BOnSAI

Stavropoulos, Thanos G.; Vrakas, Dimitris; Vlachava, Danai; Bassiliades, Nick

doi:10.1145/2254129.2254166

Cited by 73 publications

(18 citation statements)

References 17 publications

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“…The ThinkHome ontology [87] aims at creating a comprehensive knowledge base that includes all the different concepts needed to realize energy-efficient, intelligent control mechanisms for homes. The purpose of the Building Ontology for Ambient Intelligence (BOnSAI) [88] is to enable the vision of ambient intelligence in large-scale service-oriented pervasive systems. The DogOnt ontology [89] describes different characteristics of smart environments such as location, capabilities, software interfaces, states, and composition.…”

Section: Schemas For Building Operations: Sensor Network Iot and Smentioning

confidence: 99%

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

et al. 2021

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Digital and intelligent buildings are critical to realizing efficient building energy operations and a smart grid. With the increasing digitalization of processes throughout the life cycle of buildings, data exchanged between stakeholders and between building systems have grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent and hinders the development of energy-oriented applications that can be reused across buildings, limiting the scalability of innovative solutions. Addressing this challenge, our review paper systematically reviews metadata schemas and ontologies that are at the foundation of semantic interoperability necessary to move toward improved building energy operations. The review finds 40 schemas that span different phases of the building life cycle, most of which cover commercial building operations and, in particular, control and monitoring systems. The paper’s deeper review and analysis of five popular schemas identify several gaps in their ability to fully facilitate the work of a building modeler attempting to support three use cases: energy audits, automated fault detection and diagnosis, and optimal control. Our findings demonstrate that building modelers focused on energy use cases will find it difficult, labor intensive, and costly to create, sustain, and use semantic models with existing ontologies. This underscores the significant work still to be done to enable interoperable, usable, and maintainable building models. We make three recommendations for future work by the building modeling and energy communities: a centralized repository with a search engine for relevant schemas, the development of more use cases, and better harmonization and standardization of schemas in collaboration with industry to facilitate their adoption by stakeholders addressing varied energy-focused use cases.

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Section: Schemas For Building Operations: Sensor Network Iot and Smentioning

confidence: 99%

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

et al. 2021

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“…Another interesting example is the BOnSAI ontology introduced by Stavropoulos et al . (2012), which is specialized for incorporating ambient intelligence concepts for smart building scenarios. It provides the capability to model explicitly functionality, QoS, hardware, context, as well as the user.…”

Section: Enabling Technologiesmentioning

confidence: 99%

A survey and taxonomy on intelligent surveillance from a system perspective

Mihailescu

Davidsson

Eklund

et al. 2018

The Knowledge Engineering Review

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Recent proliferation of surveillance systems is mostly attributed to advances in both image-processing techniques and hardware enhancement of smart cameras, as well as the ubiquity of sensor-driven architectures. Owing to these capabilities, new aspects are coming to the forefront. This paper addresses the current state-of-the-art and provides researchers with an overview of existing surveillance solutions, analyzing their properties as a system and drawing attention to relevant challenges when developing, deploying and managing them. Also, some of the more prominent application domains are highlighted here. In an effort to understand the development of the advanced solutions, based on their most distinctive characteristics, we propose a taxonomy for surveillance systems to help classify them and reveal gaps in existing research. We conclude by identifying promising future research lines.

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“…In [14] an ontology for enabling Ambient Intelligence in a Smart Building, named BOnSAI (Smart Building Ontology for Ambient Intelligence), is proposed. The ontology extends and benefits from existing ontologies in the field, but also adds classes needed to sufficiently model every aspect of a serviceoriented smart building system.…”

Section: Rules In Literaturementioning

confidence: 99%

Towards a Uniform Ontology-Driven Approach for Modeling, Checking and Executing WSANs

Vannucchi

Cacciagrano

Culmone

et al. 2016

2016 30th International Conference on Advanced Information Networking and Applications Workshops (WAINA)

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Wireless sensor and actuator networks (WSANs) refer to a group of sensors and actuators linked by wireless medium to perform distributed sensing and acting tasks. Being reactive systems, quite often WSANs are programmed by Event-Condition-Action (ECA) rule-based languages. Because of potential interactions among the rules themselves and theirsurprising effects on the system behaviour, it is quite difficult to ensure a safe behaviour of a WSAN at design time. This paper proposes a semantic-driven approach for modeling, checking and executing ECA rule-based WSANs. The approach can be considered uniform since any of the previous phases works on a common ontology-based WSAN model integrating and linking three different system views: the static one (i.e., sensor and actuator types in the WSAN, description of its environment, deployment information etc.), the dynamic one (i.e., a set of ECA rules programming the given WSAN) and the behavioural one (i.e., a finite state machine (FSM)-based representation of the WSAN behaviour w.r.t. the given dynamics). We show how the proposed approach provides an agile verification of system properties involving (and also mixing) static, dynamic and behavioural concepts. In particular, with regard to the behavioural view, we will focus on properties like consistency, correctness and termination. In order to better explain our approach, we present a home automation case study

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BOnSAI

Cited by 73 publications

References 17 publications

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

A survey and taxonomy on intelligent surveillance from a system perspective

Towards a Uniform Ontology-Driven Approach for Modeling, Checking and Executing WSANs

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