Proactive Context-Aware IoT-Enabled Waste Management

Document identifier: oai:DiVA.org:ltu-76618
Access full text here:10.1007/978-3-030-30859-9_1
Keyword: Natural Sciences, Computer and Information Sciences, Media and Communication Technology, Naturvetenskap, Data- och informationsvetenskap, Medieteknik, Proactive adaptation, Reasoning model, Smart cities, IoT-enabled Waste Management, Pervasive Mobile Computing, Distribuerade datorsystem
Publication year: 2019
Relevant Sustainable Development Goals (SDGs):
SDG 12 Responsible consumption and productionSDG 11 Sustainable cities and communities
The SDG label(s) above have been assigned by OSDG.ai

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.

Authors

Orsola Fejzo

Luleå tekniska universitet; Datavetenskap
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Arkady Zaslavsky

Deakin University, Melbourne, Australia. ITMO University, Saint Petersburg, Russia
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Saguna Saguna

Luleå tekniska universitet; Datavetenskap
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Karan Mitra

Luleå tekniska universitet; Datavetenskap
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