Image Courtesy: Conflow Power Group
A UK based company is proposing a new approach to computing infrastructure by turning streetlights into small, networked data centres. Conflow Power Group Limited has signed an agreement with a Nigerian state to deploy up to 50,000 solar powered units that combine lighting with low power AI processing.
The system, known as iLamp, integrates solar panels, batteries, and compact computing hardware into standard lampposts. When connected, these units are designed to function as a distributed computing network, offering localized processing power without relying on traditional data centres, as reported by BBC.
Each iLamp uses a small, energy efficient chip capable of running AI tasks while drawing minimal power, around 15 watts. The solar panels charge onboard batteries, allowing the system to operate independently from the electrical grid. The concept is to scale performance by linking thousands of these units together, effectively creating a decentralized data processing system.
The company says this approach could reduce energy strain associated with large data centres while enabling real time processing closer to users. Potential applications include traffic monitoring, number plate recognition, and public safety systems. Some deployments may also include facial recognition features, depending on local regulations and partnerships.
However, experts caution that such systems are not a replacement for conventional data centres. High performance computing tasks, such as training large AI models, still require centralized facilities with significant processing capacity and high speed connectivity. Distributed lamppost systems are more suited to lighter, localized workloads.
Security is another concern. Since the hardware is physically accessible, there are risks of theft or tampering. The company says protective measures are built into the design, including mechanisms that disable the chip if removed.
The project also raises questions around privacy and surveillance. With integrated cameras and AI capabilities, the technology could enable advanced monitoring of public spaces. While the company states deployments will comply with local laws, the use of facial recognition and behavioral tracking remains a point of debate.
From an economic perspective, the system introduces a new model where cities can lease computing power generated by their infrastructure. In the Nigerian deployment, local authorities are expected to generate revenue by offering processing capacity to AI companies, creating a potential income stream alongside improved urban services.
The initiative reflects a broader shift toward distributed computing, where processing is moved closer to where data is generated. While still in early stages, the success of such systems will depend on their ability to balance efficiency, security, and real world performance.