designing business rules to identify bim impact on - 2
TRANSCRIPT
DESIGNING BUSINESS RULES TO IDENTIFY BIM
IMPACT ON DRIVING POLICIES FOR THE BUILT
ENVIRONMENT
Alan Martin Redmond PhD
The 1st International Conference on Industrial, Systems
and Manufacturing Engineering (ISME’14)
Authors
Alan Martin Redmond: Department of Civil Engineering, University of Toronto, Toronto, Canada
Project Coordinator and Technical Architect for the Green 2.0 Project, [email protected]
Prof Mustafa Alshawi: Department of the Built Environment, University of Salford, Salford, United Kingdom, [email protected]
Jason Underwood: Department of the Built Environment, University of Salford, Salford, United Kingdom, [email protected]
Proposal I: Tagging Objects
VOCs such as Acetaldehyde and Benzedrine
Proposal II: BIM Eco-service
Functional Architecture
Corporate Social Responsibility (CSR)
Policy Framework: Decision Support Tool
Atikins and UCL’s Development Planning
Unit in partnership with the UK’s
Department for International
Development (DFID) developed an
integrated diagnostic risk model.:
1. Identifying the solutions relevant to city
types,
2. Identifying vulnerabilities addressed and
economic development benefits,
3. Identifying the capacity required for
implementation,
4. Assessing impact and cost effectiveness
and
5. Assembling policy portfolios
N a t i o n a l R e s e a r c h C o u n c i l C a n a d aIndoor Air Quality Guidelines and Standards
Main groups of substance and their
source known to cause indoor air pollutionSubstance Source Indoor air pollution
Endocrine-disrupting
chemicals
Phthalates; pesticides (used in vinyl, plastics, building materials);
(gardening)
Radon Radioactive gases Enters the building from the ground and ingress
depends upon factors such as local geology
Inorganic gases Carbon dioxide (CO₂), carbon
monoxide (CO), nitrogen oxides (NOₓ),
sulphur dioxide (SO₂)
Particles from biological origin, cooking
Volatile organic compounds
(VOCs)
Aromatic or halogenated solvents,
vinyl chloride (paints),borax
Consumer products including electrical goods such
as computers and printers and cleaning products
Very volatile organic
compound (VVOC)
Formaldehyde Adhesives, office furniture, panel systems, a range
of building and consumer products
Semi-volatile organic
compounds (SVOCs)
Pentachlorophenol, polyaromatic
hydrocarbons (PAHs), and phthalates
Polymeric materials such as vinyl flooring and
paints
Microbial volatile
compounds (MVOCs)
Metabolism Compounds formed in the metabolism of fungi
and bacteria
Ozone Photochemical reaction Reaction of ambient air with surface and airborne
pollutants to produce new organic compounds
and particles
Ultrafine and nanoparticles Particles sized between 1 and 100
nanometers
Nanomaterials and combustion, such as burning a
candle or smoking a cigarette
Asbestos fibres Crocidolite (blue asbestos ), Amosite
(brown asbestos) and Chrysotile
Present in many buildings (roofs, ceilings, walls
and floors, thermal insulation products) and
presents a risk of cancer if fibres are inhaled
Source: Bluyssen, 2010
SOA – Web 2.0 – Semantic Web
RDF/XML-based serializations for the
Semantic Web
The RDF data model is similar to classic conceptual modelling i.e. entity relationship
It is based upon the idea of making statements about resources (“in particular web resources”) in the form of triples:
Statement - “The sky has the color blue”
Subject = “sky”
Predicate = “has”
Object = “the color blue”
RDF swaps object for subjects – object (sky), attribute (color), value (blue) instance
Knowledge management – process of capturing, delivering, sharing and using organisational software
Pattern matching “XSL Processor”
Exchanging information
1. Client queries the registry
2. Registry refers client to
Subset XML
3. Client access the subset
document
4. SOA provides
infrastructure for web
services
5. Client sends REST request
6. Web service return the
request
SEMANTIC WEB
Conclusion Advantages
There is great appeal in a Web that has the potential ability to “know”
and “understand” data with an even greater capacity to process better
than its parent. (http://segonku.unl.edu/beinghuman/?cat=24)
“Asynchronously linking Web services in a structure not so much
ontology (we will get there) engineers will lead the way”
Limitations
LogicGEM Decision Tables versus Prolog
Prolog; has its roots in first-order logic (mathematics and philosophy) –
the program logic is expressed in terms of relations, represented as facts
and rules. A computation is initiated by running a query over the
relations.
Semantic web; developers are challenged by providing a language that can
express both data and rules for reasoning. There is no reliable way to
process semantics which questions the purpose of developing such a
large-scale project.
Questions