An ontology-based decision support tool for optimizing domestic solar hot water system selection

Kontopoulos, Efstratios; Martinopoulos, Georgios; Lazarou, Despina; Bassiliades, Nick

doi:10.1016/j.jclepro.2015.08.088

Cited by 44 publications

(19 citation statements)

References 16 publications

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“…Knowledge-based decision support systems also have been adopted in domains other than health. For instance, in [19], the authors presented an ontology-based decision support tool that helps users to select a domestic solar hot water system that meets the user's needs such as installation costs, components and their interrelationships, number of occupants, house location, and daily hot water requirements. In [20], an ontology-enabled decision support system for manufacturing process selection is described.…”

Section: Related Workmentioning

confidence: 99%

AgriEnt: A Knowledge-Based Web Platform for Managing Insect Pests of Field Crops

et al. 2020

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In the agricultural context, there is a great diversity of insects and diseases that affect crops. Moreover, the amount of data available on data sources such as the Web regarding these topics increase every day. This fact can represent a problem when farmers want to make decisions based on this large and dynamic amount of information. This work presents AgriEnt, a knowledge-based Web platform focused on supporting farmers in the decision-making process concerning crop insect pest diagnosis and management. AgriEnt relies on a layered functional architecture comprising four layers: the data layer, the semantic layer, the web services layer, and the presentation layer. This platform takes advantage of ontologies to formally and explicitly describe agricultural entomology experts’ knowledge and to perform insect pest diagnosis. Finally, to validate the AgriEnt platform, we describe a case study on diagnosing the insect pest affecting a crop. The results show that AgriEnt, through the use of the ontology, has proven to produce similar answers as the professional advice given by the entomology experts involved in the evaluation process. Therefore, this platform can guide farmers to make better decisions concerning crop insect pest diagnosis and management.

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Section: Related Workmentioning

confidence: 99%

AgriEnt: A Knowledge-Based Web Platform for Managing Insect Pests of Field Crops

et al. 2020

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“…Ontologies have been extensively adopted in separate parts of the decision-making process [39][40][41], mostly for the formal representation of the domain of interest. On the contrary, our developed framework demonstrates the extensive use of ontologies and of relevant reasoning technologies for handling both the static (representation) and dynamic (realization, inference) processes of a DS system.…”

Section: Personalized Recommendations Based On Environmental Datamentioning

confidence: 99%

hackAIR: Towards Raising Awareness about Air Quality in Europe by Developing a Collective Online Platform

Kosmidis

Syropoulou

Tekes

et al. 2018

IJGI

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Abstract:Although air pollution is one of the most significant environmental factors posing a threat to human health worldwide, air quality data are scarce or not easily accessible in most European countries. The current work aims to develop a centralized air quality data hub that enables citizens to contribute to air quality monitoring. In this work, data from official air quality monitoring stations are combined with air pollution estimates from sky-depicting photos and from low-cost sensing devices that citizens build on their own so that citizens receive improved information about the quality of the air they breathe. Additionally, a data fusion algorithm merges air quality information from various sources to provide information in areas where no air quality measurements exist.

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“…Ontologies have been proposed in EDSS for different tasks: in [12] for semantic search and easy access of structured environmental data; in [13] for integrating existing local databases of environmental data as part of the Linked Open Data cloud, enabling the linking of data in an established context and the dissemination of environmental information to the masses; in [14] for facilitating the process of selecting domestic solar hot water systems according to specific criteria, and in [15] for integrating heterogeneous content from multiple environmental sources. Despite the increasing deployment of ontology-based solutions in DSS, their potential is merely exploited, either for creating a structured representation of the domain of interest, or for supporting parts of the decision making process.…”

Section: Related Workmentioning

confidence: 99%

An Ontology-Based Decision Support Framework for Personalized Quality of Life Recommendations

Riga

Kontopoulos

Karatzas

et al. 2018

Decision Support Systems VIII: Sustainable Data-Driven and Evidence-Based Decision Support

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As urban atmospheric conditions are tightly connected to citizens' quality of life, the concept of efficient environmental decision support systems becomes highly relevant. However, the scale and heterogeneity of the involved data, together with the need for associating environmental information with physical reality, increase the complexity of the problem. In this work, we capitalize on the semantic expressiveness of ontologies to build a framework that uniformly covers all phases of the decision making process: from structuring and integration of data, to inference of new knowledge. We define a simplified ontology schema for representing the status of the environment and its impact on citizens' health and actions. We also implement a novel ontology-and rulebased reasoning mechanism for generating personalized recommendations, capable of treating differently individuals with diverse levels of vulnerability under poor air quality conditions. The overall framework is easily adaptable to new sources and needs.

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An ontology-based decision support tool for optimizing domestic solar hot water system selection

Cited by 44 publications

References 16 publications

AgriEnt: A Knowledge-Based Web Platform for Managing Insect Pests of Field Crops

AgriEnt: A Knowledge-Based Web Platform for Managing Insect Pests of Field Crops

hackAIR: Towards Raising Awareness about Air Quality in Europe by Developing a Collective Online Platform

An Ontology-Based Decision Support Framework for Personalized Quality of Life Recommendations

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