Mobile crowd participation as innovative methodology for water research

Develop and apply MCP as an integrated research tool for water supply in the local context through behavioural adaptation and end-user participation.

Research Questions 

1. Within what boundary conditions is MCP a sound method to acquire data sets that non-selectively represent the targeted crowd (e.g., coverage, phone owners, phone types)?
2. Which behavioural adaptations are required to embed SPWS in the local context?
3. How can mobile crowd sensing be used for detection of water quality, system malfunctioning (e.g., leakage detection) and end-user service (e.g., 24/7 supply, demand)?
4. How can MCP data be combined with knowledge-based models (geo/water; SP2 and SP3) towards visualization of contaminant occurrence and exposure in a delta (combining water quality and water access)?

Methodology

1. Interviews at urban laboratories and literature review to identify generic and context specific boundary conditions for MCP.
2. An app for illiterates will be built using agile software development methods in short ‘sprints’ resulting in a complete product. This allows for early and regular delivery, end user testing, evolutionary development, continuous improvement, and a flexible response to new insights. This enables the empirical validation of boundary conditions. The app will be developed in three focal areas:

Behavioural change and monitoring app:

The app can use the location information collected by the GPS in smart phones to monitor patterns of mobility (Studio Bereikbaar, www.studiobereikbaar.nl). Photos of leakage or malfunctioning equipment can be sent to responsible stakeholders creating a log of the issue including time stamp and location (AKVO Flow, www.akvo.org), which creates an incentive for repair action. Additionally, detection of vibrations and water level changes (www.mobilewatermanagement.com) will be investigated as tool for SPWS monitoring.

Water quality app:

For water quality analyses, it is aimed to develop an app that can measure arsenic, iron and salinity (as Cl or EC) concentration with a smartphone camera in combination with inexpensive (colorimetric) test kits (such as HACH, Wagtech). A photo of the test strip against reference sheets can be sent with exact location data and a photo of the tap or well. Alternatively, when relying on the co- occurrence of arsenic with iron, one can utilize the platform and sediment discoloration methods (Biswas et al., 2011; Hossain et al., 2014) for arsenic contamination detection without the need of a testkit. Water quality measurements will be integrated with the Google maps arsenic patches of SP2 for a safe source selection app.

Payment app:

Currently, payments are hard to collect, making a payment app very attractive for sound SPWS business models, e.g., BKash (Bangladesh) and Bill Pay (India). Additionally, the app can facilitate pay per use in the future, while flat rates are currently being paid.
3. The collection, use and visualisation of MCP data to test hypotheses on the use of SPWS based on a behavioural model.

Contributors

The character of SPWS matches the dynamic urbanizing regional context. However, it also requires fundamental understanding of interacting social and technical conditions, guaranteeing rootedness in site-specific contexts.