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

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

Exploring Fuzzy Logic and Random Forest for Car Drivers’ Fuel Consumption Estimation in IoT-Enabled Serious Games

Internet of Things (IoT) technologies have a promising potential for instructional serious games related to field operations. We explore IoT’s potential for serious games in the automotive application domain to improve driving, choosing fuel consumption (FC) as an indicator of the driver performance as it is strongly influenced by driving styles and can be quantified and validated. We propose a FC prediction model, exploiting three vehicular signals that are controllable by the driver (player), that are able to provide direct coaching feedback to the driver and are easily available through the widely available On-Board Diagnostic-II (OBD-II) vehicular interface: throttle position, engine rotation speed (RPM) and car speed. We processed the data with two techniques, random forest (RF) and fuzzy logic (FL). Implementation, training and testing of both models, were made using the enviroCar database which freely provides a significant amount of naturalistic drive data. Results show that RF achieves quite a higher estimation accuracy, which complements FL’s ability to provide driver with easily understandable feedback. We thus argue that the combination of the two models can supply valuable information usable by game designers in the automotive environment

Energy feedback to domestic consumers: An evidence review for the Smart Energy Research Lab

The purpose of this evidence review is to inform a future energy advice service for domestic consumers (likely to be delivered as part of the Smart Energy Research Lab (SERL)) about what types of feedback have been trialled in the past, and what can be learned from these trials. Preliminary recommendations are offered in the next section in the executive summary, ahead of the more detailed review of different aspects of energy feedback and advice

Results and insight gained from applying the EnergyCat energy-saving serious game in UK social housing

Concerns about climate change associated with the combustion of fossil fuels urge a call for widespread reductions in household energy use. Determining means of achieving this is a key challenge faced by environmental scientists. The current research presents insights gained from a 12-month empirical trial of new serious game for energy, ‘EnergyCat’; which was designed to encourage household energy reductions in the UK social housing sector. Effects of gameplay on consumption behaviours and energy awareness were explored using 82 UK social housing households (versus a no-game control). Results indicated the intervention did not lead to any substantive changes in awareness or consumption practices. However, post-intervention feedback highlighted several issues in terms of game design and usability that may explain why the game failed to change behaviour in this instance. We provide a framework of suggestions as to how the game design process could be improved in order to engage residents in future, including use of adaptive fonts for older residents, and provision of clearer instructions on gameplay objectives at the outset. In addition, researchers should ensure close collaboration is maintained with residents throughout the design process in future efforts, in order to maximise likelihood of ongoing engagement from this population

A serious game enhancing social tenants' behavioral change towards energy efficiency

The energy consumption of the current building stock represents about 40% of the total final energy consumption in Europe. New gamification techniques may play a significant role in helping users adopt new and more energy efficient behaviours. This paper presents the advances achieved within the context of the EU-funded project EnerGAware - Energy Game for Awareness of energy efficiency in social housing communities. The main objective of the project, funded by the European Union under the Horizon2020 programme, is to reduce the energy consumption and carbon emissions in a sample of European social housing by changing the energy efficiency behaviour of the social tenants through the implementation of a serious game linked to the real energy use of the participants' homes

Household energy conservation with reality-enhanced serious games: Studies on effects in the real-world

In a reality-enhanced game player’s real-world activities, such as household energy saving activities, are integrated in the gameplay of a digital serious game. Players are then immersed in real-life situations that are generated by user interaction with the game, which stimulates the transfer of information between the game world and the real-world. This thesis presents empirical tests of principles that enhance the instructional design of reality-enhanced games to influence household energy conservation. For this research Powersaver Game is designed. We followed a user-centered game design methodology including two design-phases. In design-phase-1, principles are formulated to design a game prototype, and in design-phase-2 potential users evaluate this prototype. We conducted two studies. In a pretest-posttest design, both studies tested whether change in involved engagement, knowledge, attitude and behavior with respect to energy conservation in the household was different for participants playing Powersaver Game compared to a control condition (energy conservation dashboard or a basic version of the game). Families played Powersaver Game for more than three weeks (long-term duration) in their own household. Every day energy saving missions were provided by the game. The main goal was to reduce energy consumption. A real-time connection between the household energy meter and game server was accomplished. In the first study, effects were examined with respect to energy conservation in the household of the energy conservation game compared to an energy conservation dashboard. The form, timing and content of the information that the control condition receives from the energy conservation dashboard are as similar as possible as in the game condition, but excluded game elements. Our energy conservation game is effective in learning people to save energy in the household and to actually do that for the long term, while the energy dashboard does not change that behavior at all. In the second study, effects were examined of the game including the feature competition compared to a basic version of the game. We conclude that competition contributes to more change in energy saving behavior in the long term, and that higher awareness (more accessible knowledge) for a longer period leads to attitude change, which in turn results in behavior change in the long term; particularly the macro-attitude plays here a significant role. In general, we conclude that a digital energy conservation game with real energy conservation activities by monitoring real-life household energy consumption, which is developed in a thoughtful, iterative user-centered design process, significantly reduces energy consumption in the long term (in the weeks immediately following the intervention). In addition, the game feature competition contributes to even more change in energy conservation. Knowledge about saving energy at home increased, and engagement remained high during the whole intervention. In contrast, attitude change did not take place because it was already high from the beginning. Gamification by applying reality-enhanced games is still an emerging principle in research. It has a great potential for behavior change and attitude change in novel and engaging ways, and our results can be used in the development of effective games

Review of Serious Energy Games : Objectives, Approaches, Applications, Data Integration, and Performance Assessment

In recent years, serious energy games (SEGs) garnered increasing attention as an innovative and effective approach to tackling energy-related challenges. This review delves into the multifaceted landscape of SEG, specifically focusing on their wide-ranging applications in various contexts. The study investigates potential enhancements in user engagement achieved through integrating social connections, personalization, and data integration. Among the main challenges identified, previous studies overlooked the full potential of serious games in addressing emerging needs in energy systems, opting for oversimplified approaches. Further, these studies exhibit limited scalability and constrained generalizability, which poses challenges in applying their findings to larger energy systems and diverse scenarios. By incorporating lessons learned from prior experiences, this review aims to propel the development of SEG toward more innovative and impactful directions. It is firmly believed that positive behavior changes among individuals can be effectively encouraged by using SEG

A Fuzzy Logic Module to Estimate a Driver’s Fuel Consumption for Reality-Enhanced Serious Games

Reality-enhanced gaming is an emerging serious game genre, that could contextualize a game within its real instruction-target environment. A key module for such games is the evaluator, that senses a user performance and provides consequent input to the game. In this project, we have explored an application in the automotive field, estimating driver performance in terms of fuel consumption, based on three key vehicular signals, that are directly controllable by the driver: throttle position sensor (TPS), engine rotation speed (RPM) and car speed. We focused on Fuzzy Logic, given its ability to embody expert knowledge and deal with incomplete information availability. The fuzzy models – that we iteratively defined based on literature expertise and data analysis – can be easily plugged into a reality-enhanced gaming architecture. We studied four models with all the possible combinations of the chosen variables (TPS and RPM; RPM and speed; TPS and speed; TPS, speed and RPM). Input data were taken from the enviroCar database, and our fuel consumption predictions compared with their estimated values. Results indicate that the model with the three inputs outperforms the other models giving a higher coefficient of determination (R2), and lower error. Our study also shows that RPM is the most important fuel consumption predictor, followed by TPS and speed

Should We Play Games Where Energy Is Concerned? Perceptions of Serious Gaming as a Technology to Motivate Energy Behaviour Change among Social Housing Residents

No embargo required.The invisibility and intangibility of energy are key challenges faced by communicators looking to reduce household energy demand. ‘Serious games’—defined as formalized, goal-oriented games designed to educate, or promote health and well-being—are one potential strategy that may help to alleviate these challenges. This paper discusses the suitability of serious gaming as an educational and behavioural change tool within the context of social housing—a faction often overlooked when it comes to household energy research. The paper takes a two-part approach. First, we review current literature on serious energy games, and second, we discuss perceptions of serious energy games amongst social housing residents using data from two surveys (Survey A, n = 536; Survey B, n = 78). Perceptions of serious energy games were found to be mixed. Some residents liked the idea of a game for energy, particularly if clear, actionable solutions for reducing energy bills were provided. However, others were disinterested, due to existing time pressures, negative perceptions of gaming, and limited confidence using computers or tablets. As such, uptake may be met with challenges. The findings highlight the need for interdisciplinary collaborations and user-led approaches for the design of successful and engaging serious energy games

Eco-friendly Naturalistic Vehicular Sensing and Driving Behaviour Profiling

PhD ThesisInternet of Things (IoT) technologies are spurring of serious games that support training directly in the field. This PhD implements field user performance evaluators usable in reality-enhanced serious games (RESGs) for promoting fuel-efficient driving. This work proposes two modules – that have been implemented by processing information related to fuel-efficient driving – to be employed as real-time virtual sensors in RESGS. The first module estimates and assesses instantly fuel consumption, where I compared the performance of three configured machine learning algorithms, support vector regression, random forest and artificial neural networks. The experiments show that the algorithms have similar performance and random forest slightly outperforms the others. The second module provides instant recommendations using fuzzy logic when inefficient driving patterns are detected. For the game design, I resorted to the on-board diagnostics II standard interface to diagnostic circulating information on vehicular buses for a wide diffusion of a game, avoiding sticking to manufacturer proprietary solutions. The approach has been implemented and tested with data from the enviroCar server site. The data is not calibrated for a specific car model and is recorded in different driving environments, which made the work challenging and robust for real-world conditions. The proposed approach to virtual sensor design is general and thus applicable to various application domains other than fuel-efficient driving. An important word of caution concerns users’ privacy, as the modules rely on sensitive data, and provide information that by no means should be misused