During the seminar Smart Buildings, the students simulated smart scenarios in the AIPL building with Raspberry Pis, Fhem servers, and the FS20 protocol. This allowed students to install and configure automatic control devices such as motion sensors, (dimming) light switches, a window sensor, a RGB display, a heating sensor, as well as a remote control display.
PLATFORM 1 : Smart Housing Controlling
Scenario 1. In the first scenario, the security staff of the AIPL building was notified about the statuses or windows in a room, and about the presence or absence or people shortly before closing time. This was done using a motion sensor and a window sensor that communicated the statuses to an RGB Display. Furthermore, two motion sensors in each corner of the room allowed the automatic light control inside and would dime the light (50% 25%) if no movement was detected for a certain period of time.
Scenario 2. The second scenario allowed motion controlled lighting in the hallways and timetable-dependant lighting inside the classrooms, also taking holidays into consideration. A remote control display was used to enable timetable- and motion-independent lighting.
Scenario 3. The last scenario focused on the heating inside the classrooms and enabled preheating before the beginning of classes as well as keeping the temperature stable, regarding the room’s conditions such as the statuses of the windows and the present temperature.
PLATFORM 2: Smart system for building security
Scenario 1. The objective of this scenario is to help the Security Man to know which window is open and if there is still someone inside the building. The motion sensor, window sensor and dimmer actuator are installed on student rooms. Then RGB Display is installed in security man office and it will display messages continuously to notify the security man regarding the condition of the room:
(2) if there is an opened window in the room, the RGB display that window is opened. This scenario applies during non-office hour when the building is about to be closed which is from 18.45 – 19.00. Thus, RGB Display is only active during this period of time and inactive during the rest of the day.
Scenario 2. Another scenario that the students made is to improve efficient use of electricity (use only when is needed) by using the light dimmer. The scenario applies during office hour, from 7.00 to 19.00. Install 2 motion sensors in each corner of the room to detect the movement of people inside the room. If the motion sensor detects a movement, it notifies the FHEM server to signal the dimmer to turn on the light bulbs. Otherwise, the light bulb is OFF. Thus the lights will be on only on the side of the room where the people are, and the lights on the other side of the room are still off. After the light is turned on, it will start to count back for 5 minutes. During this 5 minutes time frame, if the motion sensor detects nothing, the light bulb will start dimming slowly from 100% to 75% to 25% and finally go off. However, if the motion sensor detects a movement during this 5 minutes time frame, the counter will be reset and the light bulbs are still on. The logic of the scenarios is explained below.
PLATFORM 3: Intelligent Classroom
Scenario 1: Lightings are switch on two minutes before class lectures and heating radiators are switch on 30 minutes to preheat the classroom before lectures begin. Also motion sensor detection is enabled to notify the FHEM server to automatically switch on lightings and heating radiators at non lecture hours or during Lunch breaks. This sensor notification mode is switch off during lecture periods to avoid conflict with specified operation commands enabled during lecture periods.
Scenario 2: Also the students implemented is an automatic control of the heating radiator on occurrence of specified events. When class windows are opened, heating radiators are automatically turned off. Also when temperature beyond habitable condition (25oC) is reached the heating radiator is automatically turned off to maintain the comfort of the room occupants. Holiday mode was also configures which turns off the heating radiator during non-working hours of the university.
The scenario is very significant for energy saving because it was able to save 62.34% of normal daily energy consumption. This in its totality justifies why ICT can help optimizing energy consumption in homes as specified by the GeSI report. Also it satisfies the economic, ethical, and environmental conditions of sustainability.