Abstract
Internet of Things (IoT) has stimulated the development of numerous innovative applications in various domains, but the real potential of IoT has not been reached yet. A new paradigm, Cognitive Internet of Things (CIoT), is a step toward grasping that potential. With cognitive capability applied to IoT solutions, a whole new level of comfort is introduced to users. For example, smart home systems can make independent decisions on ambient condition adjustments based on user preferences. Handling all context types, i.e., the information about user preferences and current ambient conditions, is a rising challenge. With the aim to resolve this issue, we propose a smart lighting system based on Colored Petri Nets. The system is context-aware as it takes into account previously learned preferences of each individual user, the outside luminosity condition, as well as the current period of the day. The proposed system relies on an Artificial Neural Network for the calculation of optimal lighting settings.
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Acknowledgements
This work has been supported by Croatian Science Foundation under the project 1986 (IoT4us: Human-centric smart services in interoperable and decentralized IoT environments).
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Mandaric, K., Skocir, P., Jezic, G. (2021). A Smart Lighting Context-Aware Model Based on Colored Petri Net. In: Jezic, G., Chen-Burger, J., Kusek, M., Sperka, R., Howlett, R.J., Jain, L.C. (eds) Agents and Multi-Agent Systems: Technologies and Applications 2021. Smart Innovation, Systems and Technologies, vol 241. Springer, Singapore. https://doi.org/10.1007/978-981-16-2994-5_13
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DOI: https://doi.org/10.1007/978-981-16-2994-5_13
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