2017 Winner & 2018 Scale Up WinnerSeeing is believing: Using smartphone camera data
The Inspire Challenge is an initiative to challenge partners, universities, and others to use CGIAR data to create innovative pilot projects that will scale. We look for novel approaches that democratize data-driven insights to inform local, national, regional, and global policies and applications in agriculture and food security in real time; helping people–especially smallholder farmers and producers–to lead happier and healthier lives.
This proposal was selected as a 2017 winner, with the team receiving 100,000 USD to put their ideas into practice. The team won the Scale Up award the following year, receiving an additional USD 250,000 for their outstanding ability to demonstrate the project’s proven viability and potential for impact.
Seeing is believing: Using smartphone camera data
Agricultural risk management solutions, for instance insurance and advisories, can improve management practices, productivity and profitability of smallholder agriculture. But these services often do not incorporate potentially useful information on crop health or crop growth observed by farmers themselves in their fields. The “Seeing is Believing” project therefore aims to integrate visible crop characteristics, derived from farmers’ own smartphone pictures, in delivering personalized agricultural advice and insurance services. The smartphone pictures will give “eyes on the ground” to optimize agronomic decision-making and claims settlement.
Using farmers’ self-collected camera data to provide agricultural services is unprecedented. In the recent past, costs associated with sending and processing large quantities of real-time plot-level camera data were too high, as smartphone ownership and mobile network penetration were low, and processing images would require significant human resources, data storage and bandwidth. However, advances in technology have improved smartphone ownership and reduced costs associated with collecting smartphone camera data.
In the first phase, the project found that real-time crop data obtained from smartphone pictures can empower data-driven farming through three channels:
- Experts can target messages towards a farmer’s individual situation, raising the value and timeliness of the advice;
- The tangibility of pictures can increase ownership and take-up of the advice as well as the insurance product;
- Insurers gather more monitoring data and provide recommendations on how to minimize risk, thus lowering expected insurance payouts.
In the second phase, the project will test alternative models for scaling, targeting a retail product for commercial crops, bundling with credit to unlock finance for small and marginal farmers, and integration into CABi’s flagship program PlantWise, which provides advisories around integrated pest and disease management to members of Farmer Producer Organizations (FPOs).
The project will provide picture-based agricultural advice and insurance to smallholder farmers in different sites in India through a dedicated smartphone application. This application has built-in features designed to facilitate the advisory and insurance process, minimize moral hazard, and limit tampering. Through this application, farmers take geotagged time-stamped pictures of insured sites from sowing to harvest. In response, timely and relevant agriculture advisories are being generated from the images alongside satellite imagery and localized data, and the images are being used in claims settlement.
The project will vary whether the insurance product, provided in partnership with HFDC Ergo General Insurance, is bundled with advisories, to test whether such bundling improves risk management, reducing expected insurance payouts and thus insurance premiums. In this way, the project will shed light on whether there is a business case for insurance providers to deliver advisories.
Berber Kramer | Email
Step by step
The project was one of five winners of the Inspire Challenge 2017 and was awarded US$100K at the inaugural annual convention of the CGIAR Platform for Big Data in Agriculture, during 19-22 of September.
Training local experts in picture-based advisory messages
The project trained four local agronomists in interpreting the images and sending out advisories based on cues visible in pictures taken by farmers from sowing to harvest on their insured plots.
The project developed an online platform, linked to an improved version of the smartphone application WheatCam, where the trained agronomists could review individual farmers’ pictures and push remote picture-based advisory messages (PBA messages) directly through the App into the farmer’s phone.
Piloting the service in 200 villages
The project piloted and tested the service through a cluster randomized trial with 200 villages in Haryana and Punjab, India. Villages were randomly assigned to one of three interventions:
- farmers in 50 villages received conventional interactive voice response (IVR) and SMS messages (control group);
- farmers in 75 villages received personalized, picture-based advisory messages (PBA treatment); and
- farmers in the remaining 75 villages received picture-based insurance (PBI) coverage on top of the IVR, SMS, and PBA messages (PBA + PBI treatment).
Assessing the results
[Photo: Madhulika Singh/CIMMYT]
The project broadcasted IVR and SMS messages to a total of 32,237 wheat producers. Results show that the advisory messages increased knowledge on best agricultural practices by 78 percent and revealed strong complementarities between PBA and PBI.
Engagement in the PBA service — measured as the number of pictures submitted and farmers’ satisfaction — was significantly higher when bundled with PBI, and while willingness to pay for PBA alone was negligible, respondents were willing to pay an extra 8.7 percent of the insurance premium when PBA was embedded in the PBI product.
Finally, greenness indices derived from the crop imagery could predict the onset of growth stages during which crops are more vulnerable to weather risk, thereby outperforming satellite vegetation indices; and project partner BKC WeatherSys – one of India’s first private sector meteorology and environmental technology companies and the first private sector entity in India to run numerical weather prediction models – was able to train a convolutional neural network that predicts crop damage with higher accuracy than BKC’s existing agronomic software (using crop models, weather data and satellite imagery) to provide advisories.
Towards smart weather index-based insurance products
With funding from the UK Natural Environmental Research Council (NERC) and the International Initiative for Impact Evaluation (3ie), and the CGIAR Research Program on Policies, Institutions, and Markets (PIM) the project was able to deepen its collaboration with HDFC.
HDFC, IFPRI, and Manchester University are using ground pictures, satellite imagery, weather data, and crop models to design smart weather index-based insurance products; and these products will be implemented and evaluated rigorously through a four-year impact assessment in Haryana State.
As such, HDFC will roll-out PBI products in 2018 for a range of crops (wheat, paddy, tomatoes, and potatoes) in four districts in Haryana, and the project is engaging closely with the Haryana Departments of Agriculture and Horticulture for implementing these products in their state-wide programs in subsequent years.
Given the observed complementarities with PBA, the project proposes linking HDFC to advisory service providers that can help HDFC in harnessing big data for crop damage prediction and remote advisory provision.
HDFC and IFPRI entered high-level conversations with the Odisha and Tamil Nadu State Governments, and the project was approached by ACRE Africa and KALRO to implement PBI complemented with remote advisory services in Eastern Africa. Resource mobilization to expand into Eastern Africa is currently well underway, with two major proposals under review.
Scale up plan
In 2019, with the support of the Inspire Challenge, the project will scale-up its efforts by evaluating the cost-effectiveness of alternative models for scaling. Part of this plan will be to introduce an automatic analysis service to process data at a larger scale, and to collect ground data for expanding into other crops in the state of Haryana.
Additionally, in the state of Tamil Nadu, the project plans to engage existing services such as Plant Doctors and Plant Clinics set up by CABI International to make integrated pest management services more comprehensive; and in the state of Odisha, the project plans to use georeferenced smartphone pictures combined with satellite imagery to expand access to credit for landless farmers.
Integrating picture-based insurance and advisory into the national crop insurance scheme in India
There is also the potential to integrate picture-based insurance and advisory into the national crop insurance scheme to improve farmer engagement and encourage the adoption of recommended practices. As a result, this may help to reduce basis risk and delays in claims settlement, improve farmer satisfaction, and promote risk prevention, which can help to reduce insurance premiums.