for you

12:28 okay i just have a quick question i

12:30 missed how many truths that you actually

12:32 need to key in and then i missed what

12:34 the accuracy is is it like a meter two

12:37 meters two meters ninety percent of what

12:38 the current stimulation is is showing we

12:40 have actually gotten less than one meter

12:42 but i'm not gonna say that publicly oh i

12:44 just did it

12:48 what i stand by and and three truths did

12:50 you say in terms of for the green field

12:53 deployments where we have no history and

12:54 no data to collect we look at these

12:56 three anchors yeah but that is like

12:57 quality installed installing we have the

12:59 mobile app yeah they just point that

13:00 mobile app gets the xy that it's as

13:02 simple as that

13:03 okay and this helps us also solve the

13:05 problem of i don't need

13:07 i know i'm not supposed to say this and

13:08 bob said to me don't say it

13:10 but i don't need an outside signal to

13:12 tell me the location of my anchor right

13:15 because often times you get in

13:16 deployments where you don't have an

13:17 outside satellite signal what do you do

13:19 there right so therefore in this

13:21 situation i'm handling both

13:23 the outside deployments which have

13:25 satellite signal which i don't need or

13:27 internal deployments only right again

13:30 think of

13:31 of hospitals and patient rooms and think

13:33 of higher ed and hallways you don't have

13:36 underside to a window that gives you

13:38 some signal

13:39 all right with that over to the next

13:42 session any last questions for bob

13:44 before we transition

13:45 tom is here go ahead tom

13:47 well anybody have any last questions for

13:49 bob

13:50 yeah i'm unliking after this oh then i

13:52 do have one question if i may

13:54 going way back on one of your earlier

13:56 slides when you showed the tools there

13:58 was a bunch of circles that said new

14:01 is that what marvelous release seven is

14:04 yes so if you look in the chat in the

14:06 data science toolbox i mean the team is

14:08 like this particle chain thing that's a

14:10 new algorithm for solving the geometry

14:13 of auto ap placement so that's a new

14:15 algorithm that we've added into the

14:16 toolboxes and so if we define release

14:18 seven that's what it is

14:20 yes i would add that to release that

14:22 that's great okay

14:24 well we had what you'd mentioned earlier

14:27 about adding lat long

14:29 how does that interface with what you

14:32 just mentioned is that

14:33 that that's for our location there's two

14:36 stories here one is connectivity like

14:38 marvis which is more around network

14:39 operations the other part is for indoor

14:41 location services

14:43 a lot of our mobile app customers want

14:45 latin long to be returned in digit xy

14:48 and that ties back to the boris client

14:51 android zebra windows because that is

14:52 essentially a combination of location

14:54 and network so that's how the lat long

14:56 piece comes across across the board

14:58 would we just set light long on those

15:00 three anchors

15:02 no we would actually get the latch long

15:04 from the client

15:05 and then and do all the calculation the

15:06 back end so

15:08 all right with that thank you so much

15:10 and overall to the next session actually

15:12 going to take a real quick break because

15:14 we've been up here for an hour and a

15:15 half and we want to make sure that

15:16 everybody has a chance to stretch their

15:17 legs