The document summarizes using MongoDB and Spark for IoT analytics on aircraft ADS-B data. Key points include:
- ADS-B data from a SDR antenna is ingested into MongoDB for real-time dashboards and historical analysis using aggregation pipelines.
- The aggregation framework enables ad-hoc queries on aircraft attributes like speed, altitude and operator without ETL.
- The BI connector projects data to SQL for analytics tools. Examples analyze FedEx flight paths and aircraft types by altitude and speed.
- Spark is used for machine learning like k-means clustering on attributes to identify patterns in the data.
MongoDB World 2016: The Best IoT Analytics with MongoDB
1. The Best IoT Analytics with
MongoDB
Jake Angerman
Sr. Solutions Architect
MongoDB
2. Sessions:
1. Building an IoT Application that Will Work
Next Year
2. Building IoT Applications the Right Way
3. The Best IoT Analytics with MongoDB
Track Overview
✔
✔
6. #MDBW16
Tin Can Reveal
homemade antenna
(6.9mm quarter-wave whip)
NooElec NESDR Mini 2 SDR $23.00
USB extension cable $10.00
RF cable RG316 female to MCX male $5.50
?n can $2.87
Total: $41.37
6.9cm antenna
USB SDR
dump1090
17. #MDBW16
Analytics without Data Migration
Database
Historical
Analysis
Devices
Dashboards
• No bulk or incremental ETL required
• One language for both real-time and ad-hoc queries
33. #MDBW16
BI Connector
• New in MongoDB 3.2 Enterprise Advanced
• Mapping and transformation layer
• Projects smaller parts of large data sets for reporting
34. #MDBW16
MongoDB Query LanguageSQL
BI Connector Data flow
MongoDB
BI
Connector
Mapping
metadata
ApplicaAon data
{name:
“Andrew”,
address:
{street:
…}}
Document Table AnalyAcs & visualizaAon
37. #MDBW16
Altitude vs Speed
• Two predictable clusters:
• turbine aircraft at cruising
altitude
• piston aircraft at lower
altitude
38. #MDBW16
Altitude vs Speed
• Two predictable clusters:
• turbine aircraft at cruising
altitude
• piston aircraft at lower
altitude
39. #MDBW16
Altitude vs Speed
• Two predictable clusters:
• turbine aircraft at cruising
altitude
• piston aircraft at lower
altitude
• Outliers are Cessnas
reporting 51,000+ ft
43. #MDBW16
Spark Connector Diagram
• diagram
MongoDB Connector for Hadoop (with Spark Plug-in)
https://github.com/mongodb/mongo-hadoop
MongoDB Connector for Spark
https://github.com/mongodb/mongo-spark
44. #MDBW16
Supervised Unsupervised
Classification
• Naive Bayes
• Support Vector
Machines
• Random Decision
Forests
Clustering
• K-means
Regression
• Linear
• Logistic
Dimensionality
Reduction
• Principal Component
Analysis
• Singular Value
Decomposition
Spark Machine Learning
45. #MDBW16
K-Means Clustering
The K-Means algorithm aims to
minimize the sum of squares of the
distance between the points and the
centroid of each cluster.
source: Lovro Iliassich, toptal.com