|Digital Matter
|Synapse
Chitosan as the future of water filtration system
|Team
Hayder Mahdi, Nikol Kirova, Shruti Jalodia
|Faculty
Areti Markopoulou, David Andres Leon, Raimund Krenmueller
|Project year
2017-18
Synapse research and experiments aim to offer designers and decision-makers a sensor-driven insight into users’ spatial behavior. This approach facilitates an evidence-based, data-driven process for behavioral research by integrating surface-embedded Graphene Nanoplatelets with capacitive sensing technology and machine learning algorithms. This innovative research presents an interactive platform capable of sensing user presence, tracking positions, and recognizing gestures, enhancing contextual understanding.
In this research, a proprietary, highly-conductive Graphene ink composition was developed. The ink mixture is programmable to exhibit high conductivity when utilized for sensory electrodes and high resistance when applied in functions like heating pads.
The sensor system, designed with surface-embedded technology, can be integrated into floor or wall surfaces, either beneath existing finishes or in the form of specialized ‘active tiles.’ It consists of perpendicular electrodes on a PETG sheet with protective layers, adaptable through two methods: large continuous under-mats for embedding on various surfaces and modular tiles, allowing for integration into concrete or wood surfaces.
In configuring spatial layouts, this research utilizes genetic algorithms and machine learning to optimize object positioning within a given space. It considers factors such as visual connectivity, sunlight exposure, and pedestrian paths to determine the ideal arrangement. By training artificial neural networks, the system predicts object coordinates based on these factors, providing designers with a comprehensive overview of spatial performance. Tools like Ladybug analysis, BioMorpher, and OWL machine learning in Grasshopper aid in achieving this holistic spatial assessment.
The applications of this research span across urban data analysis and localized heating solutions. By recording footsteps and generating dynamic occupancy maps, the system assists urban authorities in understanding user engagement, managing public spaces effectively, evaluating risks, predicting maintenance needs, and deploying emergency services. Moreover, the integration of Graphene-based heating pads with the sensory surface enables localized heating triggered by user interaction. This system’s potential development includes dynamically controlled, automatic heating based on user presence, offering substantial energy-saving opportunities
