IoT Experience- What cities will look like tomorrow greatly depends on what today’s urban leaders, planners, businesses—and of course, residents—are looking for today.
Understanding tech for tomorrow’s city begins with grasping today’s outstanding challenges. A Juniper Research report written in conjunction with Intel contends that creating a more intelligent city begins with self-awareness in areas from air pollution and traffic congestion to overcrowding and pockets of inequality. “Smart cities are those that recognize these challenges and adopt their planning and strategy to address them,” the report states.
Here are three areas where rapid advancements in IoT technology are already beginning to shape the cities of tomorrow, and how residents benefit from (and participate in) those substantial improvements.
1. Computer vision: With computer vision, cameras and other visual sensors capture raw video as data and process it into useful, actionable information. In smart cities, improved computer vision will give rise to enhanced quality of services, improved public safety, reduced congestion, and new levels of efficiency. One example of computer vision in action involves smart streetlights. Outfitted with this technology, they can reduce brightness when they detect no people or vehicles present (saving energy); monitor nearby parking to enable drivers to quickly find the nearest vacant space; or monitor pedestrian and vehicle traffic flows to optimize traffic and crosswalk signals. In terms of public safety, computer vision-enabled streetlights can send alerts on dangerous potholes or blocked storm drains.
2. Edge computing. An easy way to understand edge computing is to think of the phrase “where the action is.” Rather than relay information back to a central hub, cloud or data center mainframe, edge computing processes and analyzes data right at the source of where it’s collected.
So instead of a device or sensor sending its data over the internet, it can process this data itself—essentially becoming its own mini data center. And edge computing is strongly on the rise for one big reason: An IoT data deluge results when adding more devices to a smart cities network.
Smart buildings represent a prominent example of edge computing in action. As people occupy or crowd one part of a building, for example, sensors pick up this activity and via edge computing, can adjust lighting and climate control to optimize your comfort and visibility—while using far less energy on unoccupied floors. The result: smarter green buildings that react to our daily usage.
Edge computing (along with the emergence of powerful 5G data networks), will also play a major role in enabling driverless cars. Vehicles such as Google’s Waymo produce 1 GB of data per second. And sending that kind of data somewhere else for processing poses all sorts of problems, the biggest of which is latency—that is, a delay between when the data is generated in real time, and when it is processed. And when it comes to a car driving itself, even a few seconds of latency is, if you will, a non-starter.