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Scaling an Enterprise Drone ProgramBest practices in drone program design and management to overcome common obstacles to scaling a drone program

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About Us

Measure is an aerial intelligence company that enables enterprises to realize the transformative benefits of drone technology.

AES is a Fortune 500 global energy companythat has built a successful drone program across 100 AES businesses in 15 countries.

Program Results

Turnkey Aerial Inspections

Drone Advisory Services

Advanced Pilot Training

Drone Data Analysis

Drone Program Toolkits

Drone Program Software

$10MTotal Financial Value

57,000Hazardous Manhours Avoided

170Pilots Trained

AES deploys drones across their operations in solar, wind, thermal gen, and transmission & distribution

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The Road to Scalab i l i ty

Curiosity

Centralization

Experimentation

Development

Scale

Increasing riskIncreasing costs

Increasing complexityIncreasing employees

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What ’s in a Drone Program

Goals

• Safety is #1• Employee Development• Cost Savings• Production Improvements

Team

• Executive Sponsorship• Centralized Management• Cross-functional ownership• Third-party partners

Technology

• Application Development• Hardware• Software• Integrations• Advanced Technology

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Module Blade Boiler Poles Site Assessment

Inverter Tower Stack Towers Progress Tracking

Shading T&D Cooling Tower Lines Volumetrics

Vegetation Expansion Joints Vegetation Terrain

Fencing Volumetrics Substations Drainage

Roof Survey

Maximize Appl icat ions

Solar Wind Transmission & Distribution

Coal & Gas Construction

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Data , Not P ic tures

While a picture may be helpful for one-off use, true value comes from thinking of drones as a data collection platform.Your processed and analyzed drone data should allow you to:• Sort• Report• Take Action• Store• Track• Compare

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Defect IdentificationVisual and thermal data processed and analyzed to identify and classify all types of damage – solar panels, turbine blades, utility hardware, boilers, facades, etc.

Site Assessments & MappingPre-construction topography, surface models, site shading assessments, pipeline mapping, and volumetrics.

Condition Documentation & TrackingVegetation conditions, fencing review, construction progress tracking, overlays, etc.

Types of Data Products

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Develop Your Team

Program Management• Establish a centralized function to oversee

implementation, ensure compliance, track results, and share best practices

Cross-Functional Ownership• Assign business, plant, regional, and/or

functional representatives to your program team.

Pilot Training• Consistent, hand-on training

• Real-world applications

• Actual program equipment & software

Example Training Plan

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In-sourcing vs. Outsourcing

Many large programs will use a mix of in-house and out-sourced resources.

Examples:

• In-source simple, day-to-day operations

• In-source quick response tasks (e.g. post-disaster assessments)

• Out-source data analysis and delivery

• Out-source scheduled, large-scale operations

• Out-source operations at un-staffed or remote sites

• Out-source advanced operations requiring special waivers or equipment (e.g. LiDAR)

What to consider when choosing to in-source or out-source drone projects:

• Frequency

• Predictability / Response Time

• Complexity / Pilot Skills Required

• Project Size / Manhours Required

• Location / Proximity

• Data Analysis Capabilities

• Equipment Requirements

• Software Requirements

• Risk Conditions

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Streaml in ing Your Operat ions

Order Airspace Access

Asset Management

Flight Planning Data Capture

Data Processing, Analysis &

Visualization

Data Integration & Management

ERPsystems

EAMsystems

GIStools

USScompanies

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Software Enabl ing Operat ions at Scale

Enterprises can’t scale autonomous drone technology if they don’t have effective deployment, control, oversight, and analysis.

A software solution should centralize:• Pilot and equipment information• Scheduling and tracking• Flight plans• All flight data• Compliance & activity reporting• Raw collected data• Analyzed data, data products, and

reports

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Making a Mission

1. Request an inspection

2. Assign pilots and aircraft

3. Check airspace

4. Create a flight plan incl. automated flight path

5. Collect data

6. Automatically upload flight data

7. Automatically track compliance and flag incidences

8. Upload raw inspection data

9. Process, analyze, and report inspection data

10.Drive informed operational decisions

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Flight Planning Best Practices

Data RequirementsEvery project begins with a discussion of data requirements – what type of data is needed and how will it be used.

Scheduling & AssignmentsUse a master schedule to manage and plan all missions. Assign appropriate equipment & pilots and automate task assignments.

Building a Flight PlanCheck airspace and build a plan that prioritizes data quality – path overlap and altitude settings, as well as weather and irradiance requirements.

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Data Collection Best Practices

Safety FirstConduct pre-flight risk assessments and safety meetings, complete checklists, and always double check weather and airspace conditions.

Automated FlightMaximize data quality with automated grid and waypoint patterns or use active track modes such as spotlight, POI, trace, orbit and profile.

Automatic Flight LoggingFlight logging should happen automatically –uploading detailed flight logs and screen captures.

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Automated & Manual AnalysisMaximize automation to process thousands of images into organized, useable data and identify common defects. Use manual analysis for more complicated analysis or measurements, or for low volume data.

Manual Quality ControlExperts review all data results and complete the final analysis and visualization of the data.

User-Friendly Data DeliveryInteractive online portals and user-friendly pdf reports make sure that drone data can provide real value to operations.

Best Practices for Data Processing, Analysis & Delivery

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Data Management Best Practices

Data CollectionTrain pilots on best practices; block DJI data sharing with local data mode and/or operate in ‘airplane mode.’

Data HandlingUse controlled data transfer practices, wipe SD cards after data is uploaded, and (for critical infrastructure) don’t send data through non-FedRamp approved systems.

Data StorageUse secure, US-based cloud data servers or local storage solutions.

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Map Assets

Inspect with Drone

Upload Data

Review Defects

Manage SAP

Events

Review & Act in SAP

Asset Management Integration

Integrating drones into your existing workflows and systems will be key to maximizing value in the long term.

Measure is working to integrate aerial intelligence into the Asset Management platform for AES. Inspections can be requested, planned, performed, analyzed, reviewed, and acted upon.

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The technology exists today for companies to general real ROI with drone technology, include significant gains in safety, efficiency, and operational costs. However, continuous innovation will open even more opportunities to benefit from drones

Continuous Innovation

Advanced Drone Technology

State-of-the-Art Data Engineering

Autonomous Operations

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Advancing Autonomous Flight

• Technologies such as automated flight control and LiDAR can guide autonomous drone flights, which will help reduce the need for on-site skilled operators.

• On-going R&D of air traffic control systems, advanced communications and sensor equipment, and long-distance drones will help allow the opening of airspace for BVLOS operations.

• Data collection and analysis solutions are being advanced to accommodate with vast increase of data from BVLOS (beyond visual line of sight) operations.

Measure has partnered with AES subsidiary, DP&L, and AiRXOS, a division of GE Aviation, to develop BVLOS services.

• R&D work on a solution for transmission line inspections has begun with DP&L in Ohio.

Example

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Developing A.I .

Artificial Intelligence will further increase efficiency and reduce costs for drone programs.

AI technology will:

• Fully automate defect identification and classification on energy infrastructure.

• Provide predictive analytics, informing better maintenance & repair decisions.

• Execute fully autonomous data collection missions with drones.

AES and Measure worked with Google to build and refine algorithms that automatically identify and classify turbine blade defects, reducing the amount of images requiring human review and speeding-up the delivery of quality inspection results.

Example

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VIDEO >

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Questions?

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