Intelligence At The Edge For Industrial IoT
Intelligence at the Edge for Industrial IoT1
FogHorn BackgroundEdge Intelligence Software for Industrial IoTSilicon ValleyStart-UpEst. 2014Purpose-BuiltEdgePlatformKey ries A in Q2 2016Series B in Q4 2017Proprietary and Confidential2
IIoT and AI Industry Recognition#1 Hot IoT Startupto Watch in 2017The 10 Coolest TechStartups of 20161.2.3.4.5.6.7.8.9.10.Proprietary and ConfidentialQualcommCiscoIntelFogHorn SystemsAmazon Web ServicesMicrosoftEverythngGoogleTeslaIBM3
Ascendancy of Edge ComputingProprietary and Confidential4
The Rise of the Internet of ThingsIndustrial InternetConnected CitiesManufacturingConnected HomesConnected Cars IoT devices will grow to as manyas 30 billion devices by 2020.TransportationWearablesUtilitiesMcKinsey & Company. Image: GoldmanSachs.Oil & GasHealthcareProprietary and Confidential5
Industrial IoT Data Volume OverwhelmingEdge intelligence will drive real value in Industrial IoTLess than 1 percent of the data being generated by the 30,000sensors on an offshore oil rig is currently used to make decisions.McKinseyEdge solutions are critical for IoTCloud models are not designed for thevolume of data IoT generates.Cisco“Things” generatemore data every day11 PB480 TB24 TB1 TB0.8 TB0.5 TBMiningJet engineAutomated manufacturingLarge refineryLarge retail shopUS Smart metersProprietary and Confidential6
Edge AdvantageMaximize insight by analyzing real-time asset data Streaming ML Clean diverse/noisy OT data for maximum insight Determine sensor health in real-timeApply your best intelligence to the Edge Update models on-the-fly Deploy with confidenceOptimal Edge performance Sub millisecond decisioning enables new applications Compact, commodity hardware/software foundation, No FPGAEdge computing shifts processing from central servers or a cloud to the asset. Thisenables richer data, faster reactions, and lower bandwidth requirements.Proprietary and Confidential
FogHorn Edge Intelligence for Industrial IoTEdge Management/Monitoring/ConfigurationEdge Node(PLC/DCS, Gateway)Key Customer Benefits Lowers bandwidth/hosting costsTriggers real-time insightsEnables proactive use casesMaximizes security and privacyFogHornEdge IntelligenceApplications/SDKFogHorn ManagerClosed Loop Analytics/MLEdgeCloudTransport/PublicationFogHorn Differentiators Tiny footprint OT-centric Cloud agnosticMachine LearningCEPAnalyticsLocal HistorianMain Use Cases EnrichmentData IngestionMonitorCondition MonitoringPredictive MaintenanceAsset Performance ManagementIndustrial Process OptimizationManageProprietary and Confidential8
Edge Processing Advantages for Analytics/MLEdge (GB’s)Control logic,streaming analyticsand ML inferencesachieve far higherfidelity on live dataInsignificant events(sensor fluctuations)appear significantCloud (MB’s)Significantevents missedProprietary and ConfidentialEdge processing delivers: Higher quality, cleaner dataReduction in false positivesMaximum insightFaster responseBetter inferencesFault tolerance9
Closed Loop Machine LearningBusiness InsightsEdge MLTMOperational InsightsFiltered, Normalized, Enriched DataVELTMCEP AnalyticsDeep Learning ModelsMESML ModelsEnterprise Reference DataData EnrichmentProprietary and Confidential10
FogHorn IIoT Partner EcosystemIndustrial Solution ProvidersCloud Infrastructure and AI/ML CompaniesIIoT Consultants and SIsIIoT Semiconductor DevelopersIIoT Gateway SuppliersProprietary and Confidential11
Industrial IoT Use CasesManufacturing APM andProcess IntelligenceDrilling EquipmentPredictive MaintenancePipeline Leak andCorrosion DetectionRenewable EnergyOutput ForecastingWind Turbine Optimizationanf Predictive MsintenanceMining Equipment TrackingAnd Asset OptimizationCompressor/ValvePredictive AnalyticsLocomotive Fuel Consumptionand Remote MonitoringProprietary and ConfidentialPump Condition Monitoringand Predictive MaintenanceTurbine PerformanceMonitoring and OptimizationSmart Cities andSmart BuildingsIntelligent Real-TimeHealth Monitoring12
MANUFACTURINGImproving Capacitor Production YieldANALYTICS/ML ON WINDING MACHINE DATA DETECTS EARLY DEFECTS Hard-to-detect failure conditions reducing yield and increasing scrapCHALLENGE No real-time monitoring of large amounts of sensor data No OT-centric analytics for manufacturing team members FogHorn VEL : Real-time analytics on winding machine sensor dataFOGHORNSOLUTION EdgeML : ML on normalized data streams for real time failure alerts Iterative refinement of VEL analytics and ML models to assist operatorsBENEFITSImprove yield,reduce scrapProprietary and ConfidentialDeliver real-timeanalytics to OT staffSmart, not scheduled,maintenance13
OIL & GASAutomated Flare Stack MonitoringREAL TIME VIDEO ANALYTICS AND ROOT CAUSE CORRELATION ANALYSIS Monitor large number of flare stacksCHALLENGE Limited communications / compute resources Ensure compliance with environmental/regulatory requirements Reduce large spend on maintenance and compliance FogHorn installed into existing gateways ( 1Gb)FOGHORNSOLUTION Real time audio / video analysis of flare feeds Convolutional neural networks (CNN) for deep learning Sensor fusion correlate flare state with compressor audioBENEFITSLower Opex andmaintenance costsProprietary and ConfidentialBroad compliancemonitoringImproved safety14
TRANSPORTATIONLocomotive Operational EfficiencyON-BOARD ANALYTICS DRIVE CENTRALIZED OPERATIONAL OPTIMIZATION Optimize fuel usageCHALLENGE Detect sub-optimal operating conditions Reduce mobile networking costs of monitoring FogHorn installed into on-board hardened data collection systemsFOGHORNSOLUTION RT analytics on idling & throttle data based on location, speed & time Proactive alerts sent to command centers for operational optimization Video only sent on abnormal conditions reducing cellular costsBENEFITSReduction in fuel andcellular costsProprietary and ConfidentialOptimize crew andtrain performanceEnsure safe operatingconditions15
SMART BUILDINGSOptimizing Elevator Performance50 ML MODELS ON TINY CONTROLLERS DELIVER PREDICTIVE MAINTENANCE Monitor 1.5M elevators / escalators deployed globallyCHALLENGE Limited communications / compute resources Mine sensor information for actionable insights Reduce inspection / repair fees of 2K/eventFOGHORNSOLUTION FogHorn installed on existing motion sensor kits, 1 Gb footprint CEP time-aligns state and activity data in 20 lines of code 40 ML models generate predictive maintenance alertsBENEFITSSmart, not scheduled,maintenanceProprietary and ConfidentialReduce costly repairand servicingNew managedservice revenue16
WIND ENERGYWind Farm Output ForecastingREAL TIME TURBINE CONTROLS-DRIVEN MACHINE LEARNING FORECASTS Monitor large volumes of windmillsCHALLENGE Limited communications / compute resources Accurately predict, report and meet 24 hour power generation goals FogHorn installed into existing gatewaysFOGHORNSOLUTION Models trained on 20 attributes to predict power generation Real-time scoring on power generation with alerts for problems Enables technician tuning of settings or revised forecastBENEFITSAlerts with 90minutes lead timeProprietary and ConfidentialConstantly updatedpower forecastsEnsure governmentcompliance17
Intelligence at the Edge for Industrial IoT18
Predictive Maintenance Pipeline Leak and Corrosion Detection Compressor/Valve Predictive Analytics Pump Conditio n Monitoring and Predictive Maintenance Renewable Energy Output Forecasting Wind TurbineOptimization anf Predictive Msintenance Mining Equipment Tracking And Asset Optimization Lo
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