Usability perceptions and beliefs about smart thermostats by chi-square test, signal detection theory, and fuzzy detection theory in regions of Mexico

The lights are on, but no one’s home: A performance test to measure digital skills to use IoT home automation

“…Users of smart thermostats, for example, do not fully use the thermostats' potential because they are unable to set up and use advanced functions such as the automatic adjustment of energy consumption patterns (e.g. through GPS or motion sensors) (Ponce et al, 2019). In contrast, underdeveloped skills could lead to increased energy consumption due to inappropriate application of prewarming rooms or simply due to the inefficient adoption of energy-consuming smart home devices (Hargreaves et al, 2018).…”

Tailored gamification and serious game framework based on fuzzy logic for saving energy in connected thermostats

“…As proposed in (Ponce et al, 2018a), signal detection theory (SDT) and fuzzy detection theory (FDT) are used to determine whether the output values are related to the input values introduced to the system. Therefore, it is proposed to develop an experimental study by surveying 50 participants to understand which elements of gamification and SG lead them to get engaged and improve their energy usage, attitude, and knowledge.…”

“…The fundamental goal of an HVAC control system is to keep temperature and air quality within a comfortable range while minimizing energy usage (Soltanaghaei and Whitehouse, 2018). In (Ponce et al, 2018a), a connected thermostat (CT) is defined as an electrical device that links smart homes with smart grids. CTs are thus designed to automatically learn occupants' schedules and turn heating and cooling on or off on the users' behalf (Soltanaghaei and Whitehouse, 2018).…”

“…However, because end-users operate them differently than intended by the manufacturers and designers, they produce major energy waste (Pritoni et al, 2015); (2) Although CTs can automatically adjust the patterns of electrical consumption to save energy, end users do not use these functions. As a result, the users expect features that decrease the complexity of operating the product and do not feel confident in using the functions; (3) End users are unable to accurately understand the features and advantages of the CTs because they do not know what to expect of these devices; (4) Customers should receive accurate and complete information regarding the relationship between kWh and CO 2 so that they can understand the environmental impact of incorrect operation of a CT (Ponce et al, 2018a); (5) The device is designed only for meeting certain types of expectations, it means that those devices are generally designed for the typical user rather than non-typical user; thus it cannot be entirely or quickly adopted because some end users do not consider saving energy to be their main expectation. Their primary expectation is what they look for when buying an air conditioning system: cost, energy efficiency, performance, durability, reliability, brand, greenness, and aesthetics; (6) If customers do not use an HVAC correctly, then the human-machine interface (HMI) will be unable to support the CT in improving the customers' understanding of energy efficiency (Ponce et al, 2018b(Ponce et al, , 2017.…”

Towards human-computer interaction on smart metering systems

“…Finally, in Mexico, there is a lack of related work in SMS fields, the works are related to other technical aspect such as communications [8] or focused in other electrical appliances like smart thermostats [19]. In this way, it is very crucial a formal study of SMS with HCI to improve the user acceptance of this new devices in Mexico electrical prosumers.…”