Reduce outages by shaping autonomous drone programs deployed across power lines, solar farms and critical infrastructure
Challenge
Regular inspections of infrastructure is crucial to reduce the losses incurred from outages or malfunctioning equipment. Current inspection methods with helicopters and UAVs have drawbacks: Sheer scale of inspecting thousands of miles of transmission lines. Utility line workers are in the top 10 most dangerous jobs in the United States. The workflow resulting from vast amounts of data produced from a UAV is inefficient and labor intensive.
Solution
UAV’s are the first step in raising operational efficiency to a new level. Leverage A.I. to automate the process of visually inspecting for vegetation overgrowth, corrosion, rust, burnt items across switches, steel structures, non-steel structures, conductors, insulators and other hardware. Live stream high definition video with ultra low latency into a single cloud solution changing workflows to be more productive when out in the field.
Case Study
Solarai delivers fully autonomous drone thermographic analysis for enterprises conducting solar panel inspections. Solarai is a complete analytics solution that delivers continuous, automated end-to-end visual inspection and analysis of photovoltaics. Conventional solar plants inspection methods are limited: +    PV inspections are manual, slow, and complex to perform. +    PV defects are not being detected accurately. +    Reporting is slow, complex, and time-consuming. Solarai is powered by Skysense and Unleash live.
Transmission lines
  • Reduce the resources required for manual inspections with the use of A.I. to detect damage and reduce maintenance costs
  • Reduce cost, operational overhead and speed to action by eliminating the need for helicopters
  • Overhaul record keeping to visual records for faster access, deeper insights due to extensive analysis capabilities of this new data set and lower cost for auditing purposes
Solar
  • Use point cloud models to determine land elevation and erosion points for solar module installation
  • Scheduled and fully autonomous drone flights Automated and accurate aerial data collection
  • Intelligent fault detection with A.I.
  • Automated reporting system to drive immediate insights
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Sample A.I. Algorithms
Power line
A live inventory of power line components, damage identification, component assessment and recorded inspection history
Solar A.I.
Inspect Solar panels to identify module faults
Perimeter Detection
Reduce the time required to visually analyze perimeters, identify unusual activity or breaches, notify the responsible personnel for fast action