As digitization increases, vast amounts of data will be collected, analyzed and stored. According to Forbes, the world produces more than 2.5 trillion bytes of data every day. The corresponding challenge is to create the platforms to support these volumes of data.
In the case of smart cities, platforms help manage the collection and processing of data from multiple sources to provide information on topics of interest such as weather conditions, events, parking, or transportation, both for analysis, and decision making.
The challenge in Latin America
It is the second most urbanized region on the planet. In fact, it could even reach an urbanization of up to 90% by 2050. According to the Inter-American Development Bank (IDB), the urbanization process in Latin America has accelerated and is occurring in a disorderly manner, which poses greater challenges in terms of mobility, urban planning and public services.
Despite the clutter, our cities have started to move towards smart initiatives, focused on public transportation, smart buildings, communications networks, Wi-Fi, and mobility. Some cities such as Santiago, Mexico City, Bogotá, Buenos Aires, Curitiba, Medellín and Montevideo already have projects of this nature.
Trust the infrastructure
For these initiatives to be successful, both citizens and governments need to trust the infrastructure behind them. There are 2 key factors in fostering this trust: reliability and latency.
In this regard, the 5G network and edge computing will be important contributors to achieving the low latency required to connect various dedicated networks of mobile devices, sensors, automobiles, home appliances, and data centers. A mix of physical facilities and the cloud will create the right ecosystem for smart infrastructure. The right edge infrastructure is one of the first steps in reaching the level of computing power and low latency that smart cities demand.
In order to make the right infrastructure decisions, Vertiv has developed a framework with specific edge infrastructure models to help organizations make practical decisions:
• Device edge. The computation is on the end device. It is embedded in the device, for example, an intelligent video camera with AI capabilities, or it is a “companion edge”, for example, a computer connected to an automated guided vehicle.
• Microedge. It is a small, stand-alone solution that ranges in size (from one or two servers to four racks). It is usually installed on a company’s own site.
• Data centers at the distributed edge. A small data center of less than 20 racks that is located at enterprise sites, telecommunications facilities, or regional sites.
• Data center at the regional edge. A data center facility located outside the network hubs of the Core data centers; it shares many of the characteristics of hyperscale data centers.
Smart cities have the potential to harness technology to benefit the way we work, travel, connect and do business. But we also need to choose the right edge infrastructure, as well as make important decisions about how best to use our smart infrastructure and where to invest. Stakeholders working on the creation of a smart city environment in Latin America, such as governments, telecommunications and companies, do well to ask themselves: what is the right edge infrastructure model for my needs and how can I create one? Is it an infrastructure that supports the required latency and reliability? The answer to this questionn will mark the way to the future.
