Rule-based approaches for energy savings in an ambient intelligence environment

Stavropoulos, Thanos G.; Kontopoulos, Efstratios; Bassiliades, Nick; Argyriou, John; Bikakis, Antonis; Vrakas, Dimitris; Vlahavas, Ioannis

doi:10.1016/j.pmcj.2014.05.001

Cited by 36 publications

(31 citation statements)

References 14 publications

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“…Kobayashi et al [8] proposes a home energy monitoring system composed by human activity and environment monitoring system and a rule-based energy-saving advice system. Stavropoulos et al [9] report on the design, development and real-world adoption of an energy saving system in the building of a Greek public university. The system leverages a heterogeneous sensing infrastructure and a semantic middleware on top of which two rule-based approaches for enforcing energy-saving policies are proposed, one based on production rules and the other one using defeasible logics.…”

Section: Related Workmentioning

confidence: 99%

A resource-based rule engine for energy savings recommendations in educational buildings

Cuffaro¹,

Paganelli²,

Mylonas

2017

2017 Global Internet of Things Summit (GIoTS)

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Raising awareness among young people on the relevance of behaviour change for achieving energy savings is widely considered as a key approach towards long-term and costeffective energy efficiency policies. The GAIA Project aims to deliver a comprehensive solution for both increasing awareness on energy efficiency and achieving energy savings in school buildings. In this framework, we present a novel rule engine that, leveraging a resource-based graph model encoding relevant application domain knowledge, accesses IoT data for producing energy savings recommendations. The engine supports configurability, extensibility and ease-of-use requirements, to be easily applied and customized to different buildings. The paper introduces the main design and implementation details and presents a set of preliminary performance results.Index Terms-Internet of Things, REST, rule engine, energy consumption, behaviour change, educational buildings, Web of Things

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Section: Related Workmentioning

confidence: 99%

A resource-based rule engine for energy savings recommendations in educational buildings

Cuffaro¹,

Paganelli²,

Mylonas

2017

2017 Global Internet of Things Summit (GIoTS)

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“…Another interesting approach has been developed in [35] by Bikakis et al, for energy saving in an ambient intelligent environment is the usage of rulebased techniques. In this work it is suggested to use an agent, either reactive or deliberative, which enforces several energy-saving policies.…”

Section: Related Workmentioning

confidence: 99%

“…In this paper we go much further than has been done in [35,8] as we provide a general method for rule processing as applied to human interfaces to smart environments, in the specific case of energy saving.…”

Section: Related Workmentioning

confidence: 99%

Non-monotonic reasoning rules for energy efficiency

Tomazzoli

Cristani

Karafili

et al. 2017

AIS

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Abstract. Conflicting rules and rules with exceptions are very common in natural language specification employed to describe the behaviour of devices operating in a real-world context. This is common exactly because those specifications are processed by humans, and humans apply common sense and strategic reasoning about those rules to resolve the conflicts. In this paper, we deal with the challenge of providing, step by step, a model of energy saving rule specification and processing methods that are used to reduce the consumptions of a system of devices, by preventing energy waste. We argue that a very promising non-monotonic approach to such a problem can lie upon Defeasible Logic, following therefore an approach that has shown success in the current literature about usage of this logic for conflict rule resolution and for human-computer interaction in complex systems. Starting with rules specified at an abstract level, but compatibly with the natural aspects of such a specification (including temporal and power absorption constraints), we provide a formalism that generates the extension of a basic Defeasible Logic, which corresponds to turned on or off devices.

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“…Ambient Intelligence and Smart Environments are impulsed by ubiquitous computing and take advantage of the ease of collecting data from numerous devices in order to produce tasks such as optimisation of energy consumption [1], [2], recognition of human activity and preferences [3], [4], aid the elderly or persons with health problems [5], or even increase the lifestyle of blind people [6]. Although this type of implementations require physical sensors to capture data, there is another way to gather data without the need of a physical sensor.…”

Section: Introductionmentioning

confidence: 99%

Online social networks as sensors in smart environments

Barbosa

Santos

2016

2016 Global Information Infrastructure and Networking Symposium (GIIS)

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Abstract-Smart environments need to successfully identify their user needs, personality and behaviour in order to prepare appropriate interactions when facing different types of events. Personality is strongly associated with human behaviour and can be predicted with relatively accuracy by analysing online social profiles. Due to a constant presence in the lives of their users, online social networks have a decidedly strong social impact leading to a blur between offline and virtual life as well as the concept of digital identity and provide a rich source of data that can be used to profile and understand personal preferences and interactions of an individual. Users reveal a lot about themselves and share their personal preferences in a freely way and this paper exploits a new approach for smart environments to correctly identify their user's personality, using online social network as a sensor.

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Rule-based approaches for energy savings in an ambient intelligence environment

Cited by 36 publications

References 14 publications

A resource-based rule engine for energy savings recommendations in educational buildings

A resource-based rule engine for energy savings recommendations in educational buildings

Non-monotonic reasoning rules for energy efficiency

Online social networks as sensors in smart environments

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