• Intelligent Fire Safety system whose intelligence lies in implementing smart ways to detect and extinguish fires .
• Indoor Air Quality management system whose task is to self-monitor temperature , humidity and freshness of air for comfort and protection from diseases .
• Refrigerant leak detection system which smartly discovers leaks to prevent accidents .
• Integrated Communications Systems , AV systems and document management systems , which improve productivity in the workplace .
Discussion
This research has highlighted that achieving sustainability is one of the many features of building intelligence and by using the predictive model developed by this research one can add building intelligence as one of the prescriptive parameters of LEED and BREEAM rating systems , making intelligence one of the many features of sustainability .
Predicted BREEAM / LEED Score = a + b × log x ( where x = number of intelligent building technologies )
Both BREEAM and LEED rating systems calculate the sustainability value of a building based on various set parameters such as energy performance , CO2 emissions , water efficiency , materials , waste management , land ecology , site selection , air quality , etc . Though LEED and BREEAM are both well-established rating systems , there has been a growing chorus of critics which have taken issue with the point-based systems . The most commonly cited example being , developers get the same number of points for installing a bike rack as they do for a complex water recycling system ( Leonard , 2010 ). One can argue that the introduction of LEED and BREEAM have stimulated research into the building sciences though there is a lot to be done to perfect them , this research being a step towards the same . ( BSRIA , 2009 ; Inbuilt , 2010 ) The findings from this research also substantiate that sole reliability on prescriptive parameters is not a good idea . While developing a Rating System for evaluating a building ’ s cumulative intelligence and sustainability , one will have to take into consideration a more holistic approach so that the tool is more than just a measurement device .
Building intelligence is multi-dimensional , just like BREEAM and LEED , and can be categorised according to parameters such as resource efficient , dynamically responsive , self-monitoring , interactive within themselves and with people , comfort , safety and security , etc . Thus it was inferred from this study that intelligent buildings could also be defined in terms of the core intelligence functions of their systems based on what aspect of the building they made smarter . From the analysis one can clearly observe that ensuring a building is resource efficient is just one part of its being intelligent . If resource efficiency were the only definitive trait of intelligent buildings then a linear model would best describe the relation between the two variables in question . For example , the use of multiple LCD screens as part of an intelligent Security System . These screens require additional energy but if the function of the building were to protect highly classified data , then having a building , which ensures high standards of security would be of much more relevance than energy efficiency . This highlights that building functionality is a defining factor and by consequence of inter-relatability , so are the occupants ’ needs . Following on with the example , the users of the building require a highly secure facility with state-of-art intelligent security equipment for the hypothetical business to flourish and in turn increase their productivity and job satisfaction .
330 ZEMCH 2015 | International Conference | Bari - Lecce , Italy