With the rapid rise of smart city projects — a recent report by the International Data Corporation (IDC) predicts investment in smart city initiatives will reach €69.2bn in 2018 — the difficulties inherent in digitalising critical infrastructure, such as transport, has taken on greater prominence.
Smart city initiatives have been driven by a multitude of factors, with the evolution of digital technology and mass urbanisation playing starring roles. With more than six billion people expected to live in urbanised areas by the year 2050, intelligent transportation represents the first (and most crucial) step in seeing these projects come to fruition.
According to INRIX’s 2017 Traffic Scorecard, the estimated total economic costs from traffic congestion in the US, UK and Germany amounted to $461bn. When coupled with the forecasted explosion of migration to major cities, the effects and economic impact of congestion are likely to be substantial.
Many of the issues stem from the limitations of current traffic management systems. These systems are programmed on outdated traffic data and based on traditional timing; which leaves them unable to adjust to irregular events like accidents and construction work. So, when the pre-programmed flow is disrupted, there is a knock-on effect.
An intelligent or “smart” digital system could help cities manage congestion and flow more efficiently. And it seems that software innovations hold the key to optimising these antiquated systems. While there are lots of complexities and complications involved with digitalising our roads, there are a number of intelligent technologies that utilise existing assets to transform and update transportation.
Fibre enabled solutions, powered by state-of-the-art distributed acoustic sensor (DAS) technology, provide a smarter way to improve and manage the efficiency of transport networks. These solutions work by augmenting and optimising fibre optic cables, assets that run for miles and are already in place in almost all cities and urban areas.
Such solutions combine DAS with advanced artificial intelligence and edge computing systems to detect, classify and report on traffic and transport infrastructure activities with confidence in real-time. This means that local authorities can determine the speed and density of traffic, locate congestion and detect disruptions. By having access to such intelligent insights in real-time, city departments can optimise the efficiency of their entire transportation networks – either by dynamically adapting traffic controls or redirecting traffic to balance overall flows and avoid crippling congestion on major arteries.
When it comes to smart cities, DAS is set to be a vital part in the technology puzzle. Such projects need solutions that can both adapt and enhance existing assets while working collaboratively alongside other technologies. Due to its flexibility, DAS is likely to be one of the first ‘live’ installations of true smart city technology.