# Collecting, Processing and Secondary Using Personal and (Pseudo)Anonymized Data in Smart Cities
## 1 Introduction  
Urban data are the backbone of smart cities [1]. However, besides the promises of maximizing control and resources, reducing costs and improving public services, the deployment of smart cities strives in problems related to current technologies, designed for a specific job or context, most needing more privacy as a concern. As urban data include data about the citizens, including personal data, the indiscriminate application of these technologies to the context of a smart city might produce buggy, brittle and hackable urban systems, which create systemic vulnerabilities across critical infrastructure and compromise data security [2]. The intensive collection and processing of personal data, the emergence of privacy regulations, and the ubiquitous Internet of Things (IoT) are among the most challenging aspects of creating privacy-preserving smart city solutions. These challenges are not only caused by the secondary use of data, i.e., data used for another purpose than the one initially collected for, but also by the fact that data should be shared with others to optimize resources, improve the quality of life of inhabitants and create sustainable economic development. One example is provided by [3] using the collected checking-in and checking-out data in the public transportation system as an example. In this case, the primary use for the data is to bill the passenger for the traveled distance. However, the municipalities and transportation companies might post-process these data for better public transportation planning, such as deploying additional or more extended vehiclesfor a busy route. The municipalities can also share the data with the police to optimize their police patrols by identifying the hotspots in a city. Commercial companies might also exploit the data to develop new services for citizens, such as (real-time) route planners to guide citizens along the safest and shortest way to their destination. Municipalities might also use these data to improve their environmental policies, e.g., planting trees against air pollution in the identified area. The data types are also diverse and include a wide variety of content, such as geolocation, connections, environment measurements, social networks, text, web, image footage, videos, emails, tweets, audio recordings and others. This diversity is another challenge for the deployment of privacy protection mechanisms. Wide-used solutions, e.g., de-identification and anonymization, become increasingly complex for some data types or even impossible. The massive amount of data available in a smart city, including personal data, comes from different sources, such as the city's database, IoT sensors and third-party apps. For example, the city's database includes data about geographic information systems; smart building heating, ventilation and air conditioning systems; business supervisor (lighting, parking, waste, finance, etc.) systems; existing video surveillance systems; city police systems; municipal services; etc. In the case of IoT sensors, all things in public spaces must become \"smart\" to consolidate a truly smart city. So smart cities use sensors and other data collection tools to amass vast information about the town and their citizens that are stored in large data lakes. Later, the city's leadership analyzes all this information to generate an accurate picture of the urban environment, including details on how citizens live in and interact with their city. In most cases, third-party companies or software are employed for the analysis, requiring the data to be shared somewhere (e.g., a private cloud), which brings severe concerns regarding personal data privacy. The data maintained by service providers (bus transport, metro, etc.) and various third-party applications (energy suppliers, weather forecasts, water authorities, Waze, telecom operators, etc) are also a valuable source for the city. The collection of personal data for the sake of improving services and users' experience is not a new issue of smart cities.