The Experts below are selected from a list of 38784 Experts worldwide ranked by ideXlab platform
Arturo Molina - One of the best experts on this subject based on the ideXlab platform.
-
tailored gamification and serious game framework based on fuzzy logic for saving energy in connected Thermostats
Journal of Cleaner Production, 2020Co-Authors: Pedro Ponce, Alan Meier, Therese Peffer, Juana Isabel Mendez, Arturo Molina, Omar MataAbstract:Abstract Connected Thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers’ expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their Thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes.
-
s 4 product design framework a gamification strategy based on type 1 and 2 fuzzy logic
International Conference on Software Maintenance, 2019Co-Authors: Juana Isabel Mendez, Alan Meier, Therese Peffer, Pedro Ponce, Omar Mata, Arturo MolinaAbstract:Connected Thermostats control the HVAC in buildings by adjusting the setpoint temperatures without losing the comfort temperature. These devices consider end user profiles, preferences, and schedules to reduce electrical energy consumption. However, users are reluctant to use connected Thermostats due to behavior and usability problems with the interfaces or the product. Typically, users do not use connected Thermostats correctly, which can lead to increased rather than decreased electrical consumption. Thus, the S4 product concept is emerging as a strategy and framework to design functional prototypes to provide user-friendly sensing, smart, sustainable, and social features. An S4 product enables communication between products and between products and end users. Such communication can provide better understanding of the type of consumer who uses the product. Gamification and serious games are emerging as a strategy to shape human behavior to achieve goals; however, such strategies are not applied to product design. Fuzzy logic can be applied to human reasoning and has been used in intelligent systems based on if-then rules. Nevertheless, to the best of our knowledge, applying a gamification strategy based on fuzzy logic to develop an S4 connected thermostat has not been studied previously. Therefore, a framework that integrates gamification and serious games elements using fuzzy logic is proposed to develop a tailored gamification human machine interface. Thus, the proposed framework could tackle the behavior and usability problems of connected Thermostats to teach, engage, and motivate end users to become energy aware, thereby reducing electrical consumption.
-
framework for evaluating usability problems a case study low cost interfaces for Thermostats
International Journal on Interactive Design and Manufacturing (ijidem), 2018Co-Authors: Pedro Ponce, Therese Peffer, Arturo MolinaAbstract:When an evaluation for detecting usability problems is conducted in low-cost thermostat interfaces, several usability problems can show up in one evaluation, and sometimes results are difficult to interpret to correct those problems. If an expert is not implementing, evaluating, and analyzing the test, part of the information could be lost. In addition, designers of interfaces need support in order to provide the most important usability problems. On the other hand, it is important that consumers of low-cost thermostat interfaces use the interface in a correct manner to save energy and time when they are installing and programming the thermostat. Therefore, the usability problems must be eliminated in interfaces before the consumer uses the interface. Thus, the critical usability problems, which drive Thermostats to a catastrophe usability problem in the interfaces, have to be found and solved during the design stage to get a successful interface design in the early stages. This paper presents a framework based on information from experts and consumers to solve usability problems. Moreover, it gives a structure and guidelines for designing and evaluating thermostat interfaces. This proposal assumes that it is possible to use information from experts and consumers for detecting and solving usability problems. The framework includes information from experts who rank the usability problems, and then this information is used to design the time on task and success rate evaluations for end users during the design process.
-
deep learning for automatic usability evaluations based on images a case study of the usability heuristics of Thermostats
Energy and Buildings, 2017Co-Authors: Pedro Ponce, Therese Peffer, David Balderas, Arturo MolinaAbstract:Abstract Thermostats are designed for increasing requirements on indoor thermal comfort. Nevertheless, they are critical devices for saving energy in buildings and households. However, when Thermostats do not accomplish the usability requirements, the end-users do not save energy. Then, when a thermostat is designed or validated, one of the leading problems that must be tackled is the usability evaluation. Generally, the evaluation is based on usability heuristics that are done by experts and designers and involve a very complicated cycling process in which usability experts need to be included in the complete usability evaluation. On the other hand, there are several proposals for generating an automatic usability analysis that can be used by designers or end-users. However, they are limited by the methodologies that are implemented in the evaluation because usability evaluations necessitate a large amount of data abstraction, and the amount of processed information is enormous; As an alternative, Artificial Intelligence can help to solve this problem, especially machine learning techniques with deep learning capabilities that can reach a high level of data abstraction with a significant amount of information and implement an automatic usability evaluation based on images. Convolutional networks that are included in deep learning can classify complex problems, attain highly accurate results. This paper proposes to train a convolutional network with standard usability heuristics for evaluating usability, which is an easy method for evaluating usability in Thermostats, based on images. The proposed automatic method gives excellent results for evaluating usability heuristics in the heuristic assigned. This paper provides a complete methodology, using deep learning, for automatically evaluating the usability heuristics of Thermostats.
-
framework for communicating with consumers using an expectation interface in smart Thermostats
Energy and Buildings, 2017Co-Authors: Pedro Ponce, Therese Peffer, Arturo MolinaAbstract:Abstract One of the main problems for adopting smart Thermostats is consumers’ expectations about smart Thermostats. Generally, the interfaces in smart Thermostats and smart devices in the energy market are designed without consideration for the expectations of the customers or are not adjusting their operation according to the consumers’ expectations and behavior. Moreover, the business model does not consider one part of the product as the main link between customers and value propositions. This study shows a structure for creating a smart interface based on consumers’ expectations and shows an extension of the CANVAS business model. Furthermore, the paper re-defines the term “smart” in electric devices as the ability to adjust the system in order to reach the expectations of the consumer and to save energy. This term is not only defined in terms of saving energy but also it includes the customer’s expectations. If the system is only smart to control the temperature and save energy, the customer’s expectations may not always be achieved; thus, the smart devices are not successfully adopted in households. The design is based on artificial neural networks and a fuzzy logic controller to achieve the consumer’s expectations. The results show the interface operation on each block. The classification systems have to operate to detect changes in the customer’s market segment. The fuzzy logic controller tries to reach the customer’s expectations in order to move the customer into the energy saving market. This expectation interface tries to motivate designers to focus on consumer’s expectations for smart devices in the energy market. Not only are the energy requirements important to design a smart thermostat, but also the consumer’s expectations to create a successful smart thermostat in the electric market. Smart Thermostats can reduce the consumption of electrical energy, but they need to be accepted. This interface provides an effective manner to connect the consumer’s expectations with the consumption of energy. This papers shows a proof of concept about intelligent interfaces.
Therese Peffer - One of the best experts on this subject based on the ideXlab platform.
-
tailored gamification and serious game framework based on fuzzy logic for saving energy in connected Thermostats
Journal of Cleaner Production, 2020Co-Authors: Pedro Ponce, Alan Meier, Therese Peffer, Juana Isabel Mendez, Arturo Molina, Omar MataAbstract:Abstract Connected Thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers’ expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their Thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes.
-
s 4 product design framework a gamification strategy based on type 1 and 2 fuzzy logic
International Conference on Software Maintenance, 2019Co-Authors: Juana Isabel Mendez, Alan Meier, Therese Peffer, Pedro Ponce, Omar Mata, Arturo MolinaAbstract:Connected Thermostats control the HVAC in buildings by adjusting the setpoint temperatures without losing the comfort temperature. These devices consider end user profiles, preferences, and schedules to reduce electrical energy consumption. However, users are reluctant to use connected Thermostats due to behavior and usability problems with the interfaces or the product. Typically, users do not use connected Thermostats correctly, which can lead to increased rather than decreased electrical consumption. Thus, the S4 product concept is emerging as a strategy and framework to design functional prototypes to provide user-friendly sensing, smart, sustainable, and social features. An S4 product enables communication between products and between products and end users. Such communication can provide better understanding of the type of consumer who uses the product. Gamification and serious games are emerging as a strategy to shape human behavior to achieve goals; however, such strategies are not applied to product design. Fuzzy logic can be applied to human reasoning and has been used in intelligent systems based on if-then rules. Nevertheless, to the best of our knowledge, applying a gamification strategy based on fuzzy logic to develop an S4 connected thermostat has not been studied previously. Therefore, a framework that integrates gamification and serious games elements using fuzzy logic is proposed to develop a tailored gamification human machine interface. Thus, the proposed framework could tackle the behavior and usability problems of connected Thermostats to teach, engage, and motivate end users to become energy aware, thereby reducing electrical consumption.
-
framework for evaluating usability problems a case study low cost interfaces for Thermostats
International Journal on Interactive Design and Manufacturing (ijidem), 2018Co-Authors: Pedro Ponce, Therese Peffer, Arturo MolinaAbstract:When an evaluation for detecting usability problems is conducted in low-cost thermostat interfaces, several usability problems can show up in one evaluation, and sometimes results are difficult to interpret to correct those problems. If an expert is not implementing, evaluating, and analyzing the test, part of the information could be lost. In addition, designers of interfaces need support in order to provide the most important usability problems. On the other hand, it is important that consumers of low-cost thermostat interfaces use the interface in a correct manner to save energy and time when they are installing and programming the thermostat. Therefore, the usability problems must be eliminated in interfaces before the consumer uses the interface. Thus, the critical usability problems, which drive Thermostats to a catastrophe usability problem in the interfaces, have to be found and solved during the design stage to get a successful interface design in the early stages. This paper presents a framework based on information from experts and consumers to solve usability problems. Moreover, it gives a structure and guidelines for designing and evaluating thermostat interfaces. This proposal assumes that it is possible to use information from experts and consumers for detecting and solving usability problems. The framework includes information from experts who rank the usability problems, and then this information is used to design the time on task and success rate evaluations for end users during the design process.
-
deep learning for automatic usability evaluations based on images a case study of the usability heuristics of Thermostats
Energy and Buildings, 2017Co-Authors: Pedro Ponce, Therese Peffer, David Balderas, Arturo MolinaAbstract:Abstract Thermostats are designed for increasing requirements on indoor thermal comfort. Nevertheless, they are critical devices for saving energy in buildings and households. However, when Thermostats do not accomplish the usability requirements, the end-users do not save energy. Then, when a thermostat is designed or validated, one of the leading problems that must be tackled is the usability evaluation. Generally, the evaluation is based on usability heuristics that are done by experts and designers and involve a very complicated cycling process in which usability experts need to be included in the complete usability evaluation. On the other hand, there are several proposals for generating an automatic usability analysis that can be used by designers or end-users. However, they are limited by the methodologies that are implemented in the evaluation because usability evaluations necessitate a large amount of data abstraction, and the amount of processed information is enormous; As an alternative, Artificial Intelligence can help to solve this problem, especially machine learning techniques with deep learning capabilities that can reach a high level of data abstraction with a significant amount of information and implement an automatic usability evaluation based on images. Convolutional networks that are included in deep learning can classify complex problems, attain highly accurate results. This paper proposes to train a convolutional network with standard usability heuristics for evaluating usability, which is an easy method for evaluating usability in Thermostats, based on images. The proposed automatic method gives excellent results for evaluating usability heuristics in the heuristic assigned. This paper provides a complete methodology, using deep learning, for automatically evaluating the usability heuristics of Thermostats.
-
framework for communicating with consumers using an expectation interface in smart Thermostats
Energy and Buildings, 2017Co-Authors: Pedro Ponce, Therese Peffer, Arturo MolinaAbstract:Abstract One of the main problems for adopting smart Thermostats is consumers’ expectations about smart Thermostats. Generally, the interfaces in smart Thermostats and smart devices in the energy market are designed without consideration for the expectations of the customers or are not adjusting their operation according to the consumers’ expectations and behavior. Moreover, the business model does not consider one part of the product as the main link between customers and value propositions. This study shows a structure for creating a smart interface based on consumers’ expectations and shows an extension of the CANVAS business model. Furthermore, the paper re-defines the term “smart” in electric devices as the ability to adjust the system in order to reach the expectations of the consumer and to save energy. This term is not only defined in terms of saving energy but also it includes the customer’s expectations. If the system is only smart to control the temperature and save energy, the customer’s expectations may not always be achieved; thus, the smart devices are not successfully adopted in households. The design is based on artificial neural networks and a fuzzy logic controller to achieve the consumer’s expectations. The results show the interface operation on each block. The classification systems have to operate to detect changes in the customer’s market segment. The fuzzy logic controller tries to reach the customer’s expectations in order to move the customer into the energy saving market. This expectation interface tries to motivate designers to focus on consumer’s expectations for smart devices in the energy market. Not only are the energy requirements important to design a smart thermostat, but also the consumer’s expectations to create a successful smart thermostat in the electric market. Smart Thermostats can reduce the consumption of electrical energy, but they need to be accepted. This interface provides an effective manner to connect the consumer’s expectations with the consumption of energy. This papers shows a proof of concept about intelligent interfaces.
Pedro Ponce - One of the best experts on this subject based on the ideXlab platform.
-
tailored gamification and serious game framework based on fuzzy logic for saving energy in connected Thermostats
Journal of Cleaner Production, 2020Co-Authors: Pedro Ponce, Alan Meier, Therese Peffer, Juana Isabel Mendez, Arturo Molina, Omar MataAbstract:Abstract Connected Thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers’ expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their Thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes.
-
s 4 product design framework a gamification strategy based on type 1 and 2 fuzzy logic
International Conference on Software Maintenance, 2019Co-Authors: Juana Isabel Mendez, Alan Meier, Therese Peffer, Pedro Ponce, Omar Mata, Arturo MolinaAbstract:Connected Thermostats control the HVAC in buildings by adjusting the setpoint temperatures without losing the comfort temperature. These devices consider end user profiles, preferences, and schedules to reduce electrical energy consumption. However, users are reluctant to use connected Thermostats due to behavior and usability problems with the interfaces or the product. Typically, users do not use connected Thermostats correctly, which can lead to increased rather than decreased electrical consumption. Thus, the S4 product concept is emerging as a strategy and framework to design functional prototypes to provide user-friendly sensing, smart, sustainable, and social features. An S4 product enables communication between products and between products and end users. Such communication can provide better understanding of the type of consumer who uses the product. Gamification and serious games are emerging as a strategy to shape human behavior to achieve goals; however, such strategies are not applied to product design. Fuzzy logic can be applied to human reasoning and has been used in intelligent systems based on if-then rules. Nevertheless, to the best of our knowledge, applying a gamification strategy based on fuzzy logic to develop an S4 connected thermostat has not been studied previously. Therefore, a framework that integrates gamification and serious games elements using fuzzy logic is proposed to develop a tailored gamification human machine interface. Thus, the proposed framework could tackle the behavior and usability problems of connected Thermostats to teach, engage, and motivate end users to become energy aware, thereby reducing electrical consumption.
-
framework for evaluating usability problems a case study low cost interfaces for Thermostats
International Journal on Interactive Design and Manufacturing (ijidem), 2018Co-Authors: Pedro Ponce, Therese Peffer, Arturo MolinaAbstract:When an evaluation for detecting usability problems is conducted in low-cost thermostat interfaces, several usability problems can show up in one evaluation, and sometimes results are difficult to interpret to correct those problems. If an expert is not implementing, evaluating, and analyzing the test, part of the information could be lost. In addition, designers of interfaces need support in order to provide the most important usability problems. On the other hand, it is important that consumers of low-cost thermostat interfaces use the interface in a correct manner to save energy and time when they are installing and programming the thermostat. Therefore, the usability problems must be eliminated in interfaces before the consumer uses the interface. Thus, the critical usability problems, which drive Thermostats to a catastrophe usability problem in the interfaces, have to be found and solved during the design stage to get a successful interface design in the early stages. This paper presents a framework based on information from experts and consumers to solve usability problems. Moreover, it gives a structure and guidelines for designing and evaluating thermostat interfaces. This proposal assumes that it is possible to use information from experts and consumers for detecting and solving usability problems. The framework includes information from experts who rank the usability problems, and then this information is used to design the time on task and success rate evaluations for end users during the design process.
-
deep learning for automatic usability evaluations based on images a case study of the usability heuristics of Thermostats
Energy and Buildings, 2017Co-Authors: Pedro Ponce, Therese Peffer, David Balderas, Arturo MolinaAbstract:Abstract Thermostats are designed for increasing requirements on indoor thermal comfort. Nevertheless, they are critical devices for saving energy in buildings and households. However, when Thermostats do not accomplish the usability requirements, the end-users do not save energy. Then, when a thermostat is designed or validated, one of the leading problems that must be tackled is the usability evaluation. Generally, the evaluation is based on usability heuristics that are done by experts and designers and involve a very complicated cycling process in which usability experts need to be included in the complete usability evaluation. On the other hand, there are several proposals for generating an automatic usability analysis that can be used by designers or end-users. However, they are limited by the methodologies that are implemented in the evaluation because usability evaluations necessitate a large amount of data abstraction, and the amount of processed information is enormous; As an alternative, Artificial Intelligence can help to solve this problem, especially machine learning techniques with deep learning capabilities that can reach a high level of data abstraction with a significant amount of information and implement an automatic usability evaluation based on images. Convolutional networks that are included in deep learning can classify complex problems, attain highly accurate results. This paper proposes to train a convolutional network with standard usability heuristics for evaluating usability, which is an easy method for evaluating usability in Thermostats, based on images. The proposed automatic method gives excellent results for evaluating usability heuristics in the heuristic assigned. This paper provides a complete methodology, using deep learning, for automatically evaluating the usability heuristics of Thermostats.
-
framework for communicating with consumers using an expectation interface in smart Thermostats
Energy and Buildings, 2017Co-Authors: Pedro Ponce, Therese Peffer, Arturo MolinaAbstract:Abstract One of the main problems for adopting smart Thermostats is consumers’ expectations about smart Thermostats. Generally, the interfaces in smart Thermostats and smart devices in the energy market are designed without consideration for the expectations of the customers or are not adjusting their operation according to the consumers’ expectations and behavior. Moreover, the business model does not consider one part of the product as the main link between customers and value propositions. This study shows a structure for creating a smart interface based on consumers’ expectations and shows an extension of the CANVAS business model. Furthermore, the paper re-defines the term “smart” in electric devices as the ability to adjust the system in order to reach the expectations of the consumer and to save energy. This term is not only defined in terms of saving energy but also it includes the customer’s expectations. If the system is only smart to control the temperature and save energy, the customer’s expectations may not always be achieved; thus, the smart devices are not successfully adopted in households. The design is based on artificial neural networks and a fuzzy logic controller to achieve the consumer’s expectations. The results show the interface operation on each block. The classification systems have to operate to detect changes in the customer’s market segment. The fuzzy logic controller tries to reach the customer’s expectations in order to move the customer into the energy saving market. This expectation interface tries to motivate designers to focus on consumer’s expectations for smart devices in the energy market. Not only are the energy requirements important to design a smart thermostat, but also the consumer’s expectations to create a successful smart thermostat in the electric market. Smart Thermostats can reduce the consumption of electrical energy, but they need to be accepted. This interface provides an effective manner to connect the consumer’s expectations with the consumption of energy. This papers shows a proof of concept about intelligent interfaces.
Omar Mata - One of the best experts on this subject based on the ideXlab platform.
-
tailored gamification and serious game framework based on fuzzy logic for saving energy in connected Thermostats
Journal of Cleaner Production, 2020Co-Authors: Pedro Ponce, Alan Meier, Therese Peffer, Juana Isabel Mendez, Arturo Molina, Omar MataAbstract:Abstract Connected Thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers’ expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their Thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes.
-
s 4 product design framework a gamification strategy based on type 1 and 2 fuzzy logic
International Conference on Software Maintenance, 2019Co-Authors: Juana Isabel Mendez, Alan Meier, Therese Peffer, Pedro Ponce, Omar Mata, Arturo MolinaAbstract:Connected Thermostats control the HVAC in buildings by adjusting the setpoint temperatures without losing the comfort temperature. These devices consider end user profiles, preferences, and schedules to reduce electrical energy consumption. However, users are reluctant to use connected Thermostats due to behavior and usability problems with the interfaces or the product. Typically, users do not use connected Thermostats correctly, which can lead to increased rather than decreased electrical consumption. Thus, the S4 product concept is emerging as a strategy and framework to design functional prototypes to provide user-friendly sensing, smart, sustainable, and social features. An S4 product enables communication between products and between products and end users. Such communication can provide better understanding of the type of consumer who uses the product. Gamification and serious games are emerging as a strategy to shape human behavior to achieve goals; however, such strategies are not applied to product design. Fuzzy logic can be applied to human reasoning and has been used in intelligent systems based on if-then rules. Nevertheless, to the best of our knowledge, applying a gamification strategy based on fuzzy logic to develop an S4 connected thermostat has not been studied previously. Therefore, a framework that integrates gamification and serious games elements using fuzzy logic is proposed to develop a tailored gamification human machine interface. Thus, the proposed framework could tackle the behavior and usability problems of connected Thermostats to teach, engage, and motivate end users to become energy aware, thereby reducing electrical consumption.
Alan Meier - One of the best experts on this subject based on the ideXlab platform.
-
tailored gamification and serious game framework based on fuzzy logic for saving energy in connected Thermostats
Journal of Cleaner Production, 2020Co-Authors: Pedro Ponce, Alan Meier, Therese Peffer, Juana Isabel Mendez, Arturo Molina, Omar MataAbstract:Abstract Connected Thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers’ expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their Thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes.
-
s 4 product design framework a gamification strategy based on type 1 and 2 fuzzy logic
International Conference on Software Maintenance, 2019Co-Authors: Juana Isabel Mendez, Alan Meier, Therese Peffer, Pedro Ponce, Omar Mata, Arturo MolinaAbstract:Connected Thermostats control the HVAC in buildings by adjusting the setpoint temperatures without losing the comfort temperature. These devices consider end user profiles, preferences, and schedules to reduce electrical energy consumption. However, users are reluctant to use connected Thermostats due to behavior and usability problems with the interfaces or the product. Typically, users do not use connected Thermostats correctly, which can lead to increased rather than decreased electrical consumption. Thus, the S4 product concept is emerging as a strategy and framework to design functional prototypes to provide user-friendly sensing, smart, sustainable, and social features. An S4 product enables communication between products and between products and end users. Such communication can provide better understanding of the type of consumer who uses the product. Gamification and serious games are emerging as a strategy to shape human behavior to achieve goals; however, such strategies are not applied to product design. Fuzzy logic can be applied to human reasoning and has been used in intelligent systems based on if-then rules. Nevertheless, to the best of our knowledge, applying a gamification strategy based on fuzzy logic to develop an S4 connected thermostat has not been studied previously. Therefore, a framework that integrates gamification and serious games elements using fuzzy logic is proposed to develop a tailored gamification human machine interface. Thus, the proposed framework could tackle the behavior and usability problems of connected Thermostats to teach, engage, and motivate end users to become energy aware, thereby reducing electrical consumption.
-
energy efficiency and the misuse of programmable Thermostats the effectiveness of crowdsourcing for understanding household behavior
Energy research and social science, 2015Co-Authors: Alan Meier, Daniel Perry, Marco Pritoni, C Aragon, Therese PefferAbstract:Programmable Thermostats are generally sold as energy-saving devices controlling heating and cooling systems, but can lead to energy waste when not operated as designed by the manufacturers. We utilized Amazon Mechanical Turk, an online crowdsourcing service, to investigate thermostat settings and behavior in households. We posted a survey and paid respondents to upload pictures of their Thermostats to verify self-reported data. About 40% of programmable thermostat owners did not use programming features and 33% had programming features overridden. Respondents demonstrated numerous misconceptions about how Thermostats control home energy use. Moreover, we found that 57% of households were occupied nearly all the time, limiting the potential energy savings. The study revealed flaws in self-reported data, when collected solely from traditional surveys, which raises concerns about the validity of current thermostat-related research using such data. “Ground truth” temperature data could now be available in homes with Internet-connected Thermostats. Online crowdsourcing platforms emerge as valuable tools for collecting information that would be difficult or expensive to obtain through other means. Advantages over traditional surveys include low-cost, rapid design–implementation–result cycle, access to diverse population, use of multimedia. Crowdsourcing is more effective than alternative online tools due to easier recruitment process and respondents’ reputation system.
-
Facilitating energy savings with programmable Thermostats: evaluation and guidelines for the thermostat user interface
Ergonomics, 2012Co-Authors: Therese Peffer, Cecilia Aragon, Daniel Perry, Marco Pritoni, Alan MeierAbstract:Thermostats control heating and cooling in homes – representing a major part of domestic energy use – yet, poor ergonomics of these devices has thwarted efforts to reduce energy consumption. Theoretically, programmable Thermostats can reduce energy by 5–15%, but in practice little to no savings compared to manual Thermostats are found. Several studies have found that programmable Thermostats are not installed properly, are generally misunderstood and have poor usability. After conducting a usability study of programmable Thermostats, we reviewed several guidelines from ergonomics, general device usability, computer–human interfaces and building control sources. We analysed the characteristics of Thermostats that enabled or hindered successfully completing tasks and in a timely manner. Subjects had higher success rates with thermostat displays with positive examples of guidelines, such as visibility of possible actions, consistency and standards, and feedback. We suggested other guidelines that seemed miss...
-
How people use Thermostats in homes: A review
Building and Environment, 2011Co-Authors: Therese Peffer, Alan Meier, Cecilia Aragon, Marco Pritoni, Daniel PerryAbstract:Abstract Residential Thermostats control a substantial portion of both fuel and electrical energy—9% of the total energy consumption in the U.S. Consumers install programmable Thermostats to save energy, yet numerous recent studies found that homes with programmable Thermostats can use more energy than those controlled manually depending on how—or if—they are used. At the same time, Thermostats are undergoing a dramatic increase in capability and features, including control of ventilation, responding to electricity price signals, and interacting with a home area network. These issues warrant a review of the current state of Thermostats, evaluating their effectiveness in providing thermal comfort and energy savings, and identifying areas for further improvement or research. This review covers the evolution in technologies of residential Thermostats; we found few standards and many features. We discuss studies of how people currently use Thermostats, finding that nearly half do not use the programming features. The review covers the complications associated with using a thermostat. Finally, we suggest research needed to design—and especially test with users—Thermostats that can provide more comfortable and economical indoor environments.
