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Founded to create real-time IIoT edge intelligence platform
Million in funding from industrial leaders$47.5
Commercial IIoT engagements globally100+
Analyst report coverage in 2018, including 7 from Gartner20+
Awards for innovation, edge intelligence, ML, AI and more 25+
Partners across OEM, cloud, SI, gateway, and semiconductors 50+
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Real-time edge intelligence for industrial IoT
Introducing FogHorn
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Proprietary and Confidential 3
IIoT and AI Industry Recognition
1. Qualcomm2. Cisco3. Intel4. FogHorn Systems5. Amazon Web Services6. Microsoft7. Everythng8. Google9. Tesla10. IBM
10 Hot IoT Startups to Watch in 2018
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Proprietary and Confidential 4
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Proprietary and Confidential 5
World’s smallest and fastest
inference engine that powers
transformational solutions
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FogHorn Products
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EdgeAI Platform
Out of Box Solutions
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STREAMING ANALYTICS AT THE EDGE
A PRIMER
Proprietary and Confidential
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DRIVERS FOR EDGE COMPUTING
Limited Connectivity
Bandwidth Costs
Risk of Cyberattacks
Real time decision making
High fidelity analytics
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Traditional Batch AnalyticsCollect→ Store→ Transmit→ Process→ Transmit→ Act
FogHorn Streaming AnalyticsStream→ Process→ Act
Proprietary and Confidential 9
Batch vs. Streaming Analytics
11001010
cloud
data center
edge device
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Traditional Batch AnalyticsData at Rest
Streaming AnalyticsData in Motion
Proprietary and Confidential 10
Data at Rest vs. Data in Motion
11001010
cloud
data center
edge device
Characteristics
Historic, several minutes to hours Data Freshness→ Real-time, milliseconds
Disk based and transmitted Data Location→ In memory and local
Often downsampled Data Resolution→ High resolution and raw
Seconds to hours Processing Speed→ Milliseconds to seconds
Periodic Processing Frequency→ Continual
High Power, Large Storage Processing Power→ Lower power, only memory
Historical analysis Use Cases→ Time critical decisions
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IoT Data Requires Different AnalyticsHigh Volumes, Varieties and Velocities of Data
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Bandwidth costs of moving large volumes of data
Latency and real-timedecision making
Limited or noconnectivity
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Proprietary and Confidential 12
Stream Processing Your Data with FogHorn
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FogHorn’s Real-time Stream Processing Engine
Proprietary and Confidential 13
VEL® Complex Event Processing (CEP)
• Designed from the ground up in C++ for edge and small compute environments
• Performs real-time analysis of disparate asynchronous streams of sensor & control system data
• Executes complex pattern recognition and machine learning inferencing on high frequency and temporally continuous data
• Detects events, anomalies, and deviations from rules in real-time, enabling immediate control actions
• Highly advanced tooling for authoring, testing, debugging with live introspection and instrumentation of live system in production
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TransportationWearables
Connected Cars
Connected Homes
Connected Cities
Industrial Internet
Manufacturing
Utilities
Oil & Gas
Healthcare
Proprietary and Confidential 14
The Rise of the Internet of Things
…IoT devices will grow to as many as 30 billion devices by 2020.McKinsey & Company. Image: Goldman Sachs.
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Industries and Use Cases
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Manufacturing, Oil & Gas, Energy, Transportation, Smart Buildings
Proprietary and Confidential
EdgeML®
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Industrial IoT Data Volume Overwhelming
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1 PB Mining
480 TB Jet engine
24 TB Automated manufacturing
1 TBLarge refinery
0.8 TB Large retail shop
0.5 TB US Smart meters
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IOT Signals Report 2019
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Continuum of IoT Use Cases
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Edge Analytics
EdgeML®
Edge AI
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TRANSFORMER DEFECT DETECTION
Real-time edge testing improved yields and reduced scrap
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Transformer Defect Detection
Real-time edge testing at each stage of manufacture
for improved yields and reduced scrap
PRINT DEFECT DETECTION
Vision Model detectsvariations in printed characters and markings
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Transformer Defect DetectionPrint Defect Detection
FINISHED GOODS INSPECTION
Deep learning algorithms identify defects through vision models
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FACIAL RECOGNITION WITH DEEP LEARNINGDriver facial recognition as a vehicle access authentication mechanism
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Fusing of disparate sensor data streams
to derive insights
Pressure, vibration,
temperature, etc
Audio, video, 3D imaging
Geofencing for asset tracking, perimeter
monitoring
Sensor Fusion
Proprietary and Confidential
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VIDEO-BASED SECURITY SURVEILLANCE
Real time monitoring & identifying worker movements in restricted zones
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HAZARD DETECTION USING VISION MODELSDetect hazardous Conditions in real time to ensure worker safety
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FLARE MONITORINGSOLUTION
Running deep learning models on Jetson Nano
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