# Intelligent Thermal Comfort Controlling System for Buildings Based on IoT and AI
## 6 Conclusions and Future Work  
Among the methods for building energy prediction based on artificial intelligence technology, each algorithm has advantages and disadvantages. How to choose a specific intelligent algorithm for different needs becomes important. This paper analyzes different model prediction methods and proposes a combined algorithm for real-time analysis of short-term energy consumption prediction, which reflects the importance of fast prediction. Fast and effective analysis of building energy consumption is achieved through feedback correction of predicted values. It is helpful for the occupants of the building to make adjustments based on the feedback in a timely manner and has certain theoretical guiding significance and practical application value. Although the method in this paper only performs data collection and analysis for a single room, in practical applications, it can be arranged to multiple rooms, multiple floors, and even individual buildings. The method has high scalability. The experimental method covers systems including heating and air conditioning equipment, as well as independent ventilation equipment. However, this methodology of this research still has some limitations. In the data verification part, some untested samples were selected for verification. From the results, there is a certain error (about 3%) between the expected value and the actual value, which may be caused by two reasons. * The accuracy of the BP algorithm still needs to be improved. This is limited by computer hardware conditions. At present, it is impossible to achieve infinite precision to achieve extreme accuracy. * In the current case study, it concerns more about the influence of the temperature for thermal comfort, while the influence of air velocity was neglected. The air velocity could become an important variable for assessing thermal comfort. Relatively, the complexity of the monitoring system will be greatly increased. * The experimental site cannot be strict and accurate. Due to the hardware problems of the sensors and controllers, errors may occur when recording and storing data. In the future, the research direction of intelligent thermal comfort control systems for buildings based on the Internet of Things will gradually increase with the development of computer hardware. This will make the prediction model more accurate so that the predicted value is closer to the actual value. Moreover, the current system is researched on thermal comfort considerations by using computational methods. Besides the virtual experiments in a lab environment, however, it's highly demanding to apply with related research with multi-objective simulations, for instance, the facades, construction process. [PERSON] et al. presented the study on a special system with a sandwich design made of glass fibre-reinforced polymer (GFRP) purltruded profiles. Their novel design concept has up to over 10% and 15% respectively improvement on thermal and structural performances compared to traditional non-integrated systems [32]. Combining with actual building projects is the best practice direction of the system. [PERSON] et al. collected some recent examples and design concepts of adaptive systems with classification for structural assessment and adaptive facades of buildings [33]. No matter indoor or exterior system, the most fundamental aim is to predict or control building energy consumption in reasonable and efficient methods. In future research, the proposed framework and system for detecting the indoor environmental variables related to this research will introduce more variables based on the various types of algorithms. More hardware will also be applied to the controllers. Therefore, it can be applied to different rooms or different areas of the same space, as each area has an internal adjustment terminal. Further extended investigations are required to exploit and optimize the potential of the system. In this paper, [PERSON], [PERSON] and [PERSON] conceived the idea.