### Prior Research on Performance Evaluation of Energy Saving  
Several scholars have attempted to find effective ways to tackle energy saving and conduct a performance evaluation of various appliances for office and residential buildings. For example, one study [50] adopted advanced audio processing techniques to reduce the impacts of ambient noise. This experiment demonstrated that the proposed audio processing with the background noise cancellation algorithm improved the accuracy of room utilization estimates by approximately 11-12%, resulting in average ventilation power reduction of 3.54% compared to the absence of background noise cancellation. This proposed audio processing technique is likely to achieve a non-intrusive, cost-effective, robust and accurate solution for building occupancy estimates. Additionally, a study [51] deployed the design and implementation of low-cost, wireless, and incremental sensor systems. This pilot project was able to (1) identify significant opportunities for energy savings due to idle intervals, (2) show an estimated battery lifetime of more than 5 years while accurately detecting occupancy, and (3) show that this system can potentially save energy from 10% to 15%. Furthermore, a study [52] reviewed commonly available systems used in commercial office buildings for occupancy detection and control applications driven by demand and experimental results from evaluating the effectiveness of indoor chair sensors. This study provided detailed access information for demand-driven control applications. Furthermore, a study [53] used WinOSS in a 1500 m\({}^{2}\) built environment for four weeks to determine its efficacy. WinOSS was chosen because it can provide detailed access information by leveraging the existing commodity WiFi infrastructure with WiFi-enabled mobile devices operated by occupants to outperform existing access detection techniques. Extensive results showed that WinOSS could provide detailed ownership information (including possession detection, counting and tracking) in an accurate, reliable, cost-effective and non-intrusive approach. Lastly, a study [54] proposed an access monitoring system built on non-intrusive sensors capable of detecting indoor temperature, humidity, CO\({}_{2}\) concentration, door status, light, sound and movement. The efficiency of each sensor in the occupancy estimate was assessed. The sensor data is communicated wirelessly and real-time processing using a back-propagation (BP) artificial neural network (ANN) algorithm. For fifteen consecutive days, the test results reported an overall detection rate of over 90%, indicating the proposed system's ability to monitor real-time multi-room access data to support demand-drivenHVAC operations. These prior studies have proposed performance evaluation for energy efficiency and cost-effectiveness in office and residential buildings. Collectively, smart technologies, models, and approaches have been studied extensively. Despite their energy efficiency and cost-effectiveness, few studies have paid attention to existing electrical appliances. Currently, little is known about how to improve these appliances for better energy efficiency and cost-effectiveness management. It has been observed by numerous electrical engineering experts, like [45] and two of the experts in this study, that the sizes of the existing electrical appliances that have been currently installed in condominiums in cities like Bangkok, are too large for the levels of energy usage and, as a result, the operation of the appliances appears to be significantly lower than their optimal capacity. It is estimated that downsizing the currently installed and used electrical appliances can help condominiums achieve energy efficiency and cost effectiveness management. However, the estimation has never been investigated and this was a research gap that needed to be further investigated.