Processing and retrieval of geotagged unmanned aerial system telemetry

Processing and Retrieval of Geotagged Unmanned Aerial System TelemetryKristopher Kane

2 © Hortonworks Inc. 2011 – 2016. All Rights Reserved

Who am I?Kristopher Kane – Systems Architect, Hortonworks

What is the purpose of this topic? Commercial and military unmanned aerial systems (UAS) require that the decision

making data points be accessible remote They produce a lot of telemetry and decisions are made based on the timeliness and

accuracy of that telemetry Some UAS carry additional payloads for full motion video and electro optical sensors We will cover creating an application that covers this ingesting and searching on UAS

telemetry


Example Telemetry Types

Military grade: Key-Length-Value (KLV) – embedded telemetry as a elementary stream PID inside an MPEG 2 transport stream - See MISB for the open specification– interesting data points like center of frame lat/lon and video angle – thousands of keys

Hobby grade 1: MAVLINK – APM (ArduPilot Mega) telemetry that covers battery voltage, airspeed, temperature, pitch, roll, yaw angles and acceleration, GPS data, etc– open source – hundreds of keys

Hobby grade 2: FrSky receiver telemetry with a subset of what you get from MAVLINK– closed source but has been reversed engineered– a few keys


Telemetry Velocity – What is the problem to be solved?

Hobbyist level small UAS– open source hardware, software and protocol spec – ArduPilot Mega– 150 sensor points– 3 sets per second equals 450 points per aircraft/sec– Yesterday, FlightAware recorded 35,662,229 location positions/hour from transponder ground

stations but this is only includes a few sensor points

Current manned aircraft– At 0500 local today (28JUN2016), FlightAware was tracking 9,804 aircraft in the air

4,411,800 data points per second29,412 entries per second

Ingest Architecture


Ingest Architecture

Ground Control Station915 MHZ - Serial

Apache Knox

Undertow HTTP API

4G -TCP HTTPS

KafkaStorm

TCP HTTP

possible to embed this in Knox

custom topology entry

Other Consumers

JSON HBase

spatial missionsSolr

telemetry

Aircraft


Ingest Architecture - Spatial based load distribution

* Alerts like congested airspace will happen here

Partition based on geohash prefix as a simple dimension for distribution

Increase prefix characters as load increases. This works for:– Kafka broker partitions– Storm bolts - a couple grouping options here– Pre-split HBase regions


Geohash

Created for a URL shortening service in 2008 Encodes latitude and longitude into a string – two dimensions into one which is

important for HBase key scanning My house is at decimal degrees: 35.45380534178051,-78.8184043765068 geohash: dnrcwqjk More characters = more precision Geohash doesn’t follow the base-32 RFC - read about that and don’t lose sleep like I did


Geohash

http://geohash.gofreerange.com/


Geohash Decoding

My house (area) geohash: dnrc

Using base-32:

d (base-32) = 12 (base-10) = 01100 (binary) n = 20 = 10100r = 23 = 10111c = 11 = 01011

Binary representation = 01100-10100-10111-01011

From the geohash Wikipedia article


Geohash Decoding – House Latitude

01100-10100-10111-01011Bits alternate longitude (even) and latitude (odd) respectively, left to right.

Latitude = 1011001001 bit min mid max latitude1 -90.000 0.000 90.000 45.0000 0.000 45.000 90.000 22.5001 0.000 22.500 45.000 33.7501 22.500 33.750 45.000 39.3750 33.750 39.375 45.000 36.5620 33.750 36.562 39.375 35.1561 33.750 35.156 36.562 35.8590 35.156 35.859 36.562 35.5080 35.156 35.508 35.859 35.3321 35.156 35.332 35.508 35.420


Why Apache Knox? Let Knox handle authentication - It will provide the ‘user.name’ query parameter appended to your

parameter set

KNOX-670 allows for the hosting of simple web applications

Custom APIs can be added to your topology with only a few lines of XML for simple cases:

<rules> <rule dir="IN" name="DRONE-TELEMETRY/drone-telemetry/inbound" pattern="*://*:*/**/drone-telemetry/{path=**}?{**}"> <rewrite template="{$serviceUrl[DRONE-TELEMETRY]}/{path=**}?{**}"/> </rule></rules>

<service role="DRONE-TELEMETRY" name="DRONE-TELEMETRY" version="0.0.1"> <routes> <route path="/drone-telemetry/**"/> </routes></service>

data/services/drone-telemetry/0.0.1/service.xml

data/services/drone-telemetry/0.0.1/rewrite.xml

Egress Architecture


Egress Architecture - User Query Access

Apache Knox

UndertowHTTP API

TCP HTTP

User – mobile app or browser based

HTTPS – Twitter Oauth/LDAP

HBasespatial missions

Solrtelemetry


Well Known Text Format Both the Solr and HBase examples following use the Well Known Text format to specify

polygons This standard requires the points to be in counter clockwise order Topologically closed - make the last point the first point


HBase Queries – General Idea Encode two dimensions (latitude and longitude) into one (geohash) Use geohashes as row scanning filters Use spatial libraries against the latitude and longitude column families for accurate

calculations like distance and points inside geometries Rely on external libraries like JTS or Spatial4j You have to implement everything yourself


HBase Queries The Undertow API will accept a bounding box set of lat/lon coordinates from our user’s

map The web application will format that in WKT standard for the follow on geometry classes Ensure you close the polygon with the start point

POLYGON ((-78.818951 35.4535516, -78.818960 35.4535516, -78.818951 35.4535560, -78.818941 35.4535512, -78.818951 35.4535516))

Geometry query = reader.read(polygon);

WKT


HBase Query - Show Me Missions In This Polygon (map) Get the polygon centroid and compute minimum boundaries by reversing the geohash

into latitude and longitude Scan each geohash as a PrefixFilter to get candidate rows

*This code is from Chapter 8 of HBase In Action – I highly recommend this book.

GeoHash[] minimumBoundingPrefixes(Geometry query) ...public Set<QueryMatch> query(Geometry query) throws IOException { GeoHash[] prefixes = minimumBoundingPrefixes(query); et<QueryMatch> ret = new HashSet<QueryMatch>(); for (GeoHash prefix : prefixes) { byte[] p = prefix.toBase32().getBytes(); Scan scan = new Scan(p); Filter filters = new FilterList(new PrefixFilter(p), new PageFilter(500L));


HBase Query - Show Me Missions In This Polygon (map) Check the returned candidate rows by doing a point lookup of the lat/long CFs against

our map provided polygon

*This code is from Chapter 8 of HBase In Action – I highly recommend this book.

for (Iterator<QueryMatch> iter = ret.iterator(); iter.hasNext(); ) { QueryMatch candidate = iter.next(); Coordinate coord = new Coordinate(candidate.lon, candidate.lat); Geometry point = factory.createPoint(coord); if (!query.contains(point)) { iter.remove(); exclusionCount++; }}

‘query’ is our polygon from the map.


Solr Query - Show Me Missions In This Polygon (map)

&fq={!field f=geo_location}Intersects(POLYGON((-80.12878 35.85121, -80.12878 34.50429, -77.93152 34.50429, -77.93152 35.85121, -80.12878 35.85121)))=*:*&sort=gcs_time%20desc

35.85121, -80.12878

34.50429, -80.12878 34.50429, -77.93152

35.85121, -77.93152


Solr Query - Show Me Missions In This Polygon (map)

"response":….[ { "mission_name":"kris-02", "gcs_time":1466388208, "latitude":35.4534768, "roll":-0.00834990758449, "user.name":"tom", "ingest_date":"2016-06-20T02:03:28Z", "yaw":0.187950670719, "pitch":-0.0191747546196, "longitude":-78.8189403},…]}

35.85121, -80.12878

34.50429, -80.12878 34.50429, -77.93152

35.85121, -77.93152


Solr Query – Point in Polygon breakdown

&select?fl=mission_name,latitude,longitude,gcs_time&fq={!field f=geo_location}Intersects(POLYGON((-80.12878 35.85121, -80.12878 34.50429, -77.93152 34.50429, -77.93152 35.85121, -80.12878 35.85121&q=*:*&sort=gcs_time desc

<fieldType name="location_rpt" class="solr.SpatialRecursivePrefixTreeFieldType" spatialContextFactory="com.spatial4j.core.context.jts.JtsSpatialContextFactory" geo="true" distErrPct="0.025" maxDistErr="0.001" distanceUnits="kilometers"/>

Polygons require this.‘geo_location’ is of this type.

Don’t forget to add JTS libs to Solr server!


HBase Query – Show me current missions

The HBase table is created with a TTL and the row key is the mission name This table expects high velocity but will only store one row per mission Data is ‘UPSERT’ HBase has a cool new feature that allows for no compaction TTL clean up which is

perfect for this table’s purpose: https://issues.apache.org/jira/browse/HBASE-14468 Simply row scan the table for the mission list


Solr Query – Show me current missions

Provides a count list of the facet fields

select?facet.field=mission_name&facet=on&fq=ingest_date:[NOW-1MINUTE TO NOW]&q=*:*&rows=0&start=0

http://localhost:5000/solr/mavlink/select?facet.field=mission_name&facet=on&&fq=ingest_date:[NOW-1MINUTE%20TO%20NOW]&indent=on&q=*:*&rows=0&start=0&wt=json

http://localhost:5000/solr/mavlink/select?facet.field=mission_name&facet=on&&fq=ingest_date:%5BNOW-1MINUTE%20TO%20NOW%5D&indent=on&q=*:*&rows=0&start=0&wt=json

















Solr Query – Distance and temporal filtering with sorting

fq=ingest_date:[NOW-10SECOND TO NOW]AND{!geofilt pt=35.4,-78.81 sfield=latlon d=20}&q=*:*&sort=gcs_time desc

Show me:Mission data points in the last 10 seconds, within 20 km of my current positionand sorted by most recent ground station time

Want a unique list of missions?

facet.field=mission_name&facet=on&rows=0

http://localhost:5000/solr/mavlink/select?fl=mission_name,ingest_date,latitude,longitude,user.name,pitch,yaw,roll,gcs_time&fq=ingest_date:[NOW-10SECOND%20TO%20NOW]AND{!geofilt%20pt=37.3,-121.92%20sfield=latlon%20d=20}&indent=on&q=*:*&sort=gcs_time%20desc&wt=json


Thank You

Processing and retrieval of geotagged unmanned aerial system telemetry

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