Low carbon policies, including those aimed at increasing water efficiency, have been adopted as a crucial strategy for combating global warming and climate change. The green building evaluation system used in Taiwan was first applied in 1999 and initially utilized a building's water efficiency as the threshold index for determining the building's environmental impact. Since 1999, more than a thousand buildings have been certified as green buildings using this evaluation system. The quantitative effects of water conservation efforts should be provided to policy makers as a form of positive feedback. To that end, the present study offers a calculation process for estimating the quantitative volume of water saved by practical green buildings. The baseline water usage for all kinds of buildings was determined to serve as the criterion for determining the water-saving efficiency of individual buildings. An investigation of the average water-saving rate from 2000 to 2013 for 1320 buildings certified as green buildings was also conducted to validate the estimation results and found that these green buildings saved an average of approximately 37.6% compared to the baseline water usage rate for all buildings. Water savings will inevitably follow from the use of water-saving appliances or water-saving designs for buildings. The proposed calculation process can be used to clarify the relationships between specific water-saving concepts and the real water usage efficiency of green buildings.

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Today's world places increasing emphasis on comfort within living spaces. The growth in awareness of energy conservation and environmental preservation has gradually contributed to the widespread use of smart home control systems. In this study, data related to human comfort conditions were compiled, and the control of smart devices in home environments was explored. Specifically, information communication technology and the Internet of Things (IoT) were combined to create a smart control system that creates a comfortable, energy-conserving home environment through the concurrent monitoring of both indoor and outdoor environmental data. If the outdoor indicators are ideal (denoting a comfortable environment) but the indoor indicators are not ideal (denoting an uncomfortable environment), the system opens a window to allow the incorporation of favorable outdoor environmental factors into the indoor environment. When the outdoor environment is uncomfortable, the window is closed to prevent the infiltration of unfavorable outdoor environmental factors. When the indoor indicators are nonideal, various types of equipment are activated according to the detection values. For example, when the humidity level is overly high, the dehumidifier is turned on. When the concentration of particulate matter with a diameter of < 2.5 µm is overly high, the air purifier is turned on. When the temperature is too high or low, the air conditioner is turned on, and when the CO 2 concentration is too high, the fan is turned on for ventilation. The values detected by each sensor and the operating conditions of each device are also displayed on the screen for the reference of the user, who can adjust the threshold values to their preferences.

The COVID-19 pandemic broke out in early 2020, and the infection rate of COVID-19 variants is considerably higher than that of the original virus. The pandemic is still spreading globally. In June 2021, two families living on different floors of a building in Fongshan, Kaohsiung, were simultaneously infected with COVID-19. Investigation results suggested that an elevator in buildings was the most likely place where the virus transmission occurred. Building elevators are a necessary vertical transportation facility for residents or workers in high-rise buildings, and people touch elevator buttons while operating elevators. When a passenger carrying the virus touches elevator buttons, subsequent passengers may be easily infected if they touch those buttons and then touch their mouth, eyes, or nose by accident before sanitizing or washing their hands. In this study, we developed a contact-free elevator ride system by applying smart speech recognition, contact-free perceptual buttons, gesture recognition sensors, and a web page browser activated by quick response codes to operate an elevator. This system reduces the risk of virus infection caused by contact during an elevator ride, effectively enhancing pandemic prevention and protecting people’s health.

In recent years, smart speakers have been widely used to control related smart home appliances. For people with speech disabilities, smart speakers cannot be used to perform related voice control tasks. To help people with speech difficulties and effectively control related smart facilities, we use the Internet of Things to develop a smart home gesture-based control system. The prototype of the system is established by means of sensors and a control panel system. When a sensor detects a control gesture command, it can send related control signals to a controlled smart device. The controlled devices used in this study include smart home appliances such as doors and windows, air conditioners, curtains, dehumidifiers, and air purifiers. The system functions include the opening/closing of doors, windows, and curtains; the activation/ deactivation of heating and cooling systems, dehumidifiers, and air purifiers; temperature and humidity adjustment; and fan operation. With the development of this system, it is possible for people with language disabilities and elderly people to control the operation of various smart devices with gestures. It can also solve the inconvenience of needing to look for remote controls for various facilities. Moreover, it can save precious time and provide a safe, convenient, and smart home living environment for people with speech disabilities.