To create safe urban areas, it is important to gain insight into what influences the (perceived) safety of our cities and human settlements. One of the factors that can contribute to safety is the way urban spaces are designed. Previous work has highlighted the importance of natural surveillance: a type of surveillance that is a byproduct of how citizens normally and routinely use the environment. However, studying this concept is not a trivial task. Manual approaches such as observation studies are costly and time consuming and have therefore often limited themselves to smaller geographical areas.

In this work, we present a methodology that can automatically provide an estimate of natural surveillance by detecting building openings (i.e. windows and doors) in street level imagery and localizing them in 3 dimensions. The proposed method is able to estimate natural surveillance at the street segment level, while simultaneously being able to gather data on a whole city in a matter of hours. We then apply our method to the city of Amsterdam to analyze the relationship between natural surveillance and urban safety using the Amsterdam Safety Index.

We conclude that our chosen operationalization of natural surveillance (road surveillability and occupant surveillability) is correlated with decreases in high impact crime and nuisance as well as increases in perceived safety. Furthermore we provide evidence for the existence of a threshold after which extra natural surveillance is no longer associated with higher degrees of safety.

Escape rooms are an emerging market. In these physical and mostly group based games, players are locked in a room with the goal to solve puzzles within a certain time limit in order to ’escape’ the room. To make sure players have a pleasurable experience, they are monitored during the game by a so called game master. This person helps players during the game. When players get stuck the game master gives players a hint. Another possible task of the game master is to create an immersive story within the escape room. The game master can do this by communicating with the players while taking on the role of certain characters that are part of that story.
The goal of this project was to develop the Escape-Master system: a system that automates the role of the game master. In the system the game master can define an arbitrary escape room by inputting puzzles, characters and dialog for those characters. This dialog can include hints or storyline narrative. With this information provided, the system can automatically interact with the players. The system keeps track of the progress of the players and uses this information to interpret questions they provide to the system using natural language processing. After this the system can provide a fitting response, which can be a hint or narrative that progresses the story of the escape room. The system can also start interactions with players on its own, based on time passed of their progress in the game.
The project consisted of two phases: research and development. During the research phase information was gathered on player interaction, user engagement, and chatbots. During the development phase a system was constructed that permits the game master automate the process of giving hints and create an immersive story. Additionally, an interface was build to give the game master the ability to define an escape room and start games while being notified of the actions the system takes. It was tested in a live setting on two occasions, which yielded favorable results in terms of user engagement and immersion.