an open-source infrastructure for real-time automatic ...•opportunistically stream collected data...
TRANSCRIPT
An Open-Source Infrastructure for Real-Time AutomaticAgricultural Machine Data Processing
Yang Wang Sam Noel James Krogmeier Dennis BuckmasterOpen Ag Technology and Systems (OATS) Center
Purdue University
[1] httpswwwisoblueorg [2] httpskafkaapacheorg [3] httpopenagio [4] httpsgithubcomOATS-Groupwheres-my-isoblue [5] httpsgithubcomOpenATKTrialsTracker
Connected Machinery via ISOBlue 20
ISOBlue 20 [1] is an open-source ag IoT It is made tobull Be dust and weatherproofbull Be wake on CAN activitybull Collect machine data via ISOBUS diagnostic portbull Opportunistically stream collected data to Cloud
via a 4GLTE connection
CONNECTED MACHINERY CLOUD WEBMOBILE APPS
Cloud Architecture Powered by OADA API Real-time Data Viz amp Analytics via Apps
bull Ag machine data no longer ldquotrappedrdquo
bull Real-time diagnostic info as-harvested as-applied data
Figure 1 (left to right) an assembled and a deployed ISOBlue 20
Apache Kafka [2] manages the collected log on ISOBlue 20 it is capable of handling massive amount of incoming data
bull Microservice-based (scalable)
bull Handles massive amount of incoming data
bull Stream-processes data continuously
machines
hellipsprayers hellipharvesters
Graph database and linked resources in OADA
helliptiled-mapsdry-yield-map
Non-versioned links
hellipgeohash-index
Resource-watching microservice in OADA
Open Ag Data Alliance (OADA) API [3] is an open-source ag data exchange API that offers data security privacy and interoperability
Low-level scripts Kafka broker
Kafka MirrorMaker
Kafka queue
Workflow amp Software Used Workflow amp Software Used
Connected machinery
ISOBlue 20
OADA conformant Cloud
Workflow amp Software Used
Applications
Kafka brokeruservices
Kafka queue
Graph data store
Websockets
TrialsTracker Where-is-my-ISOBlue
T T
Figure 3 a screenshot of where-is-my-isoblueweb app interface
Where-is-my-ISOBlue [4] is a proof-of-concept web app that displays the real-time GPS tracks and debug info for different deployed ISOBlue 20s
TrialsTracker [5] enables user to ldquoaggregate-by-fingerrdquo to compute average field yield and compare trails with both historic and streaming data
AcknowledgementsMore info on ISOBlue 20
bull Offer intuitive visualizations to end users
bull Process both historic and real-time data
Figure 2 high-level Kafka workflow
Figure 4 a screenshot of TrialsTracker web app interface