Low cost air quality monitoring: comparing the energy consumption of an arduino against a raspberry Pi based system

Air pollution is one of the great challenges facing modern cities. According to the World Health Organization (WHO), 80% of people living in cities with air quality monitoring facilities are living in conditions where the quality of the air is well beyond the limits set out in the air quality guidelines. As more and more people are projected to move into urban areas by 2050, this problem is going to keep on increasing. A possible solution could be the advent of Smart Cities. One of the objectives of Smart Cities is to provide a better living environment to its inhabitants. With the Internet of Things providing easily deployable, low power, low cost air quality monitoring sensors and the resources to process the huge amount of data collected, this objective could be reached. In this paper, we propose an evaluation of the power consumption of two low cost air quality monitoring systems - one based on an Arduino and the other on a Raspberry Pi system. The air quality systems proposed are based on off-the shelf hardware and are easy to assemble and maintain. The proposed systems use Bluetooth Low Energy (BLE) to transmit data while being collected through a mobile app on a smartphone. The data was collected for five days and it was found by performing an ANOVA on the power consumption that there was a significant difference in the mean energy consumption of the two systems

Flâneries florales dans le Pays grassois

: From literary and television representations, as well as personal strolls in the Pays de Grasse, we reconstruct the international, and yet very local, course of the perfume and aroma industry in Grasse, as well as the tradition of growing perfume flowers in the region is highlighte

A perceptual model of smellscape pleasantness

Smellscape has increasingly attracted attentions across disciplines. However, little research provides a model to help understand the perceptual qualities of smellscapes. This paper, taking pleasantness as a perceptual quality dimension, aimed to explore indicators influencing people's pleasantness of smellscapes in a selected case. People's natural speaking language was used as resources to understand their perceptions. Grounded Theory was used as a methodological approach in this study in a selected case. Nineteen participants were recruited for smell walking with semi-structured interviews. Overall, nine indicators emerged from participants’ descriptions which contribute to their smellscape pleasantness: cleanliness, preference, appropriateness, naturalness, freshness, familiarity, calmness, intensity and purity. Meanwhile, four types of pleasantness were found according to dominant indicators: preference dominated, healthiness dominated, memories and habituation dominated and context dominated. A perceptual model has been developed based on the indicators which can be used to classify smellscapes through their dominant perceptual features and evaluate smellscape qualities based on pleasantness

Smelling therapeutic landscapes: embodied encounters within spaces of care farming

The conceptual framework of ‘therapeutic landscapes’ has been used as a means of considering the significance of specific environments, spaces, and places for aspects of health. Building on a growing attention to the sensory elements of spaces of health and wellbeing, this article mobilises empirical research on ‘care farming’ practices to discuss how smellscapes come to be crucial in fulfilling anticipations, imaginations, and expectations of a ‘therapeutic space’. This article highlights how embodied relationships with specific scents can constitute a therapeutic encounter with place, actively influencing practices and engagement with(in) place, and the ways by which place can have a meaningful affect on health

Politics of smell: Constructing animal waste governmentality and good farming subjectivities in colonial Hong Kong

This is the final version. Available on open access from SAGE Publications via the DOI in this record.This paper examines the governmentality of colonial Hong Kong throughout the 1980s and 1990s, focusing on the implementation of the Livestock Waste Control Scheme (1987-1997), the production of normative waste treatment knowledge, the spatial control of farming practices and the resulting subjectivity in the construction of the ‘environmentally friendly farmer’ identity. These themes are examined by analysing archival materials and conducting in-depth interviews with two Pig Farmers Association representatives and nineteen pig farmers. This paper argues that the colonial government of Hong Kong relied on environmental ordinances and zoning regulations, livestock waste demonstration projects and socially constructed perceptions of olfactory acceptability as major technologies of governance in the creation of ‘environmentally friendly’ pig farmers. Through being exposed to these technologies, pig farmers learned and internalised a particular concept of what constitutes appropriate animal waste management and treatment. This paper shows how the concept of being ‘environmentally friendly’ contributes to the creation and use of ‘good farming’ subjectivities when modernising pig farmers’ waste management practices

Capturing perceived everyday lived landscapes through gamification and active crowdsourcing

Summary Landscapes are distinguishable areas of the earth with distinct characters comprised of tangible and intangible dimensions and entities. Interactions between humans and landscapes influence social, physical and mental well-being as well as guide behaviour. Understanding how landscapes are perceived has thus gained traction in sustainable and inclusive policy and decision making processes and public participation is called for. The recognised importance of understanding landscapes from an experiential and perceptual perspective and incorporating public participation in data generation efforts is reflected in overarching conventions, policy guidelines and frameworks including the European Landscape Convention (ELC), the Millennium Ecosystem Assessment (MEA), Natures Contributions to People (NCP) and the Landscape Character Assessment (LCA) framework. Major challenges for these conventions and frameworks are 1) how to collect data on landscape experiences and perceptions from a diverse group of individuals, 2) how to integrate and link physical entities, sensory experiences and intangible dimensions of landscapes and 3) how to identify other potential sources of landscape relevant information. The abundance of storage space and the accessibility of broadband internet have led to a burgeoning of user generated natural language content. In parallel, various paradigms of exploiting ubiquitous internet access for research purposes have emerged, including crowdsourcing, citizen science, volunteered geographic information and public participation geographic information systems. These low cost approaches have shown great potential in generating large amounts of data, however, they struggle with motivating and retaining participants. Gamification - broadly defined as adding entertaining or playful elements to applications or processes - has been found to increase user motivation and has explicitly been called for in landscape perception and preference research to diversify participant demographics. Meanwhile, natural language has been found to be deeply intertwined with thought and emotion and has been identified as a rich source of semantic data on how landscapes are perceived and experienced. Written texts and the ways in which these can be analysed have gained particular interest. Therefore, the overall goal of this thesis is to develop and implement a gamified crowdsourcing application to collect natural language landscape descriptions and to analyse and explore the contributions in terms of how landscapes are perceived through sensory experiences and how additional landscape relevant natural language can be identified. To approach this goal, I first elicit key data and feature requirements to collect landscape relevant information from a heterogeneous audience. Guided by the identified requirements, I develop and implement Window Expeditions, a gamified active crowdsourcing platform geared towards collecting natural language descriptions of everyday lived landscapes. The generated corpus of natural language is explored using computational methods and I present and discuss the results in light of who the contributors are, the locations from which participants contribute and salient terms found in English and German. In a further step I annotate a subset of English contributions according to the contained biophysical elements, sensory experiences and cultural ecosystem (dis)services and explore these in terms of how they are linked. Finally, I present a novel approach of using a curated high quality landscape specific dataset to computationally identify similar documents in other corpora using sentence-transformers. Using the Mechanics, Dynamics and Aesthetics (MDA) framework, the aesthetics of discovery, expression and fellowship were identified as most fitting for an active crowdsourcing platform. In addition, four groups of main dynamics were found, namely general dynamics of user interactions, contribution dynamics, exploration dynamics and moderation dynamics. The application was gamified by introducing points and leader boards and the platform was implemented in German and English (with French being added at a later point) to collect landscape descriptions in multiple languages. Demographic information was collected about the users including their year of birth, their gender, if they were at home whilst contributing and what languages users believed to be fluent in. Using the Mechanics, Dynamics and Aesthetics (MDA) framework, the aesthetics of discovery, expression and fellowship were identified as most fitting for an active crowdsourcing platform. In addition, four groups of main dynamics were found, namely general dynamics of user interactions, contribution dynamics, exploration dynamics and moderation dynamics. The application was gamified by introducing points and leader boards and the platform was implemented in German and English (with French being added at a later point) to collect landscape descriptions in multiple languages. Demographic information was collected about the users including their year of birth, their gender, if they were at home whilst contributing and what languages users believed to be fluent in reporting not being at home (n = 172) who were more likely to contribute from areas of herbaceous vegetation. Terms describing salient elements of everyday lived environments such as "tree", "house", "garden" and "street", as well as weather related phenomena and colours were found frequently in both English and German contributions in the generated corpus. Further, terms related to space, time and people were found significantly more frequently in the generated corpus compared to general natural language and representative landscape image descriptions highlighting the importance of spatial features as well as people and the times at which these were observed. Notably, descriptions referring to trees and birds were frequently found in the contributed texts, underlining their saliency in everyday lived landscapes. The results show biophyiscal terms related to vegetation (n = 556) and the built environment (n = 468) as well as weather related terms (n = 452) to be most prominent. Further, contributions referencing visual (n = 186) and auditory (n = 96) sensory experiences were found most often with positive sensory experiences being most common (n = 168) followed by neutral (n = 86) and negative (n = 68). In regards to the intangible dimensions captured in the contributed landscape descriptions, recreation (n = 68) was found most often followed by heritage (n = 36), identity (n = 26) and tranquillity (n = 23). Through linking biophysical elements, sensory experiences and cultural ecosystem (dis)services, the results show that the biophysical category of animals appears often with the sensory experience of smell/taste and the biophysical category of moving objects appears more than expected with the sensory experience of sound. Further, the results show the cultural ecosystem service of inspiration to often appear with the biophysical category of natural features and tranquillity with weather. Using a curated subcorpus of English natural language landscape descriptions (n = 428) collected with Window Expeditions, similar documents in other collections were identified. Through translating documents to vectors by means of sentence-transformers and calculating cosine similarity scores, a total of 6075 to 8172 documents were identified to be similar to contributions to Window Expeditions, depending on if the initial dataset was prefiltered for biophysical noun lemmas (a list of biophysical landscape elements derived from the Window Expeditions corpus) and Craik’s list adjectives (a list of common adjectives used to describe landscapes). Latent Dirichlet allocation topic modelling, a clustering approach which is commonly used to identify overarching topics or themes in collections of natural language, shows four distinct clusters in both Window Expeditions as well as in the corpus of identified similar documents, namely urban and residential, rural and natural, autumn and colours and snow and weather. Overall, the results presented in this thesis provide further evidence to work that natural language is a rich source of landscape specific information, capturing underlying semantics of a multitude of referenced landscape dimensions. In particular, this thesis demonstrates that computationally aided approaches to analysing and exploring landscape relevant textual data can give detailed insights into salient features of landscapes and how individuals perceive and experience these. Especially when complemented by human annotation, natural language landscape descriptions are a welcome source of data about a landscape’s biophysical elements, individual sensory experiences in landscapes and the perceived cultural ecosystem (dis)services. The findings of this thesis are accompanied by various limitations, chief amongst which are the possibilities of users to falsify their locations, the rather small amount of data that was collected through Window Expeditions and the Eurocentric definitions and approaches common in landscape perception research. The former two limitations can be addressed through implementational reiterations and promotional efforts, whereas the latter limitation calls for further consideration of the socio-culturally induced construction of landscape perception research and a rethinking of holistic approaches, especially in multicultural participatory contexts. The work presented in this thesis shows great potential in complementing landscape perception research with gamified methods of data generation. Active crowdsourcing can be a cost efficient and scalable approach of generating much needed data from a diverse audience. Exploring landscape relevant natural language with both quantitative and qualitative methods from various disciplines including geographic information science, linguistics and machine learning can lead to new insights into landscape perception, sensory landscape experiences and how these are expressed

Waiting through Furlough: A Geography of Disorientation

This thesis tells a story of waiting. More specifically the thesis investigates the lived experience of those who waited through furlough as part of the UK Government Coronavirus Job Retention Scheme, which paid workers to not work during the COVID-19 pandemic. Although the pandemic and the scheme form its backdrop, the thesis foregrounds understandings of how waiting through furlough was lived and felt. The thesis investigates the embodied feelings and detached work life relations experienced by those furloughed and how they narrated their experience. It draws on the accounts of furloughed workers shared in thirty-five in depth interviews, and extended attention to the spatial, temporal, corporeal, felt and tensive dimensions of waiting, through literatures of waiting, affect and queer phenomenology. In doing so the thesis argues that the detachment from work life and its rhythms made life disorientating for those waiting through furlough. As such, this thesis is also a story of disorientation. Disorientation is conceptualised in the thesis as having a plurality of forms and shaped the furlough’s capacity to act, feel and endure their situation. Spatial disorientation involves an orientation towards another who becomes an emotional marker for those furloughed. Temporal disorientation is the consequence of an orientation towards work time which is maintained, substituted for, slips or become hazy. Tensive disorientation describes how the suspension from work life is felt as a series of tensions. This study’s surfacing of the different dimensions of disorientations within a duration of waiting, potentially adds to understandings of embodied disorientations and (non)work life within geographies of waiting, disorientation, labour and COVID-19