5.4 Research Approach The next element is the reasoning of the research (Sutrisna 2009) which refers to the logic of
6.4 Detailed Definition & Application of Data Instruments 6.4.1 Briefing Process
6.4.4 Asset, Facilities & Operational Systems
The impact of well‐maintained clean and vibrant cared for buildings and those which are tired and run down have a massive impact on the inhabitants and users wellbeing and effectiveness. Around 80% of the costs of an asset are expensed during its lifetime not during its delivery. However, with clear potential for good results the good application of Asset and Facilities Maintenance still eludes many businesses and assets, with many buildings operating sub‐optimally with the associated fiscal and social costs.
"Infrastructure Asset Management" is defined by the Institution of Civil Engineers (ICE) as; “The integrated, multidisciplinary set of strategies in sustaining public infrastructure assets such as water treatment facilities, sewer lines, roads, utility grids, bridges and railways. Generally, the process focuses on the later stages of a facility’s life cycle specifically maintenance, rehabilitation, and replacement. Asset management specifically uses software tools to organise and implement these strategies with the fundamental goal to preserve and extend the service life of long‐term infrastructure assets which are vital underlying components in maintaining the quality of life in society and efficiency in the economy”.
“Facilities management is the integration of processes within an organisation to maintain and develop the agreed services which support and improve the effectiveness of its primary activities”. Facilities management encompasses multi‐disciplinary activities within the built environment and the management of their impact upon people and the workplace.
Effective facilities management, combining resources and activities, is vital to the success of any organisation. At a corporate level, it contributes to the delivery of strategic and operational objectives. On a day‐to day level, effective facilities management provides a safe and efficient working environment, which is essential to the performance of any business – whatever its size and scope.
Facility Management (or facilities management or FM) is an integrated multidisciplinary, interdisciplinary field devoted to the coordination of space, infrastructure, people and organisation, often associated with the administration of office blocks, arenas, schools, convention centres, shopping complexes, hospitals, hotels, etc. However, FM facilitates on a much wider range of activities than just business services and these are referred to as non‐ core functions. Many of these are outlined below but they do vary from one business sector to another. In a 2009 Global Job Task Analysis, the International Facility Management Association (IFMA 2009) identified eleven core competencies of facility management. These are: communication; emergency preparedness and business continuity; environmental stewardship and sustainability; finance and business; human factors; leadership and strategy; operations and maintenance; project management; quality; real estate and property management; and technology.
The involvement of operational and facilities teams in the design, delivery, commissioning, training and handover of assets is known as "Soft Landings". This process ensures good communication, awareness and capability at the point of handover to ensure the operator receives an effective working asset. The application of Asset and Facilities Management services are discrete business services which require the formal application of "strategic Plans" and organisational capabilities. Effective delivery is enabled through the processing of data. New assets may receive data from the delivery process, however existing assets will require digitally surveying to establish a minimum manageable dataset to enable useful analysis to take place.
6.4.5 Operational Performance Management ‐ Telemetry, SCADA, Sensors, BMS and IoT The performance of an asset delivering it’s in service lifecycle is a complex concept to effectively measure. The variables that can be measured are vast, the position and type of sensors are almost infinite and the ability to measure consistently between spaces as well as buildings is difficult due to differences in calibration of sensors and differences in environmental conditions and asset usage. There are a vast number of methods to collect data and data has been collected discreetly in many building for several decades. Standards vary for this activity but the common systems include SCADA, IoT, BMS and other proprietary methods a summary is contained in Table 6.3.
Table 6.3 ‐ Data Collection Options
Number Method Observations
1 SCADA
(Supervisory
Control and
Data
Acquisition)
SCADA is a system operating with coded signals over communication channels
so as to provide control of remote equipment (using typically one
communication channel per remote station). The control system may be
combined with a data acquisition system by adding the use of coded signals over
communication channels to acquire information about the status of the remote
equipment for display or for recording functions. It is a type of industrial control
system (ICS). Industrial control systems are computer‐based systems that
monitor and control industrial processes that exist in the physical world. SCADA
systems historically distinguish themselves from other ICS systems by being
large‐scale processes that can include multiple sites, and large distances. These
processes include industrial, infrastructure, and facility‐based processes, as
described below:
Industrial processes include those of manufacturing, production, power
generation, fabrication, and refining, and may run in continuous, batch,
repetitive, or discrete modes.
Infrastructure processes may be public or private, and include water
treatment and distribution, wastewater collection and treatment, oil and
gas pipelines, electrical power transmission and distribution, wind farms,
civil defence siren systems, and large communication systems.
Facility processes occur both in public facilities and private ones, including
buildings, airports, ships, and space stations. They monitor and control
heating, ventilation, and air conditioning systems (HVAC), access, and
Number Method Observations
2 IoT
(Internet of
Things)
The Internet of Things (IoT) is the network of physical objects or "things"
embedded with electronics, software, sensors and connectivity to enable them
to achieve greater value and service by exchanging data with the manufacturer,
operator and/or other connected devices. Each thing is uniquely identifiable
through the allocation of a unique IP and MAC address. They may have their
own embedded computing system but are able to interoperate within the
existing Internet infrastructure.
3 BMS
(Building
Management
Systems)
A Building Management System (BMS) or a (more recent terminology) Building
Automation System (BAS) is a computer‐based control system installed in
buildings that controls and monitors the building’s mechanical and electrical
equipment such as ventilation, lighting, power systems, fire systems, and
security systems. A BMS consists of software and hardware; the software
program, usually configured in a hierarchical manner.
4 Other
Proprietary
Systems
There is also a vast array of systems which are proprietary based, using such
protocols as C‐bus, Profibus, and so on. Vendors are also producing systems that
integrate using Internet protocols and open standards such as DeviceNet, SOAP,
XML, BACnet, LonWorks and Modbus or Cube Sensors
As the researcher’s example project is a relatively simple asset with little embedded technology it was decided that a temporary mobile approach should be selected. As the project was research based cost was also a significant issue to a market analysis identified several proprietary products including a Slovenian product called Cube Sensors, which was the only product in the economy price band that was capable of measuring Volatile Organic Compounds which was one of the key measures identified in section 5.6.
6.4.5.1 Cube Sensors
Each Cube Sensor is fitted with seven sensors. They send measurements from each location to a base station every minute. Each of the measurements is recorded in a database for access by the Test Bench via a web service. Data is accessed via an applications programming interface (API) with the following data attributes available.
Table 6.4 ‐ Smart Sensor Data Properties Attribute Notes
Temperature Temperature recorded in degrees Celsius.
Temperature in °C * 100 (example: 2130 means 21.30°C)
Humidity % relative Humidity
Relative humidity in % (example: 45 means 45% relative humidity)
Air Quality Measured as a factor of Volatile Organic Compounds
Noise Recorded in dBA
Light Recorded in Lux
Atmospheric Pressure Recorded in mBar
Battery Battery Condition in %
Cable Either true or false, indicates whether the Cube is on cable and thus charging or
not
RSSI Wireless signal strength indicator (RSSI), the higher the number (closer to 0), the
stronger the signal
Time returned in UTC in the format year‐month‐dayThour:minute:secondZ (example:
"2013‐09‐27T01:06:17Z")
The values collected from the API property set shown in Table 6.4 are passed to the Test Bench data model entity "Sensor_Data1".