Critical national infrastructure is facing a generational challenge. The scale of this transition is unprecedented; to meet global Net Zero targets, operators will need to build or refurbish a total of over 80 million kilometres of electricity grid by 2040 – the equivalent of the entire existing global grid.
Many operators are turning to digitalization to meet the challenge of this green energy transition. Using tools such as simulation, automation, digital twins and AI analysis, grid operators can transform their grids at a scale, pace, and standard that was previously impossible.
However, digitalisation needs data. Survey and inspection work is vital to capture the high-quality asset condition data operators need to leverage these new technologies, and access the benefits.
sees.ai are building a system that enables operators to monitor their assets in real-time, gathering high quality instantly accessible data. Our system makes inspection and monitoring safer, more efficient, and more effective than ever before.
High quality, perfectly repeatable data
sees.ai’s drones capture detailed 2D images georeferenced against a 3D digital twin, giving a real-time view of the condition of assets, on a global and granular level. This improves the quality of regular inspections with an unprecedented depth of data. In turn, the data we capture is perfectly repeatable – ideal for machine learning and AI analysis at scale – so operators can access the best possible insights.
Safety that improves with scale
Every second of every flight is centrally recorded, providing regulators and operators with a comprehensive dataset that proves safety. This centralised mechanism makes our system uniquely able to expand and adapt safely, at pace.
Meanwhile, around 15-20% of the typical network is inaccessible by helicopter. With a drone, operators can view assets from angles and locations legacy methods can’t reach – without risky climbing inspections or shutdowns.
Efficient maintenance using fewer resources
sees.ai’s system centralises human involvement to a small group of supervisors, operating from a control room. This reduces the number of skilled pilots required, whilst providing more extensive oversight.
Plus, operators can leverage AI analysis to process our perfectly repeatable data, reducing backlogs and person-hours. This all adds up to an estimated 35% cost reduction versus current drone operations.
