Peter Hanappe

Sony CSL – Paris

Peter originally studied electronic engineering at the University of Ghent, Belgium, and then continued with a PhD in Computer Music at Ircam – Centre George Pompidou in Paris. He joined Sony Computer Science Laboratories – Paris in 2002. Some of his earlier work includes the use low-power computing techniques to exploit the unused computing power of home PCs to run large-scale climate simulations, requiring much less energy than data centers. In the NoiseTube project, users of cellphones collectively measure and create detailed maps of environmental pollution, particularly of urban noise.

The Midori Rooftop Farm

Peter Hanappe works on the urgent challenge of creating a more sustainable society and finding a new balance between Nature, Society, and Technologies. He is actively engaged in research on sustainable farming wherein he pioneers the concept of intensive microfarms. This approach combines the 19th century techniques of the Parisien market farmers with innovative technological tools and computational modeling. By emphasizing small-scale farms, his work targets an integrated solution that uses robots to assist with physically challenging tasks, sensors and AI to manage the crops, and online platforms for participatory agroecology.Many of these ideas were developed in the EU funded project, Robotics for Microfarms (ROMI) that Peter coordinated. Some of the work continues in the EU CENTRINNO project that aims to revive several industrial heritage sites in Europe by reintroducing local, small-scale production, such as urban farming in the Paris area. Peter is involved in two other noteworthy EU projects: DREAM and Mi-Hy. The DREAM project stems from a collaboration between Sony CSL – Paris and the Ecole Normale Supérieur (ENS-PSL). It develops a novel method for measuring plant health based on modulated light excitation and the classification of the plant’s chlorophyll fluorescence response using machine learning. The Mi-Hy project  combines Microbial Fuel Cells with hydroponics (soil-less, water-based crop production) to treat wastewater, produce energy, and recycle nutrients. Here, AI and robotics will be used to find the optimal system performance.