Mobile technology, as a part of ICT, can support public participation in environmental conservation in the developing countries. Relatively cheap, modern, mobile devices are equipped with numerous sensors (GPS, Compass, Accelerometer, etc) and enable citizens to monitor and log various environmental issues. At UCL’s ExCiteS, a group which develops theories, tools and methodologies to enable communities anywhere to engage in Citizen Science, we aim to create mobile tools (software and hardware) to scientifically describe specific problems (resource damage in logging, illegal logging and poaching), so that ecosystem managers can better take them into account.
Our challenge is to provide non-literate indigenous people with tools that empower them to take action, and protect their local environment and way of life. We focus on developing an application to be used with robust Android devices and allow Pygmy hunter-gatherers in Central Africa to capture points of resources, points of abuses, illegal poaching activities, capture audio stories and photos. The collected data could compose data maps and be used by the local authorities for monitoring and protecting the forest ecosystem. Furthermore, the collected data could compose an intelligent map which will recognize emerging trends and inform both the communities and the authorities.
The main difficulties of the project are:
- The Pygmy hunter-gatherers have no formal education at all and have never used a mobile device.
- The weak GPS signal into the central Africa’s tropical forest for capturing points of interest.
- The lack of electricity power for charging the capturing devices.
- The lack of internet or network connectivity in order to upload the collected data into a central database.
At present, the development of the application is based on Open Data Kit (ODK), a free and open-source set of tools which help organizations author, field, and manage mobile data collection solutions. ODK provides to the following functions:
- Build a data collection form or survey;
- Collect the data on a mobile device and send it to a server; and
- Aggregate the collected data on a server and extract it in useful formats.
The main disadvantage of ODK is that it was created to be used among literate people who have some basics operational knowledge and basic reading skills (see some of the interface on the left).
Our version of the data collection application should operate in full screen hiding any extra information appearing on the top of the mobile phone such as the time, the battery status and the signal strength, should not contain any title bars or in general any written information and be consisted of a grid of pictorial icons through which the user could navigate. The application should operate in continuous loop mode, meaning that at the end of each location capture the application should go again to the first level of the decision tree. Each location should be saved automatically without asking the user for confirmation and a sound should be played to indicate that the capture was successful to provide feedback to the use. Any informative dialogues should be removed and the application should be pattern protected so that only authorized users could access to the data collection.
Currently, our application is in advanced prototype version and a prototype has been tested by the Pygmy hunter-gatherers in Congo rainforest, in the figure on the left you can see some screenshots of the application, showing the pattern locking in the left picture, the main screen where the user could start his navigation through the decision tree on the middle picture and the screen that follows if the user press the first icon on the right picture. For now the application captures 59 different types points of interest. To measure distance, we are capturing a location in “football pitches” units away from the user and the bearing of the device at the moment of the capture, this allows non-literate users to describe a distance using spatial concept that is familiar to them (see below). We have also developed an audio recording application for non-literate users to record narratives and provide contextual information or interpretations.
Our goals for the future are to improve the data collection application and create a more generic tool that could be used by different communities who wish to address issues of concern using tools and methods of scientific research. We support participants to collect scientifically valid information that describes their problems. By presenting the data on maps participants can compare and analise the results of their work. With solid evidence describing their problems they can influence others to take their concerns more seriously, and they can support efforts to develop solutions to the problems they have identified. Maps are the format we have found most inclusive when working with non-literate people and our goal is to create an intelligent map which will present the collected data in a way that is understandable by non-literate users and informs them when recognizable emerging trends occur.