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Welcome to today’s What is The Future For Cities podcast and its Research episode; my name is Fanni, and today I will introduce a research paper by summarising it. The episode really is just a short summary of the original paper, and, in case it is interesting enough, I would encourage everyone to check out the whole paper.

Our summary today works with the article titled Smart Telki – Answering citizen demand in the outskirts of Budapest from 2020 by Bence Majoros, Marcell Molnár, Tamás Sajti, and Rolland Vida, presented at the 2020 IEEE International Smart Cities Conference. I will interview Rolland Vida in the next episode, number 054I, and this is a great preparation for that interview. Plus, since we are investigating the future of cities, I thought it would be interesting to see how the global solutions can work in different settings. This article investigates some specific smart city developments applied to Telki, a small municipality in the outskirts of Budapest, Hungary, trying to answer some particular citizen demands.

In the last few years, smart cities have become very popular, and many municipalities want to become smart. However, current studies show that majority of such approaches still lack an integrated and well thought-through smart city strategy or proper implementation. Technologies, best practices and lessons learned from other cities around the world are certainly important to investigate, but each city has its own character, culture, issues, and citizens with demands. This paper presented the results of a project call Smart Telki, a cooperation between the city of council of Telki and the Budapest University of Technology and Economics. The goals were to investigate how specific user demands could be answered by smart city developments that are cost-efficient and make use of already deployed infrastructure elements, whenever possible.

Telki is a small municipality in the outskirts of Budapest, with a population of 5000 inhabitants. They are usually commuting to the capital on a daily basis for work or school. Although the city is often cited as the richest city of Hungary based on the per capita average income tax paid by its habitants, the municipality has limited financial resources. Therefore, the cost-efficiency of the proposed solutions was a primary requirement, for the problems, such as park and ride, overcrowded and delayed buses, time prediction for future rides, ride-sharing, and traffic monitoring. The authors highlighted that the smart city applications are not ground-breaking but noteworthy examples of cooperation between a municipality and its citizens.

Having dedicated park and ride parking spaces is a well-known solution to convince people to leave their cars and opt for public transportation. People arrive from the suburbs, park their car for the day, usually for free or a symbolic fee, and get on public transport to reach the city or its centre. Using park and ride parking slots can thus reduce the traffic in the city and its centre. However, the problem in Telki was of a different nature: people used the parking spaces in front of the school or the hospital as park and ride slots, leaving their vehicles for the whole day, but obstructing others who wanted to use the services in place.

The municipality considered different solutions, such as parking fee, time limitations, or creating a bigger park and ride parking space at the outskirts of Telki. Before deciding, the municipality wanted to evaluate the problem itself. Therefore, the research team suggested a simple and cost-effective way based on processing of the video stream of a surveillance camera installed at a restaurant facing the school’s parking space. The team used different masking and filtering functions to detect the shadow under the cars creating a precise identification of parking cars. They found that there are indeed people using the parking space for whole day parking. The municipality was in the decision phase when presenting so the results are not known. However, the team showed that existing infrastructure can be used to gather meaningful data and analyse that data to create insights into urban issues.

There were many complaints about the buses being delayed on regular basis, making people wait more than 15 or 20 minutes instead of the scheduled 8-10 minutes, or they are so overcrowded, they cannot take more passengers. The bus company serves many additional towns and villages before arriving to Telki on their way to Budapest. Before taking this issue to the bus company, the municipality wanted again assess the severity of the situation. The team again proposed to use surveillance cameras to monitor the buses and timestamp their arrivals to the bus stops. The analysis proved that buses are regularly delayed, especially in rush hours.

The citizens also wanted to know better how much time it will take for them to reach their destination. Google Maps suggestions vary based on the different time slots, such as early morning or rush hour, but it also gives a very safe bet on their side, for example stating that in the rush hour, people can reach the capital from Telki in 20-50 minutes. The research team wrote a script to try predicting better the time it takes to reach popular destinations from Telki. For meaningful prediction, they used Google Maps data, over a long period, statistically analysed, and also mentioned that these predictions can be even more precise with more data.

Taking own car can be convenient to reach Budapest from Telki, but if everyone chooses this option in all the outskirts of Budapest, that will lead to serious traffic jams in the rush hours, high fuel consumption and high pollution. Using public transport is an option, but not a flexible one, therefore, ride-sharing would be a really convenient and flexible solution to these issues, being more comfortable, cheaper, reducing traffic jams, and so on. Ride-sharing is not novel, but they are usually not available or not targeted to the specific needs of small local communities. The solutions currently existing, Oszkar and Waze Carpool is not yet sufficient for these ideas, therefore, the citizens use a Facebook page to find rides or passengers. The team created a dedicated ride-sharing web-portal to serve Telki and the commuting people. The portal is currently being tested but planned to be opened to the public.

While working on these issues and gathering data, the research team tried to analyse the data set further. The passing traffic load was one such topic, and the team used again the surveillance cameras to monitor the main road and process the images regarding the load and the different vehicle types. With such approaches, they were able to capture the traffic flow from and to Telki, establishing the rush hours precisely, and investigating the types of vehicles, while also getting a sense of how the COVID-19 pandemic affected the mobility, as the team started the data collection just before the pandemic.

Smart city applications and services together with underlying technologies can be taken over from one city to another, but they should be adapted to the demands of the local communities and the financial possibilities of the respective councils. No need to crack a nut with a sledgehammer if easier and more cost-efficient solutions are also available. The Smart Telki project is an example for such developments.

As the most important things, I would like to highlight 3 aspects:

1. Smart cities and solutions need to be translated to the particular city and apply them with acknowledgement to the present opportunities.
2. The solutions need to answer the local communities’ demands.
3. With a creative approach, current infrastructure can be used in a smarter way to investigate and create solutions for the city.

Additionally, it would be great to talk about the following questions:

1. How were the citizen demands collected? How active were the citizens in giving their requirements and ideas? How representative was the demand list of the population of Telki?
2. How have these demands change during the pandemic and how the council has accommodated those changes?
3. Do you have issues with your environment? Have you articulated them to the decision-makers?
4. Do you have ideas about how to analyse an issue in your area without extra cost?

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