Can Smart Cities Solve Overpopulation?
By 2050, there will be 9 billion people living on the planet – 68% of them in cities. Population growth of this scale could create countless problems, such as overcrowding, excess air pollution, limited natural resources and further loss of natural habits.
Cities are already being forced to find solutions to become more efficient in order to cope with overpopulation such as smart city technology. Smart cities use Internet of Things (IoT) devices to collect and analyse data which is then used to make better decisions and deliver a better quality of life. However, simulating vast quantities of data is currently extremely complex and digital twins are currently being held back by slow, expensive and computationally intensive infrastructure requirements.
How Can Smart Cities Reduce Overcrowding?
Although many of us worldwide have been forced to work remotely due to the COVID-19 pandemic, we will one day return to a state where millions of people in cities across the world will pile onto overcrowded public transport for their daily commute. As city populations increase, it will become increasingly difficult for public transport to keep up with the strain. Traffic on the roads will also increase – whilst sustainable options such as electric scooters and bikes are helping alleviate road traffic in some places, by 2050, there will be an extra 2 billion vehicles on the road worldwide.
IoT sensors and cameras can aid city planners in knowing which times of the day are busiest. This data can then be input into simulations or digital twins to predict the flow of traffic and test out adjustments in transport routes. The same method can be used to monitor where foot traffic is heaviest so that decisions can be made where to widen pavements and which areas to pedestrianise.
Intelligent traffic signals, digital signage and mobile apps displaying real-time information about delays can also be effective in improving the flow of people throughout a city, as well as IoT sensors on physical infrastructure so that problems can be identified and fixed long before roads have to be closed.
What’s Holding Smart Cities Back?
The recent explosion of IoT sensors is a core component of what makes digital twins possible. However, as the number of complex devices producing data increases, more and more compute resources are needed making the back-end requirements astronomical. Practically therefore, it is impossible to create the requisite depth and complexity – combining millions of agents, IoT devices and AI entities – while incorporating real-world data. If there is no easy means of simulating all the available data, accurate and meaningful data-driven decisions cannot be made and the whole concept of a digital twin falls flat.
These simulations need intuitive, load balancing technology that can easily spin up new servers on demand but this is a complicated computing and mathematical challenge. At Hadean, have begun to solve this issue using an octree data structure which dynamically allocates resources to complex and intensive CPU regions; as more entities condense into a single spot, the octree data structure repartitions space to balance load across CPUs. More complex regions are decomposed into a greater number of cells, while less complex regions are handled by fewer cells.
Ultimately, if we are unable to significantly optimise the computational complexity of digital twins, it will be extremely difficult to make timely decisions to accommodate overpopulation and overcome this critical issue.