As in last year, the European Space Agency (ESA) organised an App Developer Camp from 2-10 June. Twenty mobile app developers gathered in ESA’s main campus at Frascati, Rome to come up with innovative ideas on how to use Earth observation data to everyday life applications. This year’s app themes included Land-monitoring using GIO Land, Discovering Climate Change with GMES (Global Monitoring for Environment and Security), Crowd-sourcing in support of GMES, Games and leisure and Observe and learn.
The experience in itself was absolutely interesting and rewarding, as I had the chance to meet open-minded developers, full of ideas and passionate about their work. Moreover, the App Camp gave me more insight into ESA’s work and their future projects.
Regarding our project, as a part of the Crowd-sourcing team, along with Jonas Lekevicius a web and mobile designer from Lithuania, Diogo Mourão Simões a software developer and GIS master student at FCUL from Portugal and finally last but not least Timo Toivanen a Finnish software developer and researcher at VTT, we were expected to develop a prototype app that validates and/or complements remote sensing data by means of crowd-sourced in-situ data. However, the development of successful crowd-sourcing apps in general is not an easy task as it requires a lot of effort and careful thought to attract the millions of users that are usually needed to produce valid results. The resulting apps should be truly useful to the final users in order to provide their inputs and should motivate them in genuine and convincing ways. Users need incentives either social in the form of gamification and competition amongst virtual and real friends or material in the form of offers, promotions or even monetary.
Developing effective crowd-sourcing apps for the GMES is even more difficult as in most of the cases the GMES data are extremely precise, whether consumer devices such as smartphones cannot match and subsequently validate or compliment their data sets. However, after a brief analysis of GMES data we decided that the air quality layers could mostly benefit from the user’s observations. Current city air quality maps are based on models developed by the input of data from satellite observations and in-situ sensors. These models could notably benefit by the user’s input pointing to the authorities locations that do not match the model’s readings leading to improvements and in return increase the public awareness about environmental pollution and the benefits of breathing clean air to a person’s health. Clean air is vital for people’s health and wellbeing and according to research the access to clean air can improve and extend the average life expectancy. However, due to modern lifestyle, European citizens live in high polluted areas without making an effort to escape even temporarily.
Breathe More… Live More
The concept of the Breathe More… Live More application is to inform and lead citizens in areas with good quality of air nearby and induce them to participate in outdoors activities (such as jogging, running, picnicking etc), via a simple and intuitive map or list User Interface (UI) (Figure 1). Instead of just showing to the users an air quality map and asking for air quality observations, we attempt to motivate them by inserting the notion of gaining points for every minute they are actively present in areas with good air quality and as a side effect gaining minutes of their life. At the end of each area session users will be prompted to provide their feelings as a feedback to the area, helping to correlate the GMES data with people’s feelings and thoughts about the places they live in.
In this first mock-up implementation, the reporting screen can be accessed from every screen of the app and allows users to make a fast subjective observation about the air quality in that specific location, and it is graded in a simple, three step scale as more option would be confusing. Along with air quality report users can also augment their observation with tags about the area and mark the spot as dirty, smelly or noisy. These tags are in general interesting for evaluating the places the application is suggesting to users besides the air quality and relevant to decision-makers (Figure 2).
Apart from the first prototype mobile application, there is also a vision for a website where personal statistics could be compared to other users and create the element of competition between citizen to spent more time in areas with good and clean air, thus improving their general health. These leaderboards create a strong social incentive for users to use and spread the application.
What’s next, can the app advance from a conceptual / mock-up application to a finalized product and become already accessible to interested target groups? The answer is ambiguous because the main challenge is the access to the data. Most major European cities already have a sensor network that provide to the authorities information about air quality and indices about specific particles. However, access to these networks is most of the times impossible to the public and to the app developers. That introduces to our discussion the Open Data idea and the great impact to modern society of accessing them. But we can discuss open data and its significance on another post.The Air Quality Map model showed in the pictures is coming from London Air by King’s College London All the images are Copyrighted to Jonas Lekevicius, Diogo Mourão Simões, Timo Toivanen and Michalis Vitos