Upgrading BRICKS—The Context-Aware Semantic Rule-Based System for Intelligent Building Energy and Security Management

Building management systems (BMSs) are being implemented broadly by industries in recent decades. However, BMSs focus on specific domains, and when installed on the same building, they lack interoperability to work on a centralized user interface. On the other hand, BMSs interoperability allows the implementation of complex rules based on multi-domain contexts. The Building’s Reasoning for Intelligent Control Knowledge-based System (BRICKS) is a context-aware semantic rule-based system for the intelligent management of buildings’ energy and security. It uses ontologies and semantic web technologies to interact with different domains, taking advantage of cross-domain knowledge to apply context-based rules. This work upgrades the previously presented version of BRICKS by including services for energy consumption and generation forecast, demand response, a configuration user interface (UI), and a dynamic building monitoring and management UI. The case study demonstrates BRICKS deployed at different aggregation levels in the authors’ laboratory building, managing a demand response event and interacting autonomously with other BRICKS instances. The results validate the correct functioning of the proposed tool, which contributes to the flexibility, efficiency, and security of building energy systems.

FoT-Rules: A Semantic Rule-based Approach for Smart Spaces Through Fog of Things

Through the Internet of Things (IoT), Smart Spaces will enable environments to adapt according to users’ needs by using smart and connected objects. However, to turn the IoT view into a reality, the users should know about technical details of such objects, which is not a trivial task for most ordinary users. Therefore, this paper presents FoT-Rules, an approach for the construction of semantic rules aiming to create Smart Spaces through Fog of Things, which is a paradigm for Fog Computing in the IoT. FoT-Rules is designed to enable ordinary users to create and execute semantic rules in the Event-Condition-Action standard (ECA) and to take actions at the edge of the network. In this work, we present a scenario where the user can create semantic rules in the ECA standard and, in order to execute these rules at the network edge, FoT-Rules provides the following functionalities: creation of semantic rules; obtaining of the semantic models that contains information related to IoT devices; execution of a semantic reasoner over the semantic model according to the rule created by the user; a semantic observer that is responsible for observing changes in IoT devices; and in case the rule created by the user is activated, an action is taken for an IoT device. Finally, we performed four types of evaluations on our FoT-Rules approach: reliability, efficiency, scalability and usability.

Rule-Based Actionable Intelligence for Disaster Situation Management

Managing natural disasters is a social responsibility as they might cause a gloomy impact on human life. Efficient and timely alert systems for public and actionable recommendations for decision makers may well decrease the number of casualties. Web semantics strengthen the description of web resources for exploiting them better and making them more meaningful for both human and machine. In this work, the authors propose a semantic rule-based approach for disaster situation management (DSM) to reach the next level of decision-making power and its architecture for providing actionable intelligence in the domain of the earthquake. The system itself is based on a data pre-processing layer, a computation layer, and the middle layer relies on an extensive rule base of experts' advice stored over time and a disaster ontology along with its inherent semantics. The rule-based reasoning approach uses this knowledge base in combination with the expert rule base, written in SWRL rules, to infer recommendations for the response to an earthquake.