Data analytics is the trump card for reducing urban congestion

 Photo: Pexels

Photo: Pexels

Though the idea of smart cities has been lingering around in the mainstream rhetoric for a considerable amount of time, the relevance of what these futuristic cities entail is something that is left to individual perspectives. With regard to transportation, the argument put forth is about facing urban transit demands in overflowing cities, and in addressing carbon footprint milestones through zero-emission transport.

But to get this to fruition, it is imperative to develop a transportation setup which involves better utilization of data, running machine learning models that could provide predictive analytics, and bridging stakeholders through a safe and immutable channel for data sharing.

“A smart city is many things to many people. Yes, there are clearly instances of technology being able to help, but we have a situation where we need to see what the citizens feel would be useful, how we engage with them, and the impact of technology on them,” said Carl Rodrigues, head of partnerships at Streamr, a data exchange platform.

Rodrigues spoke about the immensity of data being generated every minute across cities, and the endless possibilities of data analytics which could bolster transportation networks. “People often talk about physical and data infrastructure. The physical infrastructure of a city could be anything from traffic lights to road signs. What data infrastructure does is show where congestion is in the city and insights on what is happening in real time,” he said.

“We can gather data about the state of roads - maybe cracks and potholes via sensors in cars and combine the broad data with some AI models to help do predictive maintenance judgments,” said Rodrigues. “We can look at particular cracks that are more prone to becoming bigger problems, and the ones that might develop into potholes.”

Rodrigues created an analogy between oil and data. Like oil, data needs to be refined to make it useful and valuable - the absence of which would make it harder to derive insights. For a city, acquiring quality data is a struggle as it routinely procures data from telecom companies, which could give it an estimate on the movement of people inside a city - helping it to develop traffic models and subsequent town planning.

Data could also be gathered by fitting sensors over street lights for instance, which could effectively monitor the number of people moving past specific locations, and even about how fast they move. “If you have street lights that would be able to identify a lot of people running very fast, you might be able to have analytics to understand the problem, say an accident,” said Rodrigues. However, data generation also needs to be looked at from an ethical standpoint, as it is critical to not meddle with personal freedom and the privacy of citizens.

To stop a handful of companies from taking advantage of consumer data, Streamr has created a platform that would bring different businesses, people, and organizations together to share data and more importantly, get rewarded monetarily based on the value generated by the stakeholder.

“We are more interested in a decentralized marketplace where you have peer to peer buying and selling with no middlemen. We don’t take any transaction fees in the marketplace, because we are trying to break this idea of particular companies gathering data and not sharing it with anyone else,” said Rodrigues. “This way, the city saves money, gets a better traffic model, and citizens get a better quality of life because there is less congestion in the city.”

The need for data security led the company to look at blockchain, as the technology held everyone accountable and could handle data transparently. “With real-time data, it is important to deliver that data at scale, as you get it from thousands of different devices with only about 1% of IoT data being analyzed,” said Rodrigues.

“Now is the stage where the city needs smart contracts to be involved. When you have two organizations coming into an agreement about data access, you would need to codify that into a smart contract that can enable automatic decisions and subscriptions to happen,” he said. “This is something we put in blockchain - contracts, subscriptions, ability to set subscription costs, length of the subscription, and the possibility of monetizing data. All this can be codified into smart contracts.”

China is surging ahead in this race, with many of its cities running advanced IT systems and initiatives that help local city councils to improve town infrastructure and also mitigate energy wastage. Though data privacy concerns are significantly higher in the West, it is high time for countries to look at an easier way to share anonymized data, as weaponizing data analytics could be the best way to combat urban traffic of the future.