## 1 Introduction
### Background and Related Works
#### 1.1.3 Context-Aware and Energy Saving Related Studies
The platform was developed based on a commercial supervisory control and data acquisition (SCADA) system from Siemens. The SCADA system used in Reference [64] can integrate different technologies in modern buildings. A predictive controller and a communication channel to the SCADA system are implemented. Simulation and experimental result shows that the proposed platform optimizes the satisfaction of user explicit preferences, subjected to the constraints of energy waste minimization. In Reference [65], a scheduling technique is proposed to manage electrical activities in a smart home, which has controllable home appliances, storage devices, and energy generators, for minimizing energy cost. Energy is produced from renewable and dispatchable sources. The simulation result shows that the proposed approach in Reference [65] can exploit the local energy generation and storage. Therefore, energy consumption costs can be reduced while complying with customer energy needs. In Reference [66], the energy efficiency of cyclic downtime control methods were evaluated, and authors state that the best energy-saving efficiency was achieved by the mode of cycling turning air conditioning units on for 15 min and off for 5 min. In Reference [67], a field survey for energy consumption in university building was conducted in Korea. Factors including space usage, construction year, orientation, shape factor, window area, shading devices, heating equipment, cooling equipment, and lighting system were used as parameters to analyze potential energy consumption characteristics of different buildings. Automatic standby power cutoff switches, reduction of power for lightings, adjustment of indoor air temperature are selected as energy-saving strategies in Reference [67]. In Reference [67], the authors use automatic standby power cutoff switches to reduce 10% plug load in energy-guzzling buildings. Authors also suggest that changing occupants' behavior can reduce building energy usage. In Reference [68], the authors state that the major electricity used in the educational buildings was the lighting system, which consumes almost 42% of total energy. In Reference [69], authors also state that light in classrooms is a significant portion of the energy consumption is post-secondary education institutes. To discover the most common patterns in lighting waste, a methodology based on data mining was proposed in Reference [69], the result shows that the lights were turned on with no one in the monitored classroom for 10.6 h in an average day. The authors of Reference [69] mentioned that occupancy-based lighting control systems, which are based on turning the lights off when a state of no occupancy is detected in the monitored space,which is effective for reducing lighting energy waste. However, when the class schedule is dynamically changing, the energy saving rules predefined based on a fixed schedule is no longer useful. As a summary, lots of energy has been wasted in classrooms and energy waste in classrooms can be greatly improved by correctly turning off unnecessary devices. Therefore, ways to save energy in smart classroom are also included in the proposed architecture.