## 4 Conclusions  
This work is the result of finding a solution for building smart classrooms in university campuses. Studies related to smart classroom are reviewed and important factors, in terms of technology and education for smart classrooms were found in some of the studies we have reviewed. However, a campus-wide smart classroom construction solution cannot be found. Therefore, we design and propose our own smart classroom architecture for building and maintaining smart classrooms at the university campus in this work. In Section 1, the concept of the smart campus is discussed and the works related to smart campus definitions, such as References [1; 2; 3; 4; 5; 6], are reviewed. In the subsection of background and related works, the relationship between learning and environment factors are discussed in References [8; 9; 10; 11; 12; 13; 15; 16], including seating arrangement, and environmental factors, such as CO\({}_{2}\) levels and temperature, which are related to teaching and learning quality. Previous works related to smart classroom technology issues were also reviewed, and models and architectures to address particular technical issues were proposed or discussed in Reference [18; 19; 20; 21; 22; 23]. Some technology related features important to smart classrooms are discussed in Reference [24; 25; 26; 27; 28; 29; 30; 31]. Studies related to solving technical issues or to use technology to improve classroom activities, such as Reference [32; 33; 34; 35], were also reviewed. References of the technologies used in this work, such as Raspberry Pi, Python, Flask, PHP, MariaDB,  
Figure 18: A campus-wide view of the smart classrooms based on the proposed architecture. RFID, RS232, and RS485 can be found in References [7; 37; 38; 48; 49; 50; 52; 53; 54], and recent works related to Flask, such as References [39; 40; 41; 42; 43; 44; 45; 46; 47], were also reviewed. In Reference [36], PI-SCLE was proposed for understanding students' preferences toward the smart classroom. Important factors of smart classrooms can also be found in Reference [36]. Some studies related to context-aware and smart classroom were also reviewed, such as References [55; 56; 57]. Works related to energy efficiency and energy saving issues, such as Reference [58; 59; 60; 61; 62; 63; 64; 65; 66; 67; 68; 69], were reviewed. In Reference [71; 72; 73; 74; 75; 76; 77; 78], topics such as IoT, Fog, and Cloud computing, which are important to this study, were discussed. At the end of Section 1--Section 1.1.6--recent works related to platforms and frameworks for smart campuses, such as References [79; 80; 81; 82; 83; 84], were also ereviewed. Although a suitable solution for building smart classrooms in university campuss was not found in previous studies, important features related to smart classrooms, context awareness, and energy savings discussed in the previous works are still significant for designing our proposed architecture. The contribution of this work is that the proposed architecture is based on our study and MCU Smart Classroom project. The architecture consists of a smart classroom prototype, a technology integration model, and supporting measures for smart classroom operation. The smart classroom prototype includes import classroom features based on the reviewed studies. The technology integration model is novel and is suitable for massively constructing smart classrooms in university campuses. As a result, the way of implementing the proposed architecture is detailed, illustrated and explained with examples. Raspberry Pi was used as a key role in the proposed technology integration model. The demonstration shows that Raspberry Pi is suitable for building context-aware energy saving application for smart campus. Although a feasible architecture was proposed in this work with examples for implantation, mechanisms such as authentication and authorization were not defined in this architecture. Details for data exchange in smart classroom application layers were not defined either.