Cycle 6 (2017 Deadline)
Scaled deployment of smart-phone agro-applications for field based diagnosis and real-time surveillance data collection
PI: Ernest Mwebaze, email@example.com, Makerere University
U.S. Partner: Jesse Poland, Kansas State University
December 2017 - November 2018
Cassava is a very important food security crop in Uganda and in the region and is a major crop grown by small-scale farmers who depend on it for their livelihood. The overarching goal of this project is to improve livelihoods of these small-holder farmers through provision of better tools that offer them actionable information about the health of their crops. This goal can further be broken down to two aims. The first centers around crowd sourcing of crop disease surveillance data from farmers. A total of 200 farmers will be provided with smart phones and, using several incentive schemes, will be encouraged to collect data about the state of health of their farms and gardens. The data will include both images and their geo-coordinates. The principal investigator’s hypothesis is that a great deal of data can be collected from all over the country cheaply and that this will be an empowering activity for the farmers. The second aim is to provide farmers with a system that can be used to provide real-time diagnosis of their crops. The mobile phones will be equipped with software that can calculate the state of health of a cassava crop by analyzing an image of its leaves. A farmer is therefore able to make the necessary early interventions in his garden.
This project draws on a prototype crowd sourcing system that the PI and his team have been testing for more than a year. They distributed phones to 29 people involved in agriculture in the different regions of Uganda and created a mobile phone application that they modified to allow the participants to take pictures of crops and upload them in real time. Data collected consists of an image of the cassava crop, the GPS coordinates, and a statement of whether the image taken is representative of disease, pests, or an anomaly. Using this current system the researchers collected more than 4,800 images from different places in Uganda (http://adsurv.mcrops.org/). Their PEER award will allow them to expand the network to 200 participants in order to generate evidence for a large-scale deployment of a digital system for crop disease surveillance data collection. In particular, they are interested in understanding how accurate the inferences from such data can be, how useful an on-field diagnosis application can be for smallholder farmers, and what incentive mechanisms work.
Summary of Recent Activities
In this quarter, the PI recruited students for the project. A total of 2 masters students were recruited, 1 graduate student who is serving in the capacity of project manager and 4 undergraduate students working as interns on the project. Of the 7 people, 2 are female.
On the research side of the project, they focused on setting up the structure to undertake the research aims. The project is focused on piloting a scale out of an ad hoc surveillance network by providing 200 smartphones to rural farmers in Uganda and have them report surveillance data in near real-time. The project also aims at generating evidence of the use of such a wide network of connected farmers. They held an initial workshop that brought together different players in this field including the Uganda National Farmers Federation, several representatives of farmers associations, academia and people from the Ministry of Agriculture in Uganda, specifically NARO. Workshop generated a lot of feedback that helped design its implementation.
The project team held an activity at the offices of the National Crops Resources Research Institute (NaCRRI), the body responsible for surveillance of cassava in Uganda. This was a small activity mainly attended by farmers close to the offices. The goal was to test the whole system with this small group before scaling it out to the wider group. Several sessions were also held to prepare for the deployment of the equipment to the 200 rural farmers. Particularly this involved setting up and testing the equipment, setting up the training materials, organizing for logistics of the different farmer training workshops and setting up the telecommunication network to support the transmission of data from the farmers. A huge proportion of time was spent on this activity.
So far the PI and his team have held 5 training and deployment sessions in the different selected regions to at least 150 farmers. This is an activity that is currently ongoing, at the end of which we should have a fully functional network of small holder farmers interfacing with the system.
This phase has mainly focused on set up of the project. In the the next 3-6 months, the team will focus on how the network of farmers is being leveraged to support surveillance tasks. Specifically, they plan to carry out the following activities:
1. Completing training and deployment of devices. They will carry out 7 trainings at 7 different locations across Uganda, targeting 30 - 40 farmers within the different localities. This will be concluded by end of April/early May.
2. Testing and monitoring the live network of 199+ farmers exchanging information
3. A mid-term review of the system towards the end of the next quarter to ascertain usage patterns and address any issues the small-holder farmers may have.
4. Attending a hackathon (2 members of the team) in the US (mid July 2018), where aspects of the mobile phone application they are using will be discussed.
5. Possible dissemination of the current system set up and early results through a blob entry
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