The Experts below are selected from a list of 264 Experts worldwide ranked by ideXlab platform
Nicholas R Jennings - One of the best experts on this subject based on the ideXlab platform.
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a scalable low cost solution to provide personalised Home Heating advice to households best paper award buildsys 2013
5th ACM Workshop On Embedded Systems For Energy-Efficient Buildings (BuildSys), 2013Co-Authors: Alex Rogers, Siddhartha Ghosh, Reuben Wilcock, Nicholas R JenningsAbstract:In this paper, we present a deployed prototype of a scalable low-cost solution providing personalised Home Heating advice to households. Our solution, named MyJoulo (www.myjoulo.com), uses intelligent algorithms to analyse data collected from a specially designed USB temperature logger, placed on top of the thermostat, in order to build a thermal model of the Home and to infer the operational settings of the Heating system. This model is then used to calculate the impact, in terms of percentage reduction in Heating costs, of various interventions (such as reducing the thermostat set-point temperature or adjusting timer settings); providing specific actionable advice to the household. The system was launched in beta form in December 2012 and registered over 750 users in its three months of operation.
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a scalable low cost solution to provide personalised Home Heating advice to households
ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, 2012Co-Authors: Alex Rogers, Siddhartha Ghosh, Reuben Wilcock, Nicholas R JenningsAbstract:In this paper, we present a deployed prototype of a scalable low-cost solution providing personalised Home Heating advice to households. Our solution, named MyJoulo (www.myjoulo.com), uses intelligent algorithms to analyse data collected from a specially designed USB temperature logger, placed on top of the thermostat, in order to build a thermal model of the Home and to infer the operational settings of the Heating system. This model is then used to calculate the impact, in terms of percentage reduction in Heating costs, of various interventions (such as reducing the thermostat setpoint temperature or adjusting timer settings); providing specific actionable advice to the household. The system was launched in beta form in December 2012 and registered over 750 users in its three months of operation.
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BuildSys@SenSys - A Scalable Low-Cost Solution to Provide Personalised Home Heating Advice to Households
Proceedings of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings - BuildSys '12, 2012Co-Authors: Alex Rogers, Siddhartha Ghosh, Reuben Wilcock, Nicholas R JenningsAbstract:In this paper, we present a deployed prototype of a scalable low-cost solution providing personalised Home Heating advice to households. Our solution, named MyJoulo (www.myjoulo.com), uses intelligent algorithms to analyse data collected from a specially designed USB temperature logger, placed on top of the thermostat, in order to build a thermal model of the Home and to infer the operational settings of the Heating system. This model is then used to calculate the impact, in terms of percentage reduction in Heating costs, of various interventions (such as reducing the thermostat setpoint temperature or adjusting timer settings); providing specific actionable advice to the household. The system was launched in beta form in December 2012 and registered over 750 users in its three months of operation.
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an intelligent agent for Home Heating management demonstration
Adaptive Agents and Multi-Agents Systems, 2012Co-Authors: Alex D Rogers, Sasan Maleki, Siddhartha Ghosh, Nicholas R JenningsAbstract:Intelligent software agents are increasingly being applied within the smart grid; a future vision of an electricity distribution network where information flows in both ways between between consumers and suppliers, and where electricity prices change in real-time in response to the current balance of supply and demand across the grid. In this demonstration, we show a Home Heating management agent that can learn the thermal characteristics of a Home and predict local weather conditions, in order to provide Home owners with realtime information about their daily Heating costs. Furthermore, we demonstrate how the agent can then optimise Heating use to minimise cost and carbon emissions whilst satisfying the Home owners preferences for comfort.
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AAMAS - An intelligent agent for Home Heating management (demonstration)
2012Co-Authors: Alex D Rogers, Sasan Maleki, Siddhartha Ghosh, Nicholas R JenningsAbstract:Intelligent software agents are increasingly being applied within the smart grid; a future vision of an electricity distribution network where information flows in both ways between between consumers and suppliers, and where electricity prices change in real-time in response to the current balance of supply and demand across the grid. In this demonstration, we show a Home Heating management agent that can learn the thermal characteristics of a Home and predict local weather conditions, in order to provide Home owners with realtime information about their daily Heating costs. Furthermore, we demonstrate how the agent can then optimise Heating use to minimise cost and carbon emissions whilst satisfying the Home owners preferences for comfort.
Neville A Stanton - One of the best experts on this subject based on the ideXlab platform.
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mind the gap deriving a compatible user mental model of the Home Heating system to encourage sustainable behaviour
Applied Ergonomics, 2016Co-Authors: Kirsten M A Revell, Neville A StantonAbstract:Householders' behaviour with their Home Heating systems is a considerable contributor to domestic energy consumption. To create a design specification for the ‘scaffolding’ needed for sustainable behaviour with Home Heating controls, Norman's (1986) Gulf of Execution and Evaluation was applied to the Home Heating system. A Home Heating Design Model (DM) was produced with a Home Heating expert. Norman's (1986) 7 Stages of Activity were considered to derive a Compatible User Mental Model (CUMM) of a typical Heating System. Considerable variation in the concepts needed at each stage was found. Elements that could be derived from the DM supported stages relating to action specification, execution, perception and interpretation, but many are not communicated in the design of typical Heating controls. Stages relating to goals, intentions and evaluation required concepts beyond the DM. A systems view that tackles design for sustainable behaviour from a variety of levels is needed.
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Mind the gap – Deriving a compatible user mental model of the Home Heating system to encourage sustainable behaviour
Applied Ergonomics, 2016Co-Authors: Kirsten M A Revell, Neville A StantonAbstract:Householders' behaviour with their Home Heating systems is a considerable contributor to domestic energy consumption. To create a design specification for the ‘scaffolding’ needed for sustainable behaviour with Home Heating controls, Norman's (1986) Gulf of Execution and Evaluation was applied to the Home Heating system. A Home Heating Design Model (DM) was produced with a Home Heating expert. Norman's (1986) 7 Stages of Activity were considered to derive a Compatible User Mental Model (CUMM) of a typical Heating System. Considerable variation in the concepts needed at each stage was found. Elements that could be derived from the DM supported stages relating to action specification, execution, perception and interpretation, but many are not communicated in the design of typical Heating controls. Stages relating to goals, intentions and evaluation required concepts beyond the DM. A systems view that tackles design for sustainable behaviour from a variety of levels is needed.
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When energy saving advice leads to more, rather than less, consumption
International Journal of Sustainable Energy, 2015Co-Authors: Kirsten M A Revell, Neville A StantonAbstract:Energy saving technology that relies on behaviour change fails to deliver on its promise. Energy saving advice also has limited effect. This paper examines and reveals how technology and energy saving advice interacts with householders’ thought processes to influence energy consumption. A case study of three households that held a ‘Feedback’ mental model of the Home Heating thermostat, as defined by Kempton [1986. ‘Two Theories of Home Heat Control’. Cognitive Science 10 (1): 75–90], was undertaken to understand the driver behind differences in their Home Heating strategies, and the effect on energy consumption. Analysis was undertaken from five different data sources comprising: (1) boiler on durations, (2) thermostat set point adjustments, (3) self-reported strategies with Home Heating controls, (4) user mental model descriptions of the Home Heating system, and (5) Interview transcripts. The authors found that differences in user mental models of Home Heating at the system level explained differences in...
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Using the notion of mental models in design to encourage optimal behaviour in Home Heating use
2013Co-Authors: Kirsten M A Revell, Neville A StantonAbstract:Introduction: Understanding how to influence householder’s energy consuming behaviour, could inform far reaching strategies to combat climate change. A Mental Model (MM) approach to design, to encourage optimal behaviour was explored. Challenges exist in accessing, describing and analysing user MMs and associated behaviour. Method: A method that considered bias in interpretation was developed, involving a structured interview, concept maps and graphical selfreported behaviour. Using this method, 6 householders in matched accommodation, over winter 2011/2012, participated in a Home Heating case study. Thermostat set point data was also collected from participant’s households. A Home Heating expert was interviewed using the same method, for comparison. Results and discussion: Key variations in MMs of Home Heating were found. The differences in user MMs from each other, and an expert, were insightful in explaining non-optimal Home Heating operation. These suggest design solutions that could promote or compensate for user mental models to influence energy consumption.
Enni Ruokamo - One of the best experts on this subject based on the ideXlab platform.
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linking perceived choice complexity with scale heterogeneity in discrete choice experiments Home Heating in finland
2016Co-Authors: Enni Ruokamo, Mikolaj Czajkowski, Nick Hanley, Artti Juutinen, Rauli SventoAbstract:Choosing a specific Heating system is a complex and difficult decision for Homeowners as there exists a wide array of Heating technologies with different characteristics that one can consider before purchasing. We include multiple Heating technologies and attributes in our Choice Experiment design and explore the effect of perceived choice complexity on the randomness of choices. In particular, we investigate how different self-evaluated factors of choice complexity affect mean scale and scale variance. Our findings suggest that perceived choice complexity has a systematic impact on the parameters of econometric models of choice. However, there are differences between alternative self-evaluated complexity-related covariates. Results indicate that individuals who report that answering the choice tasks was difficult have less deterministic choices. Perceptions of the realism of Home Heating choice options also affect scale and scale variance.
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household preferences of hybrid Home Heating systems a choice experiment application
Energy Policy, 2016Co-Authors: Enni RuokamoAbstract:The residential Heating sector presents considerable energy savings potential, as numerous Heating solutions for reducing electricity consumption and utilizing renewable energy sources are available in the market. The aim of this paper is to examine determinants of household Heating system choices and to use this information for policy planning purposes. This paper investigates residential Homeowner attitudes regarding innovative hybrid Home Heating systems (HHHS) with choice experiment. Heating system scenarios are designed to represent the most relevant primary and supplementary Heating alternatives currently available in Finland. The choice sets include six main Heating alternatives (district heat, solid wood, wood pellet, electric storage Heating, ground heat pump and exhaust air heat pump) that are described by five attributes (supplementary Heating systems, investment costs, operating costs, comfort of use and environmental friendliness). The results imply that HHHSs generally appear to be accepted among households; however, several factors affect perceptions of these technologies. The results reveal differing household attitudes toward the main Heating alternatives and show that such views are affected by socio-demographic characteristics (age, living environment, education, etc.). The results suggest that households view supplementary Heating systems (especially solar-based) favorably. The other attributes studied also play a significant role in decision making.
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Household preferences of hybrid Home Heating systems – A choice experiment application
Energy Policy, 2016Co-Authors: Enni RuokamoAbstract:The residential Heating sector presents considerable energy savings potential, as numerous Heating solutions for reducing electricity consumption and utilizing renewable energy sources are available in the market. The aim of this paper is to examine determinants of household Heating system choices and to use this information for policy planning purposes. This paper investigates residential Homeowner attitudes regarding innovative hybrid Home Heating systems (HHHS) with choice experiment. Heating system scenarios are designed to represent the most relevant primary and supplementary Heating alternatives currently available in Finland. The choice sets include six main Heating alternatives (district heat, solid wood, wood pellet, electric storage Heating, ground heat pump and exhaust air heat pump) that are described by five attributes (supplementary Heating systems, investment costs, operating costs, comfort of use and environmental friendliness). The results imply that HHHSs generally appear to be accepted among households; however, several factors affect perceptions of these technologies. The results reveal differing household attitudes toward the main Heating alternatives and show that such views are affected by socio-demographic characteristics (age, living environment, education, etc.). The results suggest that households view supplementary Heating systems (especially solar-based) favorably. The other attributes studied also play a significant role in decision making.
Kirsten M A Revell - One of the best experts on this subject based on the ideXlab platform.
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mind the gap deriving a compatible user mental model of the Home Heating system to encourage sustainable behaviour
Applied Ergonomics, 2016Co-Authors: Kirsten M A Revell, Neville A StantonAbstract:Householders' behaviour with their Home Heating systems is a considerable contributor to domestic energy consumption. To create a design specification for the ‘scaffolding’ needed for sustainable behaviour with Home Heating controls, Norman's (1986) Gulf of Execution and Evaluation was applied to the Home Heating system. A Home Heating Design Model (DM) was produced with a Home Heating expert. Norman's (1986) 7 Stages of Activity were considered to derive a Compatible User Mental Model (CUMM) of a typical Heating System. Considerable variation in the concepts needed at each stage was found. Elements that could be derived from the DM supported stages relating to action specification, execution, perception and interpretation, but many are not communicated in the design of typical Heating controls. Stages relating to goals, intentions and evaluation required concepts beyond the DM. A systems view that tackles design for sustainable behaviour from a variety of levels is needed.
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Mind the gap – Deriving a compatible user mental model of the Home Heating system to encourage sustainable behaviour
Applied Ergonomics, 2016Co-Authors: Kirsten M A Revell, Neville A StantonAbstract:Householders' behaviour with their Home Heating systems is a considerable contributor to domestic energy consumption. To create a design specification for the ‘scaffolding’ needed for sustainable behaviour with Home Heating controls, Norman's (1986) Gulf of Execution and Evaluation was applied to the Home Heating system. A Home Heating Design Model (DM) was produced with a Home Heating expert. Norman's (1986) 7 Stages of Activity were considered to derive a Compatible User Mental Model (CUMM) of a typical Heating System. Considerable variation in the concepts needed at each stage was found. Elements that could be derived from the DM supported stages relating to action specification, execution, perception and interpretation, but many are not communicated in the design of typical Heating controls. Stages relating to goals, intentions and evaluation required concepts beyond the DM. A systems view that tackles design for sustainable behaviour from a variety of levels is needed.
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When energy saving advice leads to more, rather than less, consumption
International Journal of Sustainable Energy, 2015Co-Authors: Kirsten M A Revell, Neville A StantonAbstract:Energy saving technology that relies on behaviour change fails to deliver on its promise. Energy saving advice also has limited effect. This paper examines and reveals how technology and energy saving advice interacts with householders’ thought processes to influence energy consumption. A case study of three households that held a ‘Feedback’ mental model of the Home Heating thermostat, as defined by Kempton [1986. ‘Two Theories of Home Heat Control’. Cognitive Science 10 (1): 75–90], was undertaken to understand the driver behind differences in their Home Heating strategies, and the effect on energy consumption. Analysis was undertaken from five different data sources comprising: (1) boiler on durations, (2) thermostat set point adjustments, (3) self-reported strategies with Home Heating controls, (4) user mental model descriptions of the Home Heating system, and (5) Interview transcripts. The authors found that differences in user mental models of Home Heating at the system level explained differences in...
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Using the notion of mental models in design to encourage optimal behaviour in Home Heating use
2013Co-Authors: Kirsten M A Revell, Neville A StantonAbstract:Introduction: Understanding how to influence householder’s energy consuming behaviour, could inform far reaching strategies to combat climate change. A Mental Model (MM) approach to design, to encourage optimal behaviour was explored. Challenges exist in accessing, describing and analysing user MMs and associated behaviour. Method: A method that considered bias in interpretation was developed, involving a structured interview, concept maps and graphical selfreported behaviour. Using this method, 6 householders in matched accommodation, over winter 2011/2012, participated in a Home Heating case study. Thermostat set point data was also collected from participant’s households. A Home Heating expert was interviewed using the same method, for comparison. Results and discussion: Key variations in MMs of Home Heating were found. The differences in user MMs from each other, and an expert, were insightful in explaining non-optimal Home Heating operation. These suggest design solutions that could promote or compensate for user mental models to influence energy consumption.
Darren Robinson - One of the best experts on this subject based on the ideXlab platform.
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a novel spatiotemporal Home Heating controller design system emulation and field testing
Building and Environment, 2018Co-Authors: Martin Kruusimagi, Sarah Sharples, Darren RobinsonAbstract:We have developed a spatiotemporal Heating control algorithm for use in Homes. This system utilises a combination of relatively low-tech hardware interfaced with electric Heating systems and a smartphone interface to this hardware, and a central server that progressively learns users’ room-specific presence profiles and thermal preferences. This paper describes the associated spatiotemporal Heating control algorithm, its evaluation utilising the dynamic building performance simulation software EnergyPlus, and a longitudinal deployment of the algorithm controlling a quasi-autonomous spatiotemporal Home Heating system in three domestic Homes. In this we focus on the prediction of occupants’ presence and preferred set-point temperature as well as on the calculation of optimum start time and the utilisation of user-scheduled absences; this for two comfort strategies: to maximise comfort and to minimise discomfort. The former aims to deliver conditions equating to a ‘neutral’ thermal sensation, whereas the latter targets a ‘slightly cool’ sensation with corresponding Heating energy savings. Simulation results confirmed that the algorithm functions as intended and that it is capable of reducing energy demand by a factor of seven compared with EnergyStar recommended settings for programmable thermostats. Field study results align with these findings and highlight the possibility to reduce energy under the minimise discomfort strategy without compromising on occupants’ thermal comfort.
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living with an autonomous spatiotemporal Home Heating system exploration of the user experiences ux through a longitudinal technology intervention based mixed methods approach
Applied Ergonomics, 2017Co-Authors: Martin Kruusimagi, Sarah Sharples, Darren RobinsonAbstract:Rising energy demands place pressure on domestic energy consumption, but savings can be delivered through Home automation and engaging users with their Heating and energy behaviours. The aim of this paper is to explore user experiences (UX) of living with an automated Heating system regarding experiences of control, understanding of the system, emerging thermal behaviours, and interactions with the system as this area is not sufficiently researched in the existing Homes setting through extended deployment. We present a longitudinal deployment of a quasi-autonomous spatiotemporal Home Heating system in three Homes. Users were provided with a smartphone control application linked to a self-learning Heating algorithm. Rich qualitative and quantitative data presented here enabled a holistic exploration of UX. The paper's contribution focuses on highlighting key aspects of UX living with an automated Heating systems including (i) adoption of the control interface into the social context, (ii) how users' vigilance in maintaining preferred conditions prevailed as a better indicator of system over-ride than gross deviation from thermal comfort, (iii) limited but motivated proactivity in system-initiated communications as best strategy for soliciting user feedback when inference fails, and (iv) two main motivations for interacting with the interface – managing irregularities when absent from the house and maintaining immediate comfort, latter compromising of a checking behaviour that can transit to a system state alteration behaviour depending on mismatches. We conclude by highlighting the complex socio-technical context in which thermal decisions are made in a situated action manner, and by calling for a more holistic, UX-focused approach in the design of automated Home systems involving user experiences.