CON3993 Java in the Air - A Case Study for Java-Based Environment Monitoring Stations

8/18/2019 CON3993 Java in the Air - A Case Study for Java-Based Environment Monitoring Stations

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Java in the Air: A Case Study for Java-Based

Environment Monitoring Stations

Marco Carrer, Eurotech

Andrew Gilbert, Oracle


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Agenda

•

IoT Present and Challenges

•

Java, OSGi and Eclipse Kura: IoT Gateway Services

•

Embedded Data Streams: Edge Analytics

•

Use Case: Environment Monitoring Stations

•

Q&A


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Gartner’s Hype Cycle


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IoT Challenges Where IoT projects most often fail!

M2MCommunication

Infrastructure

DeviceFirmware /

Application

Business Application

Sensors &Device

Hardware

Business Application

Integration

1

2 3

46

• Selecting andintegrating sensors,devices, sensors,

human machineinterfaces (HMI),

Meters, legacy fieldbusses & actuators

•

Ensuring long life

support• Meeting certification

requirements

•

Selecting andintegratingoperating system,

device support /drivers

• Implementing thebusiness logic

• OptimumM2Mprotocols

• WAN costreduction

•

Security

•

Device data management• Device life cycle management• Security

5

•

Decoupling ofproducers andconsumers of

data• Write speeds

• Real-time datastreams

•

Data storage

• Standard APIs• Ready to use

adapters for

standardapplications

•

CEP / ComplexEvent Processingcapabilities

1 2 3

4 6

5

7

•

Application development & life cycle management•

Dashboards, user interaction & interfacing•

Integration (Big Data, social networks, enterprise IT)

7


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Challenges inthe IoT Era

Enabling

New Services

and faster

time to

market

Real-time

Data Data

Analysis &Management

Minimize

Downtime –

High

Availability

Cloud based

Services key

to reduce cost

& complexity

Common

Development

Environment

across M2Msolutions

Faster local

decision

making

Devices in-

market for longer

duration

Risk of

opportunity

lost or non

compliance

Improving

operational

efficiency

Integration

and

Automation

with existingsystems

Portability,

security with

scalability

Extracting

value from

large

amounts of

data

Support for

a wide

variety

of devices

Intermittent

connectivity

Security of

Devices and

Data

Protection


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“Today, 11% of data is machine generated. By 2020,that figure will rise to 40%, with a total of 20 billion

devices.”

IDC Enterprise WorldwideServer Predictions

March 2013

Volume of data is increasing rapidly


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IoT Architecture

BusinessApplications

Sensors,Actuators,

Displays,!

@

Application

Framework

+Multi-Service

Gateway

M2M/IoT Integration Platform on CloudM2M

Integration

Platform


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IoT Gateway StackIncrease productivity and lower time to market

OSGi

on

Linux

Hardware

Java SE Embedded

Code

Code

Code

D e v e l o p e r ’ s P

r o d uc t i v i t y


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Java TodayThe most popular programming language

for Enterprise Applications

9+ Million Java DevelopersStewardship & Innovation


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Java TomorrowThe most popular programming language

for Enterprise & Embedded & IoT Applications

3+ MILLIONJAVA DEVICES


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Linux OS

Embedded App

• Modular software for IoT Gateway Service

• Manage cloud connectivity

• Network configuration and administration

• Support for different protocols

• Remote management and access

•

Integrated development environment• Application portability

• Open sourced in Eclipse IoT

ESF, with Kura at its foundation, iscommercially supported, remotely managed,and optimized for industrial gateways and

applications.

Java / OSGi

Open HWIndustrial

HW

Eclipse Kura


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Kura Services

Java SE 7 (Oracle Java SE Embedded, OpenJDK)

OSGi Application Container (Eclipse Equinox, Concierge)

Device Abstraction

javax.comm

Basic Gateway Services

DB Service

Clock Service

Device Profile

Watchdog

Network Configuration Network Configuration

Field ProtocolsConnectivity and Delivery

Data Services MQTT Paho

A d m i n i s t r a t i o n G U I

Applications

Your Application

R e m o t e M a n a g e m e n t

C o n f i g u r a t i o n

M a n a g e m e n t

javax.usb / udev

Cloud Services

Your Application

Firewall,

Port ForwardingLink Monitors

Cellular, Wi-Fi,

Ethernet

GPS Position GPIO / SPI / PWM / I2C

Modbus

CANBus

Custom Protocols

U p d a t e s

M a n a g e m e n t

R e m o t e A c c e s s

( V P N )


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Kura Developers’ ExperienceDesigned from ground-up for developers

Emulate on PC Deploy on Target Cloud Managed

Start developing your M2M

application in the comfort ofyour PC.

• Full Eclipse Integration

• Target Platform Definition

• Emulated Services

• Run/Debug from Eclipse

•

Support Mac/Linux Hosts

When you are ready, deploy

your application on thegateway.

• One-click Deployment

• Eclipse Plugin

• Remote Debugging

Provision your application to

field devices from the Cloud.

Manage your application

configuration and lifecycle

from a Cloud infrastructure.

No more field visits!

• Web-based Console

•

REST API Integration

• Smart Alerts


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Key Elements of Connected Intelligence

Always-on

devicesconnected to

variety of

sensors and

running multiple

software

applications

1

High-frequency

data analysis forinstant decision

making and

automation of

information flows

2

Maximizing value

from hi-velocitydata in real time

3

Fast DataReal-Time AnalyticsIntelligent Devices


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The value of data decreases over timeEnsuring Real-Time Accuracy, Efficiency, and Scale

Business event

Action Time

B u s i n e s s

V a l u e

Data captured

Analysis completed

Action taken

Source: Richard Hackethorn’s Component’s of Action Time


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Complex Event Processing - CEP

! Method of tracking and analyzing

data combined from multiple streams

to infer events or patterns that

suggest more complicated

circumstances.

!

Goal is to identify business meaningof events (such as opportunities or

threats) and respond to them as

quickly as possible.

Source: http://en.wikipedia.org/wiki/Complex_event_processing

Event Patterns

Event StreamFine-grained simple events from

sensors and edge devices

Complex Events

Machine module non-functional, power outage,

device tampering, etc.


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Complex Event Processing

• Filtering

–

New stream filtered for specificcriteria, e.g. temperature > 200 F

•

Correlation & Aggregation

– Scrolling, time-based windowmetrics, e.g. average heart pulserate in the last 3 days

•

Pattern Matching

–

Notification of detected eventpatterns, e.g. machine events A,B and C occurred within 15minute window

• Geospatial, Predictive Modelingand beyond

–

Immediate recognition of

geographical movement patterns,apply historical businessintelligence models using datamining algorithms

Event Patterns

Event Patterns

Complex Events

Machine module non-functional, power outage,

device tampering, etc.

Event StreamFine-grained simple events from

sensors and edge devices


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CEP Engine

Query

Query

Oracle Event Processing Embedded OEP-E: High-Level Architecture

I n p u t A

d a p t e r s

O u t p u t

A d a p t e r sevent

event

event

Real-time event dataContext-aware filtering, correlation,aggregation and processing of data

Processed businessevents for downstream

applications

event

event

event

Sensors

Backend Applications


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Continuous Query Language - CQL

•

CQL is based on standard SQL with extensions for streaming data

–

CQL queries support filtering, partitioning, aggregation, correlation(joins across streams), and pattern matching on streaming and

relational data

–

Extends standard SQL by adding notion of Stream, operators for

mapping between relations and streams, and extensions for patternmatching

–

Window operator (e.g. RANGE 1 MINUTE) transforms stream into

a relation

•

Example:

–

SELECT AVG(temperature) AS avgTemp, tempSensorIdFROM temperatureInputStream [RANGE 1 MINUTE]

GROUP BY tempSensorId


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Efficient Handling of Streaming Data FlowEvent Processing Network (EPN) Example


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Use Case: Environmental Monitoring

21

From this!

!

to this.


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Eurotech ReliaSENS 18-12

Air Out Air In

Connectivity•

Cellular (3g, GRPS), WiFi

• Ethernet, GPS Positioning

Environment Analysis

•

Electromagnetic radiation• Radioactivity

•

Temperature, Humidity, Pressure

Air Quality Measurements

•

CO, CO2, NO, NO2, O3

•

SO2, H2S, VOC•

PM10


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Eurotech ReliaSENS 18-12

• One data point every minute

• Aggregated averages every hour, 8 hours, and daily

• Configurable thresholds and remote re-calibration


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Java in the Air: Architecture

CLOUD(device management and cloud analytics)

Everyware Cloud

MQTT

DEVICE/GATEWAY(data collection

and edge analytics)

Linux

Hardware

Java SE Embedded

OSGi

ESF

Bundles

OEP-E

Bundles

DeviceConnectivity

EUROTECHDEVICE CLOUD

DeviceManagement

Data

Cache

AccountManagement

Oracle Cloud

ORACLECLOUD

Oracle 12c DB

Oracle 12c OEP

Oracle BI


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Linux

Hardware

Java SE Embedded

OSGi

ESF

Bundles

OEP-E

Bundles

Java in the Air: Gateway

3. MQTT Output Adapter

1. Sensor Input Adapters

2. EventProcessing

Network

4. ConfigurationUpdates


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Input AdaptersPM10, ELF, TPU, CO2, GEIGER, HF, NO2,

CO, O3, VOC Sensor Malfunctioning Detection

Raw Data Filtering

Stats

Alerts

Raw Data Publisher

Java in the Air: EPN


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Java in the Air: CQL Examples

27

Stats CQL Query Alerts CQL Query


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MQTT Topic Namespace

Java1

CO2

RAW

FILTERED

DROPPED

STATS

30sec 60sec

ALERTS

CHANGE MISSING

HF

RAW

FILTERED

DROPPED

STATS

30sec 60sec

ALERTS

CHANGE MISSING

VOC

RAW

FILTERED

DROPPED

STATS

30sec 60sec

ALERTS

CHANGE MISSING


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Demo


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Lesson Learned and Next Steps

•

EPN for modelling Embedded Business Logic

•

Great Synergies with Remote Management

•

More things to be explored:

–

Reduced OEP-E footprint

–

Out-of-the-box ESF/Kura OEP-E Components


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You are important!

•

Learn More - come visit us on the Exhibition Floor: –

Eurotech Booth

–

Oracle Booth

–

Eclipse Booth

•

Contribute!www.eclipse.org/kura


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www.eurotech.com

Thank You!

www.oracle.com

Documents

CON3993 Java in the Air - A Case Study for Java-Based Environment Monitoring Stations