Visualisation in energy eco-feedback systems: A systematic review of good practice. (July 2022)

• Record Type: Journal Article
• Authors: Chalal, M.L.; Medjdoub, B.; Bezai, N.; Bull, R.; Zune, M.
• Is Part Of: Renewable & sustainable energy reviews. Volume 162(2022)
• Publication Date: 2022-07
• Subjects: Eco-visualisation -- Eco-feedback -- Energy sustainability; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2022.112447
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: While adopting eco-feedback systems can lead to significant energy savings, in the region of 5–20%, research has shown that the inappropriate use of visualisation patterns and techniques decreases their effectiveness. However, existing reviews on energy feedback visualisation provide little guidance on when to use them and how to enhance their effectiveness in various scenarios. The uncertainty and lack of clarity surrounding eco-feedback visualisation techniques and their impact on end-userengagement present challenges to the design of eco-feedback systems. This paper presents the first systematic review of a wide range of energy eco-feedback visualisation techniques, including, for the first time, Augmented-Reality (AR) and thermal imaging visualisation. We analysed 82 relevant studies published between 2000 and 2021 using the PRISMA protocol for systematic reviews. The visualisation techniques have been reported under five distinct categories, which we have identified: (a) statistical visualisation, (b) architectural and geospatial visualisation, (c) game-based visualisation, (d) artistic visualisation, (e) emerging visualisation . Furthermore, they have been analysed based on the following criteria: type of visualised information, the purpose of use, end-user perception, scholar suggestions, and potential impact. The findings show that statistical visualisation techniques are essential in any energy eco-feedback system. Furthermore, they suggested combining different visualisation techniques to accommodate different user profiles, but such combinations must be carefully planned based on usage scenarios. Following this analysis, a series of considerations and good practice guidelines are presented for each of the reviewed techniques to assist practitioners in this area (e.g., designers and researchers) while providing recommendations for future work. Highlights: The inappropriate use of visualisations in eco-feedback systems decrease their effectiveness. Little guidance on when to use different visualisations and how to enhance their effectiveness. This article reviews various energy eco-feedback visualisation techniques and provides good practice recommendations. Statistical visualisation techniques are essential in any energy eco-feedback system. Visualisation techniques should be combined but such combinations must be carefully studied based on usage scenarios.