Tomoyo Sasao

A mobile phone-based exploratory citizen sensing environment

Coping with ill-structured problems in a city involves continuous, opportunistic, and multi-perspective processes, which existing pervasive technologies for citizen participation cannot easily support. Based on two preliminary case studies, we propose Scene Memo, a mobile phone-based exploratory citizen-sensing environment that uses dynamically shared tags to provide social cues and scaffold participants.

Community Reminder: Participatory Contextual Reminder Environments for Local Communities

Abstract Many projects have looked at how communities can co-design shared online repositories, such as Wikimapia and Wikipedia. However, little work has examined how local communities can give advice and support to their members by creating context-aware reminders that may include advice, tips and small requests. We developed the Community Reminder environment, a smartphone-based platform that supports community members to design and use context-aware reminders. We have conducted a one-month field study of Community Reminder to crowdsource and deliver safety-relevant information in a local community. The results show the benefits of involving community members in reminder design and connecting different perspectives. We also show that the proposed approach can broaden participation in local communities.

Support Environment for Co-designing Micro Tasks in Suburban Communities

Designing usable tasks for coping with civic challenges can be hard without an appropriate design environment. I explore a support environment for co-designing them with citizens. I expect that co-designed tasks will help address urban issues and extend the possibility of citizen-centered urban design methods.

Crowd Geofencing

Geofencing mechanisms allow for timely message delivery to the visitors of predefined target areas. However, conventional geofencing approaches poorly support mobile data collection scenarios in which experts need in situ assistance. In this paper, we propose crowd geofencing environments, in which a large number of crowdworkers generate geofences to support mobile experts. As a first step to open up the possibilities of crowd geofencing, we have tested its feasibility by collecting more than one thousand geofences in an unfamiliar city prior to the visit to look into urban water and air quality issues. Our experience has revealed the strengths and weaknesses of crowd geofencing in terms of geofence quality and crowd-powered situated actions.

U.App: An Urban Application Design Environment Based on Citizen Workshops

Designing usable applications for coping with civic challenges can be extremely difficult without an appropriate design environment. We explore a novel application design process based on the analysis of real citizen workshops, and propose U.App, a design environment that allows citizens to create urban applications based on the process. We expect that the proposed environment will facilitate citizens’ daily activities for addressing urban issues and extend the possibility of citizen-centered mobile applications.

Supporting community-centric use and management of vacant houses: a crowdsourcing-based approach

In recent years, the number of vacant houses is increasing in Japan, as the population decline in local communities. In this context, there is an urgent need to develop smart socio-technical systems that enable effective use and management of vacant houses, thereby preventing them from having negative impacts on local communities. In this paper, we propose an approach to support community-centric use and management of vacant houses based on an integrated crowdsourcing platform. We describe our ongoing project in Kashiwa City, and argue for an open, inclusive, and community-centric distributed platform to cater for some of the important needs in the community.

The Use of Historical Information to Support Civic Crowdsourcing

Context-aware notifications cannot be designed easily without knowing which context-aware notifications will be triggered and responded in time. In this paper, we discuss methods to improve the design of context-aware notifications. Using the data from our prior experiment, we identify main factors that influence citizens’ responses to notifications and evaluate the predictability of quick responses using a simplified method. We then propose a model for designing civic crowdsourcing tasks based on historical information. We believe that creating well-designed notifications can decrease receivers’ workloads and simultaneously expands the positive impacts of civic crowdsourcing on the quality of life in the city.

Context Weaver

Mobile crowdsourcing allows people to collect data using a large pool of participants. In this paper, we focus on mobile crowdsourcing for citizens to solve local issues in context. We argue that such crowdsourcing environments need to support exploration, a continuous, opportunistic, and multi-perspective process that existing crowd sensing systems cannot easily support. We have developed a system called Context Weaver, which connects participants using networked mobile devices in order to support collaborative exploration, and conducted field trials to understand the effect of networking participants in the crowdsourced data-collection activities that encompass planning, execution, and analysis phases. We discuss a methodology for exploratory mobile crowdsourcing by citizens based on the provision of mutual awareness and rapid feedback in context. The proposed methodology can provide a basis for a model of networked mobile crowdsourcing which can exploit not only the man-power but also the creativity of citizens to gather relevant data.

A context-aware approach to microtasking in a public transport environment

Despite the pervasiveness of smart devices, meaningful data cannot be collected easily without an effective platform that meshes with human activities. In this paper, we explore the design space for mobile applications that recommend microtasks in public spaces. In particular, we take a close look at a public transportation environment and suggest some of the contexts in which microtask requests could be embedded. We then discuss a context-aware approach to microtasking in a city, as well as its implications for citizens.

Using ambient WiFi signals to find occupied and vacant houses in local communities

In many countries, the population is either declining or rapidly concentrating in big cities, which causes problems in the form of vacant houses. It is often challenging to keep track of the locations and the conditions of vacant houses, and for example in Japan, costly manual field studies are employed to map the occupancy situation. In this paper, we discuss a technique to infer the locations of occupied and vacant houses based on ambient WiFi signals. Our technique collects Received Signal Strength Indicator (RSSI) data based on opportunistic smartphone sensing, constructs hybrid networks of WiFi access points, and analyzes their geospatial patterns based on statistical shape modeling. In situ experiments in two residential neighborhoods show that the proposed technique can successfully detect occupied houses and substantially outperform a simple triangulation-based method in one of the neighborhoods. We also argue that the proposed technique can significantly reduce the cost of field surveys to find vacant houses as the number of potential houses to be inspected decreases.