DIY IoT Gaining Traction
Apr 28, 2012
6 minutes read
Photo by

Photo by dustintodd

Citizen sensing has been getting attention in this past quarter thanks to the outstanding efforts of the community behind the Air Quality Egg (AQE) project. AQE is a DIY Internet of Things project aiming to give citizens a way to participate in the conversation about air quality. After weeks of design discussions on its forum and several workshops, it finally entered Kickstarter, a popular crowd funding platform. It reached its funding objective in a mere 4 days. Initiated by Ed Borden of Pachube, AQE is an open hardware effort involving experts in DIY electronics, design, air quality, and software. I have ordered my kit and look forward to reproducing the unit already assembled by the people who attended AQE workshops.

Another remarkable event was the water hackathon involving both Pachube and Ushahidi. David Kobia and Dale Zak, two Ushahidi linchpins, joined forces with water and DIY sensemakers to integrate hard sensing and soft sensing into a single experience. Leif Percifield of the project, contributed the design for the combined sewer overflow sensor.

These projects are still experimental but prove already to be invaluable resources for defining new paths in citizen participation. They raise numerous questions around skills, objectives, participation, education, or communication to name obvious ones. For example, the first attempts by Ed to deploy air quality sensors in London forced him to improvise and purchase Internet access hardware as he faced suspicion. I can also think aspects related to electronic waste after someone has lost interest in a sensor project. I imagine projects involving hard sensing will propose take-back procedures in line with regulations such as WEEE to its participants…

I recently turned in the small thesis on citizen sensing that completes my course in sustainable development. In the document, I highlighted 5 CO-PLOt axes which seem particularly important to me when designing citizen sensing projects.


Citizen sensing is fundamentally a bottom-up approach. It leverages the power of ICT to coordinate efforts across tens or hundreds of participants approaching problems in different ways than institutions traditionally did. The opportunities for seeking synergies between both approaches is compelling. Citizen sensing samplings and derived indicators are not competing with traditional top-down indicator for at least two reasons: accuracy and granularity. Instead, they complement each other. At the recent IoT-4-Cities event in Lausanne, Andrea Ridolfi of OpenSense presented the work around air quality sensing in Switzerland. Andrea presented a solution of sensors mounted on public transportation vehicles in Zurich in Lausanne and expressed his interest in the Sensaris presentation of portable personal sensors. There is a place for all 3 levels of measurements at macro- meso- and micro-levels to be integrated into an indicator system yet to be devised.


Projects incorporating the making of hard sensing instruments for citizen sensing have been making use of open hardware components. The bill of materials and actual hardware design are transparent and discussed within the group. The data collected is publicly accessible and can be processed by anyone. This way, instrument making, data gathering and data crunching remains open to all. This allows citizens, sensemakers as Ed calls them, to contribute small, discrete, amounts of time and take ownership of environmental issues according to their own time availability and skills. Openess should also apply to the shared model of understanding which puts field data into a wider systemic context for learning purposes. The model itself is open and subject to iterative revisions by the community. Openess is the basis for the participation and learning.


There are numerous ways to participate in citizen sensing projects: making instruments (hardware or software), contributing observations, data crunching and shared model development. Soft sensing is based on our 5 senses and submitted over an application. In the case of feature phones, it’s essentially data via SMS. In the case of smartphones, it’s a native or mobile web app which is designed to receive multi-media reports. Hard sensing involves the use of hardware sensors along the lines of AQE. The second form of participation is the data contribution in itself. You could simply acquire an instrument or install a mobile app on your phone and participate. Once the data has been captured, it is made available to a third group of participants familiar with tools such as R, incanter or other data crunching tools to identify patterns in space and time. Finally, there’s the shared model of understanding which involves the participation of modelers and domain experts to refine the understanding of the phenomena being monitored. The shared model of understanding is a representation of the group’s understanding which feeds group education or learning around the subject.


Citizen sensing projects see individuals take ownership of real sustainability-related problems and learning plays a fundamental part in a secondary feedback loop above the many first sensing loops. A shared model of understanding feeds from the micro-sampling that takes place on the ground. The data collected is placed in the context of a wider model that helps participants, as well as outsiders, better understand the bigger picture. The model is co-created and subject to revision as the group’s understanding evolves. The model also leads to new research questions and new projects.

I am currently reading Companion Modelling A Participatory Approach Supporting Sustainable Development by Michel Étienne. The book presents 27 case studies based on ComMod, a method developed over a period of 10 years across numerous ecosystems. The objective of the method is to facilitate dialogue, shared learning and collective decision-making to strengthen the adaptive management capacity of communities through integrative collaborative modelling (François Bousquet). The team has gathered extensive experience in the use of multi-agent systems to model concrete systems, e.g. the Senegal River Valley irrigated systems. See also JASSS for more publications on ComMod. This is not the only approach centered around a shared model of understanding. I have mentioned the work of Krystyna Stave of the University of Nevada in a previous post. Stave uses System Dynamics models to model the situation.


Last but not least, there’s organization of the citizens involved. Citizen sensing projects imply recruiting and coordinating a large number of participants spread across wide areas. In the case of AQE, coordination is managed through a forum and regular meet-ups at key locations – Amsterdam, New York, London and Madrid. Key members of the project have been traveling to these cities to ensure a coherent execution. The forum allows a wider crowd to participate and keep track of relevant information and material relevant to the project. The organization balances costs with the complexity of the instruments being designed and assembled. But other constraints can come into play. Covering large to very large areas or operating under time constraints (e.g. environmental disaster) requires special considerations when designing a suitable organization. These considerations include the ability to retain autonomy of the groups involved, coordination mechanisms, resource allocation mechanisms, or group identity at each scale. These go beyond the mere use of social media and can be addressed through variety engineering practices. Variety is a term borrowed from Ross Ashby and nicely explained by @JavierLivas in this this short video on management cybernetics.

We frequently go over these CO-PLOt dimensions in calls with my co-conspirators @phisab and @EuroVilles. I trust we’ll find ways to refine these and use them perhaps for assessments and project definition guidelines…

Creative Commons License This material is licensed under a Creative Commons Attribution 3.0 Unported License

Back to posts

comments powered by Disqus