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Delivering the Value of Geospatial Analytics into Your Industry 4.0 Initiatives
Dr. A. IstamarCEOEsri Indonesia
W a t e r R e s o u r c e s
T r a n s p a r e n t G o v e r n m e n t
Making a Difference
Our Users
Data Fraud Failure of National Governance
Spread ofInfectious Diseases
Failure of Climate-Change Adaption
Natural Catastrophes
Critical Infrastructure Breakdown
Communicating Effectively
Unemployment
Access to Clean Water
Theft
State Conflict
Biodiversity Loss and Ecosystem Collapse
Cyber Attacks
Communities
Creating Many Challenges
The Pace of Change Is Accelerating
Drought
Mass Migration
Loss of Biodiversity
Ocean Acidification
Deforestation
Population
Climate Change
Pollution
Food
Water
Political Polarization
Urbanization
Energy
Evidence
Threatening Our Natural World
and Our Future as Humans
We Are Now at a Place Where No Humans Have Been . . .
We Need More Understanding
. . . Collaboration and
. . . Action
Social Conflict
Creating a SUSTAINABLE competitive advantage
Design with Nature
Create Sustainable Development
Make CitiesSmarter
IntegrateEnvironmental
Thinking
EngageCitizens
ImproveProductivity
and Efficiency
Leverage Our Best Technology, Geographic Science, and Holistic Design Thinking
ProtectBiodiversity
Keep Moving, Learning, and Understanding . . .
What Should We Do?Apply the Power of Digital Geography
Leveraging the Power of Geography . . .to Better Manage Our World
A Frameworkand Process
Action
Decision-Making
Analysis & Modeling
Planning & Design
Visualization & Mapping
Data Management & Integration
GeospatialInfrastructur
e
What Is Geospatial Infrastructure?
. . . and SolvingProblems Holistically
IntegrationLeveraging Location . . .
. . . and Technology
Foundational . . .. . . Directly Usable
and Services-Based
Content
Geographic Sciences . . .. . . and Visualization
Mapping & Analytics
A Platform for Sharing . . . . . . and Collaboration
. . . GIS at Scale
WebGIS
ArcGISThe Science of Where Is Advancing Rapidly
Integrating and Leveraging Many Innovations
Easier, Open,
and Accessible
Data
Computing GIS Innovation
. . . Enabling Geospatial Infrastructure
Creating Smart, Dynamic Organizations
Using the Power of Location to Integrate Everything
Interconnected Information, Processes, and Workflows . . .
. . . All Happening at the Same Time
Geo-enable the 4th Industrial Revolution
Real-Time Monitoring
Autonomous Vehicles
Smart DevicesIoT
Data-Driven Analytics
Predictive Analytics
Advanced Modeling
Automation
Cloud Computing
Efficiency and Collaboration
Geospatial Solutions
Internet
Location Intelligence
Open Data Access
and Transparency
Geospatial AI
Distributed Architecture
Machine Learning
Big Data
SaaS
ArcGIS itself is part of the Esri Geospatial Cloud
Geo-Enabled
Systems
Indoors
Insights
[ Spatial BI ]
Hub
Urban
Planning
Business
Analytics
GIS
Mapping &
Location
Esri
Field Operations
Spatial Analysis
& Data Science
Imagery
Real Time
3D
Available as SaaS or as Software
and includes distinct product offerings that work well together
Geospatial Capabilities & Geo-Enabled Systems
Developers
Data Management
Creating
a Common Language
Imagery
Lidar
3DVector
Tabular
Real-Time
(IoT)
Big Data
Maps,
Scenes,
Layers
Unstructured
ArcGISIntegrates All Types of Data
BIM
Advanced ModelingEfficiency and Collaboration
Real-Time Monitoring
ImmersiveExperiences
Automation
Artificial Intelligence
Geodesign
PervasiveMappingCloud Computing
Predictive Analytics
Data-Driven Analytics
Autonomous Vehicles
Remote Sensing
Geospatial Solutions
Smart Devices
IoT
Internet
PersistentSurveillance
Location Intelligence
Synthetic Biology
Open Data Accessand Transparency
PervasiveGeographic
Understanding
Digital Transformation Is Just Beginning . . .
Geoplanning
Geoaccounting
Web GIS
Web GIS Is Already Playing a Fundamental Role . . .. . . Integrating Geography Into Everything We Do
Robotics
We Are Living in an Era of Exponential Technological Advancement
New Challenge for National Government : Intelligence Challenges
…Multi-Jurisdiction, Multi-Agency Missions Supporting Complex Operations
Immigration Control Cyber Warfare
Domestic TerrorismBorder Security
Organized CrimeEnergy Security
Natural Disasters
Political Crisis
Adversaries
We Need Integrated Approaches . . .. . . Enabling Better Understanding
Sharing dynamic data across organizations for shared situational awareness
Integrating and analyzing data into actionable information
Deploying mission based applications to support decisions
Disseminating information to multiple devices when and where needed
The Underlying Challenges :
It’s applied everywhere..
Autonomous Cars
Predictive Maintenance
Chatbots
Cancer Detection
Crime Prediction
Personalized Marketing
FacialRecognition
Advanced Video Analytics
Stock Market Prediction
Advanced Satellite Intelligence
WarRobots
Sentiment Analysis
1. AI > ML > DL
Reasoning Knowledge Representation
Perception
RoboticsNLP Machine Learning
features Labels1. Training
2. Predicting
Supervised Learning
Unsupervised LearningReinforcement Learning
Deep Supervised Learning
Artificial Intelligence Machine Learning Deep Learning
Dog
Machine Learning
Deep Learning
Artificial Intelligence
CNTK TensorFlowTheano
Natural Language Processing
Video game behavioral AI
Robotics
Keras
IBM Watson
scikit-learn
Computer Vision
ArcGIS has Machine Learning Tools
ArcGIS
Classification
Clustering
Prediction
Combining the AI power of Microsoft with the geospatial analytics of Esri.
Pre-Configured environments in the cloud for GeoSpatialData Science & AI Modelling, Development & Deployment.
https://azure.microsoft.com/en-us/blog/microsoft-and-esri-launch-geospatial-ai-on-azure/
GeoAI Virtual Machine
ArcGIS Pro
GeoAI Patterns
PredictionObject Detection Pattern Detection
Buildings, Road Segments,
Swimming Pools, Blight,
Graffiti, Overgrowth, Road
Signs, Vehicles from CCTVs,
and more
Water Pipe Breaks, Diseases,
Crimes, Crashes, Incidents,
Fires, Congestion, 911 Calls,
Top Risky Segments, Emerging
Hotspots of 911 Calls, Disease
Clusters, and more
Machine Learning for Oil Well Optimization
Location-based analytics using clustering tool in ArcGIS Pro and scatter plot in Insights for ArcGIS
Build data pipeline
Collect and prepare data
Train ML and DL models to
derive insights
Operationalize models and
distribute insights at scale
Serving business users and end users with intelligent and dynamic
applications
And most aren’t satisfied with their current solutions
“What it Takes to be Data-Driven: Technologies and Best Practices for Becoming a Smarter Organization”, TDWI, 2017.
Are satisfied with ease of
use of analytics software46% 21%Are satisfied with access to semi-
structured and unstructured data 28%Are satisfied with ability to scale to
handle unexpected requirements
Complexity of solutions
Many options in the marketplace
Data silos
Incongruent data types
Difficult to scale effectively
Performance constraints
General purpose machine learning
Azure availability:D, F, L, M, H Series
CPUs
Optimized for flexibility Optimized for performance
GPUs FPGAs
Deep learning
N Series
Specialized hardware accelerated deep learning
Project Brainwave
And most aren’t satisfied with their current solutions
“What it Takes to be Data-Driven: Technologies and Best Practices for Becoming a Smarter Organization”, TDWI, 2017.
Are satisfied with ease of
use of analytics software46% 21%Are satisfied with access to semi-
structured and unstructured data 28%Are satisfied with ability to scale to
handle unexpected requirements
Pre-Configured environments in the cloud for Data Science and AI Development
And most aren’t satisfied with their current solutions
“What it Takes to be Data-Driven: Technologies and Best Practices for Becoming a Smarter Organization”, TDWI, 2017.
Are satisfied with ease of
use of analytics software46% 21%Are satisfied with access to semi-
structured and unstructured data 28%Are satisfied with ability to scale to
handle unexpected requirements
Identifying Broken Insulators via Deep Learning Partial Discharge Detection using Scikit Learn & ArcGIS Pro
Machine Learning for Electricity
Voice Recognition in Map
Detect Objects Using Deep Learning
Detected Objects
Model
Imagery
Detected Objects GP Tool
Advanced Object DetectionDetecting complex Objects from Satellite Imagery using a trained deep learning CNN TensorFlow Model. The model is called on-the-fly via a Raster Function from Pro. Detected Sites are then converted to vector points to apply further spatial analytics
4. ArcGIS Field Apps like Workforce + Collector and Survery123 could be used to plan inspections for detected sites. Operations Dashboard could be used to monitor execution of assigned tasks in Real-TimeInspections Results could then be analyzed in ArcGIS
1. ArcGIS “Export Training Data For Deep Learning” GP tool used to Prepare the a labelled training data set from feature class
2. CNTK or TensorFlow used to train a CNN to detect objects of interest using the labelled training data set
3. ArcGIS Imagery tools used for imagery management and analytics. A Raster Function is used to call the trained CNN and generate the results directly at Pro, allowing for further vector and raster analytics
Palm Detection with Deep Learning
Real-Time Detection of Cracks
GeoAI Sample Use-Cases (Videos)
ETA Prediction Accidents Probability Prediction Smart Road Digitization
High Resolution Land Cover Object Detection from VideosObject Detection from Imagery
How Do We Take the Next Step?
. . . Create a Geoscience-Based Foundation for Our Future
LearnContinuously
Understand the Possibilities
Envision a Better Future
Create Solutions
Inform & Educate
Participate & Take Action
Embrace Technology
Take the Initiative
Work Together
Innovate
Embrace Digital Transformation . . .
. . . and Leverage The Science of Where