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CATHEGORIES COMPONENTS Ai (Process) Related categories
COMFORT OPTIMIZATION
THERMAL
Intelligent, predictive and self-learning algorithm to use the HVAC system and the BUILDING ENVELOPE to guarantee the best Thermal condition according with defined parameters and USER REQUEST (through interface) in different scenarios
HVAC system, Building envelope (window and shading), Internal environment temperature sensors, external environment (temperature sensor + forecast), occupant presence and activity, appliances
LIGHT
Automated (light, user activity), predictive and self-learning (user habits/request) light appliances On-Off-Dimmer to guarantee the best light condition in different scenarios according with defined parameters and USER REQUEST (through interface)
External environment (light, solar intake, glare sensor + forecast), Internal environment light sensors, Occupant presence, occupant activity, Building envelope, Light appliances Shading automated (light, user activity),
predictive (weather/user habits)) and self-learning (user habits/request) regulation to guarantee the best light condition in different scenarios according with defined parameters and USER REQUEST (through interface)
ACOUSTIC
Appliances automated and self-learning (user habits) On-Off-Dimmer according with the real time user activity and the scheduling to guarantee the best acoustic condition in
different scenarios External environment (wind, noisy sensor), Internal environment noisy sensors, Occupant presence, occupant activity, Building envelope, Appliances, Systems
Building envelope automated and self-learning (user habits) regulation according with the external environment situation and the internal scenario request.
System automated and self-learning (user habits) operation to guarantee the least disturbance according with the real time user activity and the scheduling.
IAQ
Intelligent, predictive and self-learning algorithm to use the HVAC system and the BUILDING ENVELOPE to guarantee the best IAQ condition according with defined parameters and USER REQUEST (through interface) in different scenarios
HVAC system, Building envelope (windows), IAQ Internal environment sensors, external environment (Humidity, Wind + forecast), occupant presence and activity, appliances
CONVENIENCE
Lift predictive call with Occupants sensor data
Lifts, Appliances, Occupant activity and presence
Appliances automated and self-learning (user habits) On-Off
Other process request from the user
CATHEGORIES COMPONENTS Ai (Process) Related categories
COMFORT OPTIMIZATION
THERMAL
Intelligent, predictive and self-learning algorithm to use the HVAC system and the BUILDING ENVELOPE to guarantee the best Thermal condition according with defined parameters and USER REQUEST (through interface) in different scenarios
HVAC system, Building envelope (window and shading), Internal environment temperature sensors, external environment (temperature sensor + forecast), occupant presence and activity, appliances
LIGHT
Automated (light, user activity), predictive and self-learning (user habits/request) light appliances On-Off-Dimmer to guarantee the best light condition in different scenarios according with defined parameters and USER REQUEST (through interface)
External environment (light, solar intake, glare sensor + forecast), Internal environment light sensors, Occupant presence, occupant activity, Building envelope, Light appliances Shading automated (light, user activity),
predictive (weather/user habits)) and self-learning (user habits/request) regulation to guarantee the best light condition in different scenarios according with defined parameters and USER REQUEST (through interface)
ACOUSTIC
Appliances automated and self-learning (user habits) On-Off-Dimmer according with the real time user activity and the scheduling to guarantee the best acoustic condition in
different scenarios External environment (wind, noisy sensor), Internal environment noisy sensors, Occupant presence, occupant activity, Building envelope, Appliances, Systems
Building envelope automated and self-learning (user habits) regulation according with the external environment situation and the internal scenario request.
System automated and self-learning (user habits) operation to guarantee the least disturbance according with the real time user activity and the scheduling.
IAQ
Intelligent, predictive and self-learning algorithm to use the HVAC system and the BUILDING ENVELOPE to guarantee the best IAQ condition according with defined parameters and USER REQUEST (through interface) in different scenarios
HVAC system, Building envelope (windows), IAQ Internal environment sensors, external environment (Humidity, Wind + forecast), occupant presence and activity, appliances
CONVENIENCE
Lift predictive call with Occupants sensor data
Lifts, Appliances, Occupant activity and presence
Appliances automated and self-learning (user habits) On-Off
Other process request from the user Legend: [EI] = different device for each Installation, [ER] = different device for each Room
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6.2. Central Unit functionalities and Users interfaces
The central unit can be considered the building brain. All the data received are elaborated through complex algorithms, widely listed in the previous tables where they are categorized like Artificial Intelligence process. The results of these proces-ses are converted into commands for the building actuators.
Machine learning process uses the data collected and saved in the cloud to elaborate predictive algo-rithms. The “Building History Data” from the cloud collect all the information about the building during its life-cycle.
In order to better explain the process two examples are explained.
In a first case, the “External environment sensors”
with the “Weather forecast data” expect a rainfall, the C.U. elaborate the algorithm to regulate the en-velope. Windows and shading will be accommoda-ted through their actuators and consequently, the lighting system will be regulated according to the light variation, the same for the HVAC systems that will change regulation according to the change of temperature and air quality data already foreseen following the envelope adjustment. This second part will be activated only according to the occu-pant, his presence (which room and when) measu-red through “presence sensors” and the ongoing or planned/predicted activities through “activity sensors” with the relatives cloud data. In the same time, the “rainwater collector actuator” activate the device, the C.U. it’s also ready to activate the buil-ding functions that were waiting for its water. Due to rain, the possibility of irrigation of the planned garden is automatically cancelled.
A second scenario: a user suddenly leaves his smart apartment. The “Coming home-living home fun-ctions/ Access detector” recognize it. The lift is automatically called to be ready in the right floor, the television and the lights that the user left on it’s automatically switched off and the security system activated. The “Self-regulating thermostat” will change modes, and the building envelope according to the “external environment station” will be regu-lated to guarantee the best IAQ condition when he will be back.
Ai
User preferences
& REQUEST User personal
DATA Building HISTORY
DATA
Building live STATUS ADVICES for the
USER
OUTPUT INPUT
Cloud
Fig.08 Central system functionalities
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The Cloud data are also available to the user that through the “User Interface” receive all the building information.
The “User Interface” allows the occupant also to intervene in the building management process. He can modify the C.U. decisions adapting it to his
pre-ferences and needs.
In every case, the Ai will advise him the best solu-tion from an efficiency point of view that considers also his comfort. The Ai analyzes the User interven-tions in order to accord its command with his wills for future decisions.