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With the shift from combustion engines to electric vehicles (EVs), global EV sales have increased, along with the expansion of the infrastructure required to support them. Nigeria is experiencing a growing interest in EVs, driven by government efforts to promote clean energy and private-sector initiatives. While EV adoption is still in its early stages, efforts to create a sustainable EV ecosystem are gaining momentum, with projections indicating significant market growth over the next decade.
In terms of infrastructure, the number of available charging stations in Nigeria has been gradually increasing. In recent years, only a handful of charging points existed in urban areas such as Lagos, Abuja, and Port Harcourt. However, government-backed initiatives, such as solar-powered charging stations, are expected to accelerate growth. Despite this progress, the ratio between available charging stations and electric vehicles remains wide, highlighting the need for rapid infrastructure expansion to support EV adoption.
As charging stations become more widespread, new challenges emerge, particularly regarding the protection of the stations and their users. This is where smart video and video analytics come into play. These systems must be supported by an appropriate data storage infrastructure that offers the capacity, performance, security, and resilience necessary for current and future EV stations.
Primed for Success: Smart Video and EV Charging Stations
A crucial but often overlooked component in the successful expansion of charging station infrastructure is a reliable monitoring system to safeguard the facilities. With the increasing number of charging points in both urban and remote areas, operators must have a constant overview of activity at the sites.
To enhance safety and success, EV station owners in Nigeria are turning to AI-enabled security cameras with innovative features designed to transform the way operators protect their property. These smart video devices can distinguish between natural elements, vehicles, animals, and people, and can send alerts in the event of unforeseen events or unusual behavior. With ever-improving resolution, from 4K to 8K and beyond, along with advancements like motion sensors, new cameras enable object tracking, significantly reducing false alarms.
Over recent years, EV stations globally, including in Nigeria, have faced risks such as cable and battery theft, vandalism, and other forms of damage. These incidents not only result in financial losses but also affect the reliability and availability of the stations. Video analysis can help prevent vandalism before it occurs or catch perpetrators in the act. AI-enabled cameras can zoom in, automatically analyze the target, and capture a photo or video of the incident.
Additionally, intelligent video can use algorithms to detect other threats, such as fire or animals. For example, if a wildfire or electrical fault breaks out near a charging station, fire detection can trigger effective measures to prevent the spread of danger and minimize damage. It also enables the detection of approaching animals, such as stray livestock, that could potentially damage the station.
These AI-enabled smart video systems not only place new demands on the equipment but also on the data storage infrastructure that supports video analytics. Capacity, latency, and bandwidth become crucial when recording, streaming, and analyzing high-resolution footage to enable quick action.
Data Storage is Fueling EV Charging Station Security
Storage is a critical element in unlocking the full potential of smart video data. When designing infrastructure, EV station owners in Nigeria need high-capacity storage at the edge of the camera, in the server or recorder, and in the cloud or data center, offering low latency, high performance, and scalability. An important consideration in smart video is video and data retention time, which may vary based on regulatory compliance, redundancy and backup practices, or the longevity of the storage solution. Storage solutions should allow long-term data retention without compromising performance while complying with data protection regulations.
For example, a 360° smart video camera recording in full HD at 25 frames per second (fps) for 24 hours generates approximately 2.5TB of data over a typical 90-day retention period. To manage these daily streams at an EV charging station, the backend must have at least 225TB of storage.
To meet these demands, EV station operators in Nigeria need customized storage solutions that support AI workloads and associated storage requirements. As video analytics and deep learning for intelligent video solutions are performed both on-premise and in the cloud, it is essential to provide a scalable, cost-effective, durable, and high-performance storage infrastructure. EV station operators can use highly resilient, durable on-camera storage—up to 256GB in the form of microSD cards at the edge of the network, supporting card health monitoring, preemptive storage management, and reliability for continuous 24/7 high-definition video recording. Specially designed microSD™ cards, such as those from WD Purple™, can continue recording even if the connection to the network video recorder (NVR) is interrupted.
For reliable core storage, decision-makers should consider purpose-built hard disk drives (HDDs) with up to 22TB of storage and advanced features that enable up to 32 AI streams for deep learning analysis while reducing image failures. These HDDs, designed for intelligent video environments, are also optimized to handle up to 64 additional single-stream HD cameras, allowing for scalability as requirements evolve.
As EV adoption grows in Nigeria, charging station owners should prepare for success by investing in the right smart video infrastructure. This will enable operators to monitor, secure, and enhance the functionality of their stations while detecting and responding to events in real time. Video data and data storage will continue to play a crucial role in ensuring safety, security, and incident prevention in this expanding industry.
