Collecting data doesn’t automatically make for Smart Cities
“Smart Cities” is the catch-all for technology in urban environments. A true buzz word.
What it truly means is improving urban services through digital transformation; and connecting every layer of a city for maximum efficiency, from the users to the services to the air to the street to the underground. The technology contributes to making cities more sustainable and improving the quality of life for the people who live there.
Where people are often mistaken is they think by putting a million sensors on objects and hoarding the data in a data lake, their city is now a Smart City. Wahoo! KPI met. Smart Cities are about people and optimisation, not data. They provide improved mobility, better asset management, and the ability to benchmark.
What makes a city smart?
Technology and its subsequent data have always defined smart cities, but now that is not enough. In 2019 IMD World Competitiveness Center’s Smart City Observatory updated the definition of “smartness” to include people’s perception of the technology. The technological requirement is IoT connectivity. The technology needs to be optimised so that it not only exists but also actually gets used. The technology needs to get used by its inhabitants; then the services need to be improved upon. These improvements are about resource utilisation; better parking, efficient lighting, improved traffic flow, smarter security, improved waste management, and infrastructure efficiency.
Urban environment + data + people + action = Smart Cities
The often-forgotten part of smart cities is the people (you know, the ones who actually live there). An individual’s attitudes toward each technology will impact its uptake and consequently, the usability of the Smart City. Some barriers include a user’s willingness to give up personal data and also their trust in the organisation/government that the data will ultimately be used for the intended purpose. There is a transition of the way people communicate and interact with the environment around them. There can be an uncertainty around technology due to a lack of understanding from consumers, and with a globally aging population this will be an issue for some cities.
Smart Cities initiatives are often driven by private enterprise or by local councils. When asked by private enterprise, consumers will more readily give up their data, because they directly benefit from it, such as allowing google to take GPS data for live traffic information. However, as seen by the recent Government COVID-19 tracking app in Australia, consumers are hesitant to share their data with the Government.
5G — The next phase
5G is the next step in enabling Smart Cities. The word to know here is ‘latency’. Network latency is the time it takes for a set of data to travel between two points. 5G will reduce latency. With the increasing ease of data collection, we will see an increase in the number of sensors in “smart” assets. IoT technology will add a layer of intelligence to otherwise dumb objects such as all doors, light poles, fixtures, runways, etc. The more smart assets, the more data, and this is where people traditionally think Smart Cities end.
Seoul, Korea has been testing the world’s first Smart Cities 5G network integration. The city has been using digital networking for many years to improve health care, as well as transportation. Seoul is showcasing how fast, and efficiently its new network can deliver data to smart devices, which are being used by the Government, the medical community, and citizens.
Fast data is useful, but what good is getting more data if you don’t know what you do with it?
The major challenge with Smart Cities is how to extract, process, analyse and update IoT data more efficiently and effectively aka Data Analytics. Both Government and private enterprise are collecting large volumes of data from their Smart Cities and then not knowing how to create meaningful insights. What will solve this challenge is the better orchestration of data, not just faster transfer of data over short distances.
When data is held in disparate systems and databases, organisations cannot extract the full value of the data, limiting its utility. The answer is not more data but organised data. Knowing in advance what metrics are actually needed and what the outcome is of making things smart. By using a datacentric approach, businesses can optimise for the Smart Cities evolution. The next phase of development is delivering real improvements against critical metrics and priority outcomes using Smart Cities technology.
Smart Cities are about urban optimisation allowing for real-time responses. However, you cannot have real-time reactions if you do not have quality real-time data. But don’t be mistaken; data is a means to an end and not an end unto itself. By having a data-first approach with robust change management strategies and an optimisation plan, every city can successfully be a Smart City.
