Processing and Retrieval of Geotagged UAS Telemetry

Processing and Retrieval
of Geotagged
Unmanned Aerial
System Telemetry
Kristopher 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 second
29,412 entries per second

Ingest Architecture
Ground Control Station
915 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 missions
Solr
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 = 10100
r = 23 = 10111
c = 11 = 01011
Binary representation = 01100-10100-10111-01011
From the geohash Wikipedia article

Geohash Decoding – House Latitude
01100-10100-10111-01011
Bits alternate longitude (even) and latitude (odd) respectively, left to right.
Latitude = 1011001001 bit min mid max latitude
1 -90.000 0.000 90.000 45.000
0 0.000 45.000 90.000 22.500
1 0.000 22.500 45.000 33.750
1 22.500 33.750 45.000 39.375
0 33.750 39.375 45.000 36.562
0 33.750 36.562 39.375 35.156
1 33.750 35.156 36.562 35.859
0 35.156 35.859 36.562 35.508
0 35.156 35.508 35.859 35.332
1 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 - User Query Access
Apache Knox
Undertow
HTTP API
TCP HTTP
User – mobile app or
browser based
HTTPS – Twitter Oauth/LDAP
HBase
spatial missions
Solr
telemetry

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

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 position
and 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 UAS Telemetry

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Processing and Retrieval of Geotagged UAS Telemetry