SWM-PnR: ontology-based context-driven knowledge representation for IoT-enabled waste management

Using knowledge-based and semantic technologies in IoT is a very active research and promising area. This paper proposes a method of ontology-based context-driven knowledge representation for IoT-enabled hard waste management as part of a wider international project that aims at building IoT ecosystems for smart cities. The paper presents the development of the waste management ontology, rules, and proposes a multistage data processing method that allows extracting knowledge about specific nontrivial situations on its basis. The paper describes implementation of the proposed system as a web application, where the content types are based on ontology, and data processing occurs according to the proposed algorithm. Benefits of the proposed knowledge-based system are discussed and demonstrated. The proposed approach will significantly improve monitoring and management of waste collection, route planning, and problem reporting.