Agriculture
February 24, 2024
Multi-Crop Ewing Grinder
Read SolutionImplemented by
Compatible Technology International
Updated on May 24, 2024
·Created on July 17, 2017
aWhere is a SaaS (Software as a Service) application that collects and analyzes over a billion points of data from around the globe each day to create agricultural intelligence.
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:
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.
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
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.
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