@inproceedings{50a3fa4c29b544d8b69ab42b4b26e1da,
title = "E-COmate: what{\textquoteright}s your non-consumption?",
abstract = "Most people lack awareness and hence understanding about how food-related behavior affects the environment. This commonly results in unsustainable food-related decision making, such as food waste. We propose E-COmate, an augmented bin that measures the weight of food waste through a USB postal scale, a bin and a Raspberry Pi with a Wi-Fi module, and give direct feedback to its users through a tablet by visualizing metaphorical units of the weighted food waste. We intend explore the use of E-COmate in redirecting behavior through transparency, visibility and social influence strategies like social comparison. In this paper, we present our concept, implementation, design rationale and plan of research which we expect to provide insights into the potential of eco-feedback integrated in smart home technology for food sustainability.",
keywords = "Eco-feedback, Food sustainability, Social interaction",
author = "V. Lim and M. Funk and G.W.M. Rauterberg and L. Marcenaro and C.S. Regazzoni",
year = "2015",
doi = "10.1007/978-3-319-19258-1_40",
language = "English",
isbn = "978-3-319-19257-4",
volume = "9094",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "486--499",
editor = "I. Rojas and G. Joya",
booktitle = "Advances in Computational Intelligence : 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, Palma de Mallorca, Spain, June 10-12, 2015. Proceedings, Part I",
address = "Germany",
}