Abstract
Cooking a meal is a challenging and recurring task that requires the consideration of various environmental influences and constraints as well as significant domain knowledge. One way to reduce the complexity is to follow recipes that provide an ordered set of tasks for the preparation of a dish. This concept was already transferred to cooking assistants which present the recipe to the cook while adding further assistance like device control or step-by-step visualization. Although recipes and assistants simplify the cooking process itself, other factors like the available devices or differences in cooking skills are ignored. Aside from that, current assistants are often limited to one recipe at a time, ignoring the regularly occurring requirement to prepare a meal of multiple components. Considering these challenges, we propose our adaptive cooking assistant HanKA that considers the individual user skill and environmental kitchen setup, while assisting the cook at the preparation of their freely combined and synchronized recipes. This is achieved through a modular approach consisting of the automatic detection and control of the available devices and user interfaces, the scheduling of multiple recipes based on the distributed knowledge representation, and a deviation management that considers the user experience. Hereby, we created an adaptive cooking assistant that considers various influences that occur in a cooking scenario, resulting in a better assistance for the user.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Innit - Your food. Simplified and solved (2021). https://www.innit.com/. Accessed 02 Nov 2021
Plantjammer: Dynamic recipes (2021). https://www.plantjammer.com/dynamic-recipes. Accessed 02 Nov 2021
An, Y., et al.: PIC2DISH: a customized cooking assistant system. In: Proceedings of the 25th ACM International Conference on Multimedia, pp. 1269–1273. MM 2017, Association for Computing Machinery, NY (2017). https://doi.org/10.1145/3123266.3126490
Bosch: Cookit - küchenmaschine mit kochfunktion - bosch hausgeräte (2021). https://www.bosch-home.at/shop/kuechenmaschine-mit-kochfunktion1. Accessed 02 Nov 2021
De Smet, G., Open Source Contributors: OptaPlanner User Guide. Red Hat, Inc. or third-party contributors (optaPlanner is an open source constraint solver in Java) (2006). https://www.optaplanner.org
Hamada, R., Okabe, J., Ide, I., Satoh, S., Sakai, S., Tanaka, H.: Cooking navi: assistant for daily cooking in kitchen. In: Proceedings of the 13th Annual ACM International Conference on Multimedia, pp. 371–374. MULTIMEDIA 2005, Association for Computing Machinery, NY (2005). https://doi.org/10.1145/1101149.1101228
Hartmann, C., Dohle, S., Siegrist, M.: Importance of cooking skills for balanced food choices. Appetite 65, 125–131 (2013). https://doi.org/10.1016/j.appet.2013.01.016
Kephart, J., Chess, D.: The vision of autonomic computing. Computer 36(1), 41–50 (2003). https://doi.org/10.1109/MC.2003.1160055
Lawton, M.P., Brody, E.M.: Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist 9(3_Part_1), 179–186 (1969)
Light, R.A.: Mosquitto: server and client implementation of the MQTT protocol. J. Open Source Softw. 2(13), 265 (2017). https://doi.org/10.21105/joss.00265
Maedche, A., Morana, S., Schacht, S., Werth, D., Krumeich, J.: Advanced user assistance systems. Bus. Inf. Syst. Eng. 58(5), 367–370 (2016). https://doi.org/10.1007/s12599-016-0444-2
Müller, G., Bergmann, R.: CookingCAKE: a framework for the adaptation of cooking recipes represented as workflows. In: ICCBR (Workshops), pp. 221–232 (2015)
Neumann, A., et al.: “KogniChef’’: a cognitive cooking assistant. Künstl. Intell. 31(3), 273–281 (2017). https://doi.org/10.1007/s13218-017-0488-6
Neumann, N., Wachsmuth, S.: Recipe enrichment: knowledge required for a cooking assistant. In: Proceedings of the 13th International Conference on Agents and Artificial Intelligence - vol. 2: ICAART, pp. 822–829. INSTICC, SciTePress (2021). https://doi.org/10.5220/0010250908220829
Reichel, S., Muller, T., Stamm, O., Groh, F., Wiedersheim, B., Weber, M.: MAMPF: an intelligent cooking agent for zoneless stoves. In: 2011 Seventh International Conference on Intelligent Environments, pp. 171–178 (2011). https://doi.org/10.1109/IE.2011.18
Sato, A., Watanabe, K., Rekimoto, J.: MimiCook: a cooking assistant system with situated guidance, pp. 121–124 (2014). https://doi.org/10.1145/2540930.2540952
Thermomix: Thermomix® das original \(|\) vorwerk thermomix® (2021). https://www.vorwerk.com/de/de/c/home/produkte/thermomix. Accessed 02 Nov 2021
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Neumann, N., Wachsmuth, S. (2022). HanKA: Enriched Knowledge Used by an Adaptive Cooking Assistant. In: Bergmann, R., Malburg, L., Rodermund, S.C., Timm, I.J. (eds) KI 2022: Advances in Artificial Intelligence. KI 2022. Lecture Notes in Computer Science(), vol 13404. Springer, Cham. https://doi.org/10.1007/978-3-031-15791-2_15
Download citation
DOI: https://doi.org/10.1007/978-3-031-15791-2_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-15790-5
Online ISBN: 978-3-031-15791-2
eBook Packages: Computer ScienceComputer Science (R0)