Context of the case study
Climate change presents an arduous challenge to urban environments and the development and implementation of climate actions have become crucial tasks, which however heavily rely on the availability of meaningful and accurate data.
In this case study, we will assemble and deploy low-cost sensors in order to downscale scientific climate datasets, improve individual citizens’ environmental perception and create an innovative microclimate sensing network with local communities and civil society organizations, in the “living lab” constituted by NTU and its associated communities.
Objectives
Create a metropolitan Taipei urban climate map, that can support local climate action plans, using the data obtained by the sensors and local knowledge, in a participatory sensing and citizen science approach.
Participants include: (1) Academia Sinica’s Institute of Information Science (air box development team); (2) Location Aware Sensing System (LASS), a maker community, along with (3) local community actors (Wenshan Community College, Taipei City Da’an District University Neighborhood, New Taipei City Ying Ge Jian Guo Neighborhood).
- Activity 1: To develop an all-in-one device that can “sense comfortability” in three dimensions: hot/cold, polluted/clean, and quiet/noisy, using temperature, humidity, wind speed, light radiation, suspended particles, volatile organic compounds, carbon dioxide, and noise sensors.
- Activity 2: To promote the “Sensing Citizens” initiative, recruiting volunteers and students to use mobile sensors to collect environmental data during their daily commuting; to develop maker workshops, invite stakeholders to produce and deploy sensors, expanding environmental monitoring issues and capabilities.
- Activity 3: To design data analysis and visualization systems to facilitate the calibration of new sensors, combine their results with existing environmental sensing stations to establish urban microclimate models, and build a real-time information display system to help citizens understand their environmental conditions and public authorities build an annual climate risk map to serve as a reference for urban climate action.
Implementation
Expected methodological outcomes: linkages between participatory sensing, crowdsourcing activities and data assimilation in visualisation models