Projects

Responsible Sensing Toolkit

6 steps on how to use sensors in public space in a responsible way.

Quick scan multi-party-computation

We are performing a quick scan for a pilot with secure multi-party computation (MPC) in Amsterdam.

Responsible Drones

Within the Responsible Drones project we explore how cities could utilize drones in a responsible way.

The Transparent Crowd Monitoring Camera

The number of crowd monitoring cameras in public places is increasing. What could be done to inform and ensure people that counting cameras are just there for the counting?

mmWave sensor

With the mmWave project we're investigating a privacy-friendly alternative for camera surveillance in the city.

Sound trigger

We evaluate a municipal pilot study of a so-called ‘sound trigger’ that is being used to assist the municipal Enforcement department and the police in detecting incidents in the city.

Alternative imaginaries for the smart city

From public values to urban sensors. An art- and design-led inquiry into urban imaginaries and urban technologies.

Design safe routes in sensing smart cities

In this project we work on the challenge that is posed by the increasing amount of surveillance in cities.

Nuisance of loud motorcycles and other loud vehicles is a substantial problem in cities, as shown by the many submitted complaints and petitions of residents addressed to the City of Amsterdam. We are exploring the impact of the potential implementation of ‘noise flash units’ in the city.

DCODE project

In 2022, two DCODE prototeams of PhD students will be working on a grand DCODE project at AMS Institute. The Responsible Sensing Lab provides the prototeams with cases that they will work on.

Scan cars

We question and explore which public and democratic values should be embedded in the implementation of scan cars. Could they be designed in a way that makes them (more) transparent, understandable or even contestable by citizens?

Transparent charging station

The transparent charging station is a design project meant to explain smart charging algorithm decisions to users.

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