The future of sensors and geospatial analytics in international development

3 June 2015. Washington. At the ICTforAg conference, sponsored by FHI 360’s TechLab, DAI and Abt Associates, the “New tools for remote sensing and geospatial data” breakout session featured four leading thinkers on how to use sensors in ICTforAg interventions:

• Valerie Oliphant of the Social Impact Lab presented a solar-powered Arduino-based sensor to detect air pollutants that will be installed in Sao Paolo bus stations, which sends the data it collects to a central database by SMS using FrontlineSMS. The data generated by the sensor could help the municipal government issue air quality alerts and make policy changes to improve air quality, such as requiring more energy efficient buses.
• Greg Austic of MSU works on PhotosynQ, an open research project whose goal is to create a network of low cost, hand-held measurement devices which researchers, educators, and citizen scientists can use to build a global database of plant health. Greg demonstrated the MultispeQ leaf thickness detector and a soil tester that are some of the first products to come out of the PhotosynQ collaboration.
• Jawoo Koo presented Mappr, a spatial visualization and analysis tool offering easy access to over four hundred layers of spatially explicit, agricultural-related data for sub-Saharan Africa. Mappr allows researchers and any other interested parties to select from its 400+ indicators, such as rural poverty density or child mortality, to create customized maps.
• Ryan Whitley of Spatial Development presented an array of free and open source tools which support the entire process of map-making, from the simple act of gathering data, to the creation of complex, layered maps for analysis and decision-making. The tools presented include:
• Open Data Kit (ODK) – a free and open-source set of tools which help organizations author, field, and manage mobile data collection solutions
• Qgis – a FOSS alternative to ESRI, a popular commercial Geographic Information System software tool, that can be used to load and manipulate data before loading into mapping software
• Open Street Map – a collaborative world map based on open data
• MapBox – a FOSS “vector rendering framework for highly customizable and responsive client-side maps”
• PostGIS – “a spatial database extender for PostgreSQL object-relational database”
• Whitley is currently building his own tool, PGrestAPI, which incorporates the functionality of some of tools listed above.

Each noted that sensors are radically cheaper and more robust, while platforms for taking advantage of the power of sensors have matured. That combination makes it possible for enterprising people with great ideas to build their own sensor systems without the trouble of coding the platform from scratch.

These sensors may not be as accurate as high-end commercial sensors, but their extreme low cost (approximately $30 for Oliphant’s air quality sensor) allow many more to be deployed than would be possible when working with high-end sensing equipment. And the greater number of data points generated by an array of low-cost sensors allow them to approach the accuracy of high-end sensors via statistical sampling.

What does the future hold? Smaller. Better. Cheaper

• Today, experimenting “makers” cobble together parts in order to create simple sensors that gather data and send it to a specified location. In the near future, users will buy complete units and, for instance, snap them into the chassis of their modular cell phone, obviating the need for a specialized sensing instrument.
• Google’s Advanced Technology and Projects (ATAP) group, in fact, is leading Project Ara, an effort to make such a device, which would allow users to purchase components from an App store-like entity and plug them into a basic mobile phone so that users can create their own cell phones, with the features they care most about. Many of those components could be highly refined sensing devices.
• We’re living in the age of the electronic sensor. Sensors will continue to improve, while both proprietary and FOSS software will help to make sense of all the data that the sensors generate. As FOSS platforms become more mature, however, users will not need specialized skills to use the technology. Sensors will be more accessible to people in the developing world , who will be able to lead their own sensor driven development programs.