Modern cities are continually adapting to the needs of an increasing urban population. Issues that are becoming ever more pressing include concerns about traffic congestion, energy consumption and the control of public services. Local authorities are having to cope with inefficiencies, environmental concerns and reduced quality of life.
Fortunately, models exist today to help put in place solutions to these problems. AI (artificial intelligence), ML (machine learning), and (IoT) Internet of things are all combining to take the pressure off public servants charged with solving issues such as urban mobility and sustainability, the end point being cities which are smarter, greener and more resilient.
Urban mobility is the ability of people and goods to move around efficiently. This will become even more critical since it is thought that by 2030, 5 billion of us will be living in urban areas across the globe.
Collecting data and processing it has become easier since the advent of cloud computing, while AI and ML look at the outcome of some of the designs proposed, allowing for analysis of how real time situations will cause us to behave before any modifications are made concrete.
Minimising congestion can be achieved using evidence taken from traffic sensors, cameras and GPS, combined with assessments made clear from computer modelling. It is thought that with AI assistance time taken travelling through urban environments like London can be reduced by 20%.
Efficient consumption of energy is also being facilitated through artificial intelligence. Specifically, this can monitor vehicle performance, predict energy consumption and make accurate decisions on where and when electric buses and trains require charging up. AI is helping with safety and operational organization in public transport as well, using information from cameras and sensors. Hence, issues with the efficient provision and scheduling of public transport become solvable.
Even effective waste management can be brought about using technology. It sends back data, via sensors on bins, about when they are relatively full, meaning that hopefully, in the future, scheduling, lower fuel consumption and a cleaner environment will all be within our grasp.
When efficiencies are looking to be achieved, municipal service providers are one of the first to look to AI. It may furnish us with optimal resource allocation, lower costs and an improvement in the overall service.
The environment will benefit too, with less fuel being used and therefore reduced emissions, the population profiting from better air quality and less respiratory illnesses.
AI can make a city less arduous to navigate for those with mobility scooters or wheelchairs while adaptive transportation services will certainly help the elderly and those with mobility issues.
Collaboration between governments, academic institutions and the private sector will achieve, with the help of AI, such things as autonomous public transport and multi-modal travel systems in the near future. Responsiveness will improve with the crunching of real-time data, to take the pressure off already taxed systems.
The picture does look, and needs to be, a good one with the future of urban mobility and sustainability only being helped using computer technology. Lowering our carbon footprint, optimizing operational efficiency and improving quality of life are all within our reach.
