aWhere

Product Description

aWhere is an agriculture intelligence platform that uses data analytics to give farmer the information needed to make decisions based upon real-time data. They collect and process over 8 billion data points daily from across the planet to produce their analytics platform. They provide these data to partners to promote farmer productivity, more resilient communities, and improved food security.^{Interview with representative}

Target SDGs

SDG 2: Zero Hunger

Target Users (Target Impact Group)

Small and Medium-sized Enterprises, NGOs

Distributors / Implementing Organizations

Partner NGOs, businesses or governments. Below are a few of their partners:

Vodafone - Farmers Club
iShamba
Esoko

Manufacturing/Building Method

aWhere is a SaaS (Software as a Service) application that has built out an object oriented framework that allows their application or partner's api access to their data sets. They have built out "foundation databases" which are comprised of public or low cost data sets that are available to everyone, but they are applying their technical expertise to compile these disparate data sets together. aWhere Overview and Capabilities Statement

Intellectural Property Type

Trade Secret

User Provision Model

Users can directly subscribe to aWhere's services here where they offer a two week trial. Data for specific areas of interest can be queried by contacting aWhere. aWhere APIs can be accessed by subscribing to a package with different conditions and pricing.

Distributions to Date Status

aWhere has 400,000 - 500,000 small holder farmers who access their data sets through partners.Interview with representative

Design Specifications

aWhere provides insightful direction for pre-season and in-season decisions, weather data specifically built for agricultural insight, and does not collect any personal farmer information. More information on aWhere's development community All of aWhere's API codebase is available on GitHub.

Product Schematics

Technical Support

aWhere offers support as part of the subscription service. A community Q&A service is recommended, apart from e-mail support.

Replacement Components

N/A

Lifecycle

N/A

Manufacturer Specified Performance Parameters

AWhere's mission is "to deliver the most complete agricultural information and insight for real-time agriculture decisions, every day, globally."

Vetted Performance Status

aWhere's partners have run field trials and have found: Esoko in Ghana - "89% of users received at least weekly texts and found the information meaningful." iShamba in Kenya - "The program has experienced a drop-out rate of only .45%. This is due to some polled farmers reporting yield increases of 50% and output increases of 80%, while 63% report having changed their practices thanks to the information provided by iShamba services."

Safety

N/A

Complementary Technical Systems

Statistical analysis software (Stata, R, etc.)
GIS software (OpenStreetMap, GeoNode, ArcGis, etc.)

Academic Research and References

While there is not any peer reviewed research on aWhere’s activities, their data sets are utilized in several academic papers:

Diaz R., Overholt W.A., Samayoa A., Sosa F., Cordeau D. and Medal J., 2008, Temperature-Dependent Development, Cold Tolerance, and Potential Distribution of Gratiana boliviana(Coleoptera: Chrysomelidae), a Biological Control Agent of Tropical Soda Apple,Solanum viarum(Solanaceae), Biocontrol Science and Technology, 18(2), pp. 193–207.

Mailafiya D.M., Ru B., Kairu E.W., Dupas S. and Calatayud P. A., 2011, Parasitism of Lepidopterous Stem Borers in Cultivated and Natural Habitats, Journal of Insect Science, 11(15), pp. 1–19.

Kamilaris A., Kartakoullis A., and Prenafeta-Bold F.X., 2017, A Review on the Practice of Big Data Analysis in Agriculture, Computers and Electronics in Agriculture, 143, pp. 23-37.

Archer, E., Conrad, J., Münch, Z., Opperman, D., Tadross, M. and Venter, J., 2009, Climate Change, Groundwater and Intensive Commercial Farming in the Semi-Arid Northern Sandveld, South Africa, Journal of integrative environmental sciences, 6(2), pp. 139-155.

Kaur, R., Garg, R. and Aggarwal, H., 2016, Big Data Analytics Framework to Identify Crop Disease and Recommendation a Solution, IEEE 2016 International Conference on Inventive Computation Technologies (ICICT), Vol. 2, pp. 1-5.

Ulzen, J., Abaidoo, R. C., Mensah, N. E., Masso, C. and AbdelGadir, A. H., 2016, Bradyrhizobium Inoculants Enhance Grain Yields of Soybean and Cowpea in Northern Ghana, Frontiers in plant science, 7, pp. 1770.

Setimela, P. S., Zaman-Allah, M., and Ndoro, O., 2018, Performance of Elite Drought Tolerant Maize Varieties: Across Eastern and Southern Africa, CIMMYT.

Compliance with regulations

According to their terms and conditions page aWhere is compliant with all applicable privacy and data sharing laws or regulations.

Evaluation methods

The product was evaluated for user satisfaction in delivering meaningful information, and its ability to increase crop yields and change practices.

Other Information

Implemented by

University of Toronto Water and Energy Research Lab

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