Abstract
Exploiting future opportunities and avoiding problematic upcoming events is the main characteristic of a proactively adapting system, leading to several benefits such as uninterrupted and efficient services. In the era when IoT applications are a tangible part of our reality, with interconnected devices almost everywhere, there is potential to leverage the diversity and amount of their generated data in order to act and take proactive decisions in several use cases, smart waste management as such. Our work focuses in devising a system for proactive adaptation of behavior, named ProAdaWM. We propose a reasoning model and system architecture that handles waste collection disruptions due to severe weather in a sustainable and efficient way using decision theory concepts. The proposed approach is validated by implementing a system prototype and conducting a case study.
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Acknowledgement
This research was funded by the PERCCOM Erasmus Mundus Joint Master Program of the European Union [8]. Part of this study has been carried out in the scope of the project bIoTope, which is co-funded by the European Commission under Horizon-2020 program, contract number H2020-ICT- 2015/688203-bIoTope. The research was also supported by ITMO University, Russia and Luleå University of Technology, Sweden.
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Fejzo, O., Zaslavsky, A., Saguna, S., Mitra, K. (2019). Proactive Context-Aware IoT-Enabled Waste Management. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2019 2019. Lecture Notes in Computer Science(), vol 11660. Springer, Cham. https://doi.org/10.1007/978-3-030-30859-9_1
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