There are over 500 million smallholder farms in the world. They make up a significant portion of the world’s poorest people, living on less than $2 a day, and they produce about a third of the world’s food. Our goal with SolarSENSE is to make some of the technology that is typically only available to large industrial farms more accessible to small family farms. This helps them adapt their farming practices to the impacts of climate change.
The primary aim with this initiative is to aid 250,000 smallholder farmers across sub-Saharan Africa in enhancing crop yields through the implementation of conservation agriculture practices.
SolarSENSE has been tested in fields around the world and was exhibited at SaloneSatellite in Milan, Italy.
This project is in progress.
Role
Industrial Design
Dimensions
Width: 9.5 cm
Height: 19.7 cm
Don Norman Design Award Finalist
Some Context
SolarSENSE is a project by the SolarSPELL initiative at ASU to expand on the mission of designing solutions that deal with remote off-grid infrastructure issues globally. SolarSPELL is a global educational initiative that combines curated digital libraries, solar-powered technology, and the training to build information literacy and internet-ready skills in offline environments, focusing on the half of the world that remains unconnected.
More information about SolarSPELL can be found here: solarspell.org
Background
At current estimates, there are more than 608 million family farms around the world. Because these farmers account for such a large portion of the world’s poor, and are vital to the world’s food supply, improving the lives of this group is essential in the fight to end global poverty and hunger. Recently, more and more research has been focused on these farmers and the challenges they face.
Existing smart sensing systems for commercial farms can cost tens of thousands of dollars. In addition, deploying wireless networks cost, on average, another $50,000. SolarSENSE utilizes solar-powered low-cost soil sensors which connect wirelessly with SolarSPELL’s off-grid and off-network technology to allow farmers to easily access valuable information and data. This presents a powerful yet affordable approach to help small-scale farmers adapt to changing agricultural practices.
Process
The development of SolarSENSE has been a continuous and interactive process as we have spent time in the fields with farmers to understand their perspectives and needs. Thus far, we have met with farmers three different times to get feedback on our progress.
We are collaborating with two NGOs, B2R Farms in Rwanda and PPC Madagascar, to monitor, evaluate and truly measure the impact of SolarSENSE. These groups are dedicated to educating small shareholder (subsistence) farmers on transitioning to conservation agriculture practices.
Bringing Affordances
to the Front
I explored different shapes and form factors that would fit the required components while being visually dynamic with a specific focus on interactions and affordances.
I then used Rhino 3D to quickly model in higher fidelity. I explored different orientations and placements of the internal sensors and components and then iterated towards the final form.
Surface Analysis
Testing in the Fields
SolarSPELL initiative co-founders, Dr. Laura Hosman and Bruce Baikie, testing SolarSENSE and SolarSPELL prototypes on a farm in Rwanda.
SolarSENSE has been put to use on farms across Rwanda, and Madagascar.
How it Works
SolarSENSE uses ESP32-based sensor nodes developed in-house by ASU teams. These sensors communicate with an an MQTT broker running on Raspberry Pi 3. This structure makes it possible and easy to add additional sensor nodes in the future as needed. Soil data is collected by connecting to the SolarSPELL Web API which is then displayed through an open-source web interface.
Next Steps
SolarSENSE allows farmers to test their soil and get the information straight onto their wifi/bluetooth capable devices through a browser. However, this raw data isn’t always useful if the user doesn’t know what it means. We are currently working on incorporation TinyML into SolarSENSE so that farmers can get easy access to not just the data about their fields, but also actionable insights into what that all of that information means and what to do about it.