An Environment Monitoring System as Element of Urban Life

I am co-writing the journal version of the paper Real-Time Geo-awareness – Sensor Data Integration for Environmental Monitoring in the City, a work led by Bernd Resch. My contribution considers the implications of the integration of environment monitoring system as element of urban life. I plan to articulate it as follows:

a) Tools to support practitioners
I reemphasize that this kind of work is first targeted to the information needs of local and regional governments. It can change the work of practitioners that was previously about predicting and accommodating and now it becomes more observing and improving. Indeed, this new ability to render all kinds of ‘machine readable’ environments not only provide new views on the city, but also provide urban and transportation engineers and planners with indicators to evaluate their interventions. For instance Dan Hill and Duncan Wilson foresee the ability to tune buildings and cities through pre and post occupancy evaluations. They speculate that the future of environmental information will be part of the fabric of buildings (see The New Well-Tempered Environment: Tuning Buildings and Cities). However, this integration opens all sorts of issues regarding sampling, density, standardization, quality control, power control, officiality of data, and update frequency (freshness).

b) An imperfect mirror to reality
A complete picture might be hard to achieve with incomplete environmental data patched together by data mining, filtering and visualization algorithms. In many ways we are limited to classic technical issues related to data resolution and heterogeneity. Even mobile sensors do not yet provide high-density sampling coverage over a wide area, limiting research to sense what is technically possible to sense with economical and social constraints. One set of solutions rely on the calibration of mathematical models with only a few sensors nodes and complementing data sources to create a set of spatial indicators. Another, approach aims at revealing instead of hiding the incompleteness of the data. Visualizing the uncertainty of spatial data is a recurrent theme in cartography and information visualization (see Approaches to Uncertainty Visualization). These uncertainty visualization techniques present data in such a manner that users are made aware of the degree of uncertainty in their data so as to make more informed analyses and decision. It is a strategy to promote the user appropriation of the information with an awareness of its limitations (see Notes on Seams, Seamfulness and Seamlessness).

c) Crowdsourcing
Another way to improve the environment data is to alter the current model whereby civic government would act as sole data-gatherer and decision-maker by empowering everyday citizen to monitor the environment with sensor-enabled mobile devices. Recently providers of geographic and urban data have also learned the value of people-centric sensing to improve their services and from the activities of their customers. For instance the body of knowledge on a city’s road conditions and real-time road traffic network information thrive on the crowdsourcing of geodata the owners of TomTom system and mobile phone operators customers generate. Similarly, the users of Google MyMaps have contributed, without their awareness, to the production the massive database necessary for the development of the location-based version of the application. This people-centric approach to gather data raise legitimate privacy concerns. These issues can be handled with a mix of policy definition, local processing, verification and privacy preserving data mining techniques (see Debates on Privacy-Preserving Statistics and Data Mining). These technical solutions necessitate a richer discussion beyond the academic domain on these observing technologies’ social implications.

d) Linking people to their environment
Similar crowdsourcing strategies have been considered for environmental monitoring with individuals acting as sensor nodes and coming together with other people in order to form sensor networks. Several research project explore a wide rande of novel physical sensors attached to mobile devices empowering everyday non-experts with sensing abilities. For instance, Participatory Urbanism investigates the empowerment of citizens to collect and share air quality data measured with sensor-enabled mobile devices. This ‘citizen science’ approach creates value information for researchers of data generated by people going on their daily life, often based on explicit and participatory sensing actions. By turning mobile phones (SensorPlanet), watches (Montre Verte) or bikes (MetroSense) into sensing devices, the researchers hope that public understandings of science and environmental issues will be improved and can have have access to larger and more detailed data sets. This access to environmental data of the city also become a tool to raise the citizen awareness of the state of the environment. Moreover, with the increasing rendering ability of data processing and visualization solutions, citizen can become the actual producers of these awareness tool (example: In the Air).

e) Linking people to their practices
These data gathering and rendering possibilities also implies that we are at the end of the ephemeral, in some ways we will be able to replay the city. In contrast we are also ahead of conflicts to reveal or hide unwanted evidences, when new data can be used to the detriment of some stakeholder and policy makers. Indeed, the capacity to collect and disseminate reconfigure sensor data influence political networks, focussing on environmental data as products or objects that can be used for future political action. Therefore, the openness, quality, confidence and trust in the data will also be subject of debate (e.g. bias to have people record their observations, who gets to report data and who not). The implication of citizens in measuring, sharing, and discussing our environment might increase agencies’ and decision makers’ understanding of a community’s claims, thereby potentially increasing public trust in the information provided by a real-time geo-awareness approach. In consequence this could connect people to the environment in which they live, and provide them with tools for reflection on the impacts of their practices (for example Scanning Objects in the Wild: Assessing an Object Triggered Information System). This objective of improving the environmental sustainability of a city calls for behavior modification can be induced by intervening in moments of local decision-making and by providing people with new rewards and new motivations for desirable behaviors (see Stanford Pesuasive Computing Lab). These kinds of strategies have been common, for instance, in health and fitness applications. However, when we think about persuasion in the real of environment sustainability, what we might want to persuade people of is the ways in which their interests are aligned with those of others (see Paul Dourish’s Points of Persuasion: Strategic Essentialism and Environmental Sustainability). Therefore, this process of alignment and mobilization, by which one can start to find one’s own interests as being congruent with those of others will be critical in the success of these strategies based on real-time geo-awareness.

Relation to my thesis: Applying the kind of transdisciplinary work I have been discussing since the Real-Time Cities Round Table I setup last year. Here trying to provide an HCI perspective to the cutting edge work lead by research in GIS (Research Studio iSPACE) and Environmental Fluid Dynamics (Rex Britter) in the domain of sensor data integration for urban environmental monitoring.