An intelligent system for facility management

A software system has been developed that monitors and interprets temporally changing (internal) building environments and generates related knowledge that can assist in facility management (FM) decision making. The use of the multi agent paradigm renders a system that delivers demonstrable rationality and is robust within the dynamic environment that it operates. Agent behaviour directed at working toward goals is rendered intelligent with semantic web technologies. The capture of semantics though formal expression to model the environment, adds a richness that the agents exploit to intelligently determine behaviours to satisfy goals that are flexible and adaptable. The agent goals are to generate knowledge about building space usage as well as environmental conditions by elaborating and combining near real time sensor data and information from conventional building models. Additionally further inferences are facilitated including those about wasted resources such as unnecessary lighting and heating for example. In contrast, current FM tools, lacking automatic synchronisation with the domain and rich semantic modelling, are limited to the simpler querying of manually maintained models.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An intelligent system for facility management

A software system has been developed that monitors and interprets temporally changing (internal) building environments and generates related knowledge that can assist in facility management (FM) decision making. The use of the multi agent paradigm renders a system that delivers demonstrable rationality and is robust within the dynamic environment that it operates. Agent behaviour directed at working toward goals is rendered intelligent with semantic web technologies. The capture of semantics though formal expression to model the environment, adds a richness that the agents exploit to intelligently determine behaviours to satisfy goals that are flexible and adaptable. The agent goals are to generate knowledge about building space usage as well as environmental conditions by elaborating and combining near real time sensor data and information from conventional building models. Additionally further inferences are facilitated including those about wasted resources such as unnecessary lighting and heating for example. In contrast, current FM tools, lacking automatic synchronisation with the domain and rich semantic modelling, are limited to the simpler querying of manually maintained models

Towards a synchronized semantic model to support aspects of building management

To improve the performance of building facility management tools and optimize operational costs, a semantic model is being developed that is synchronized in almost real time with a range of sensors throughout the building. The semantic aspect of the model will be comprised of novel ontological perspectives with identified scopes and restricted domain theories that will simplify the modeling representations to deliver easier knowledge maintenance and continued integrity of the overall system. Specialized ontologies are linked to shared higher level abstract ontologies (to facilitate interoperation), and target a wide range of domains including those to capture physical processes and product mode

An ontology framework for intelligent sensor-based building monitoring

Contemporary building management is highly complex. Real time building information collected from various sensors needs to be managed smartly and promptly, and the corresponding software system ideally should have enough intelligence to consume these inter-connected and domain oriented information in an autonomous way. This paper focusses on the ontology development process to deliver an intelligent multi-agent software framework (OntoFM) supporting real time building monitoring. Different ontology development methodologies and frameworks have been reviewed. These have informed the development of a building monitoring ontology framework and its underpinning ontologies (sensor ontology, building ontology, and other supporting ontologies). The resulting ontologies have been tested and validated following a two-staged approach. The development renders a system that delivers demonstrable rationality and robustness within the dynamic environment in which it operates. The capture of semantics through formal expression to model the environment adds a richness that the agents exploit to intelligently determine behaviours to satisfy goals that are flexible and adaptable. The developed building monitoring software framework has been deployed in several locations for testing purposes, and demonstrates the potential for larger scale deployments

Towards intelligent agent based software for buildings related decision support

To automatically deliver enhanced knowledge relating to building use, for tasks such as facility management (FM), a software system has been developed that exploits the combination of a number of technologies. As well as generating useful knowledge for decision support, the software aims to remove reliance on expert users, be self configuring, continually adapt to the environment, and employ learning to evolve its performance. The system is realised centrally by a multi agent society in which the agents are characterised by the strong notion of agency using the BDI (belief, desire, intention) model. In most existing applications in construction agents are task focussed rather than the goal focussed deliberative agents employed here. The BDI model is a ‘natural’ (human) abstraction for modelling complex systems, and goals are a stable way to define required behaviour. The agents are supported by a range of ontologies describing the semantics of the domain as well as aspects of agents’ goals. Furthermore the agents utilise a distributed network of readily available wired and wireless sensors and associated data storage providing access to near real time and historical data, as well as an Industry Foundation Classes (IFC) model describing building geometry and construction. The system produced can be used by non-specialist users, simply requiring an IFC specification of the building and sensor locations. Agents infer the roles of the sensors from an ontology together with context, and assign appropriate roles. The agents individually and cooperatively work towards identifying the usage and dynamics of arbitrarily sized spaces in buildings. Such knowledge can be used to support FM decisions such as the optimisation of the energy consumption/environmental comfort demand trade-off. Negotiation is used to increase robustness as well as to fill in missing information. The limitations of practical application of the technologies that failed to deliver expected benefit are also detailed

Software agent reasoning supporting non-intrusive building space usage monitoring

Conventional facility management (FM) software tools, lacking automatic synchronisation with the domain and rich semantic modelling, are limited to the simpler querying of manually maintained models. A software system that monitors and interprets temporally changing (internal) building environments and generates related knowledge can better assist in facility management decision making. This paper introduces a non-intrusive building monitoring framework that includes ZigBee sensor network and supporting software agents to provide better building space usage monitoring through software agents based on the belief-desire-intention (BDI) abstraction, exploiting ontology based reasoning to direct behaviour. The non-intrusive method is particularly useful and more amenable than the use of cameras for example when building monitoring involves human behaviours. The use of the multi agent paradigm renders a system that delivers demonstrable rationality and is robust within the dynamic environment that it operates. Agent behaviour directed at working towards goals is rendered intelligent with semantic web technologies. The capture of semantics through formal expression to model the environment adds a richness that the agents exploit to intelligently determine behaviours to satisfy goals that are flexible and adaptable. The agent goals are currently used to generate knowledge about building space usage as well as environmental conditions by elaborating and combining near real time sensor data and information from conventional building models. The deployed and tested sensor based monitoring framework exhibits intelligence that will find application in the better support of decision making by integration with existing FM tools