Learning from the Veg Box

Verame, Jhim Kiel M.; Costanza, Enrico; Fischer, Joel E.; Crabtree, Andy; Ramchurn, Sarvapali D.; Rodden, Tom; Jennings, Nicholas R.

doi:10.1145/3173574.3174021

Cited by 8 publications

(10 citation statements)

References 49 publications

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“…Overall, the contingencies people bring up-and our categorisation of them-reveal and systematise the reasons for why everyday use of household products is variable. The statements together are testament to the need for variety when it comes to food, echoing previous findings [57]. The following set of results sheds more light on this topic, by examining the aforementioned equivalency problem.…”

Section: Understanding Household Consumptionsupporting

confidence: 68%

“…[30]), and in-home breaching experiments (e.g. [57]), to algorithmic Machine Learning-driven approaches (e.g. [1]).…”

Section: The Proactive Internet Of Things (Iot)mentioning

confidence: 99%

“…The authors have found shopping to be both comprised of incidental (i.e., opportunistic) and intentional (i.e., planful) practices. Data collection methods have included photo diary studies of participants preparing and consuming food [28,57], and wearable cameras to reveal food consumption cycles in the home [39]. IoT technologies, however, hold the potential to allow such data to be collected automatically [40], using devices such as smart fridges to track how products in the home are used [9].…”

Section: Domestic Grocery Shoppingmentioning

confidence: 99%

“…In sum, a proactive IoT system that supports grocery shopping must address: how and which data to collect to make sense of the product life cycle [39], how to compute metrics to drive a system that reliably reorders food 'in time' while considering human desires for variety [57], how to deal with the 'out-of-stock substitution' problem, but without generating food waste [50]. The gap we address in this work is to offer an examination of the contingencies that shape the uncertainty of everyday routine, and how this could be systematically handled in and through design.…”

Section: Domestic Grocery Shoppingmentioning

confidence: 99%

“…Research in HCI is beginning to examine how people experience emerging 'proactive' Internet of Things (IoT) technologies in their everyday lives [20], for example to automate elements of food shopping [57]. Current approaches for managing grocery shopping vary, relying on various degrees of automation and technology, including buttons for instant re-ordering (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Tracking the Consumption of Home Essentials

Fuentes

Porcheron

Fischer

et al. 2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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Predictions of people's behaviour increasingly drive interactions with a new generation of IoT services designed to support everyday life in the home, from shopping to heating. Based on the premise that such automation is difficult due to the contingent nature of people's practices, in this work we explore the nature of these contingencies in depth. We have designed and conducted a technology probe that made use of simple linear predictions as a provocation, and invited people to track the life of their household essentials over a two-month period. Through a mixed-method approach we demonstrate the challenges of simple predictions, and in turn identify eight categories of contingencies that influenced prediction accuracy. We discuss strategies for how designers of future predictive IoT systems may take the contingencies into account by removing, hiding, revealing, managing, or exploiting the system uncertainty at the core of the issue. CCS CONCEPTS • Human-centered computing → Field studies; Empirical studies in ubiquitous and mobile computing; Empirical studies in HCI .

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Section: Understanding Household Consumptionsupporting

confidence: 68%

“…[30]), and in-home breaching experiments (e.g. [57]), to algorithmic Machine Learning-driven approaches (e.g. [1]).…”

Section: The Proactive Internet Of Things (Iot)mentioning

confidence: 99%

Section: Domestic Grocery Shoppingmentioning

confidence: 99%

Section: Domestic Grocery Shoppingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Tracking the Consumption of Home Essentials

Fuentes

Porcheron

Fischer

et al. 2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Self Cite

View full text Add to dashboard Cite

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Interactions of fast‐moving consumer goods in cooking: Insights from a quantitative ethnographic study

2022

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Fast‐moving consumer goods (FMCGs) are increasingly equipped with enhanced packaging that incorporates novel functionalities. Providing FMCGs with this technology is challenging due to their unique characteristics, such as their low cost and short lifespan. Knowledge derived from a comprehension of their interactions in practice can help develop FMCGs that better cater to consumer needs and are well‐integrated into real‐world contexts. To help develop a method for the formation of such practical insights, 20 households were visited where participants were then observed as they cooked a meal. The sessions were captured on video, and a detailed record of the interactions between individuals, FMCGs and other items was made. A quantitative ethnographic approach was applied to analyse and build an understanding of different aspects of these interactions including their frequential, sequential and correlational features. The findings are discussed through the lens of how an appreciation of the interactions of FMCGs can serve as a valuable guidance for the design and development of their enhanced counterparts. The discovery that FMCGs are linked to the use of other items, for instance, is proposed as an opportunity to make use of the unique properties of the other items that a given FMCG commonly interacts with as a resource to create functionalities. As an exploratory reflection of how FMCGs are utilised in practice, the methods and knowledge presented in this study can be valuable in creating enhanced FMCGs by advocating for a product development process in which decisions are firmly grounded in empirical insights.

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