SpaceX has its own ambitious plans for AI data centers in space, while Microsoft has explored the idea by sinking them underwater. However, building AI data centers is expensive and power-intensive. This is why a UK firm wants to build one using street lamp posts in Nigeria, and it has already signed a deal to do it.
Warwickshire-based Conflow Power Group has agreed with Nigeria’s Katsina State Government to deploy 50,000 solar-powered smart lamp posts called iLamps across the state (via BBC). Each unit runs on a cylindrical solar panel and battery, powering a low-energy Nvidia chip that draws just 15 watts.
Networked together, CPG says the units would deliver 13.75 petaOPS of combined computing power without pulling a single watt from the grid. For comparison, a traditional data center typically needs 300 megawatts of grid power, millions of liters of cooling water, and years to build.
What else can these lamp posts actually do?
Each iLamp can support cameras for traffic enforcement, spotting speeding vehicles, parking violations, and seatbelt non-compliance. Facial recognition for identifying wanted or missing persons is also on the roadmap, though no such deployment exists yet.
The units can also offer public WiFi and Bluetooth connectivity. Katsina will earn revenue from traffic fines captured by the cameras, with CPG taking a 20% share after three years. Income from renting out computing power to AI companies is funneled into a green bond that funds installation and maintenance.
Can lamp posts really replace data centers?
Experts say the iLamps won’t replace conventional data centers for heavy AI workloads since the distance between posts makes communication too slow for demanding tasks. But they could serve as useful access points for lighter AI tasks, functioning similarly to mobile phone masts.
If all ongoing negotiations across seven Nigerian states, universities, and institutions are finalized, the total network could exceed 300,000 iLamp units, forming the largest distributed AI compute network on the continent.
All of this comes as AI infrastructure continues to strain global resources, with experts warning it could significantly worsen the e-waste crisis already choking the planet.