The Inspire Challenge is CGIAR’s signature digital innovation process. It leverages the global footprint and deep food security subject matter expertise of CGIAR with expert industry partners to link digital technologies to impact in developing economies.
The winners and finalists of the 2020 Inspire Challenge are presented below. The winners were announced during the virtual Big Data in Agriculture Convention “Digital Dynamism for Adaptive Food Systems” on 19-23 October.
An Inspire 2020 winning project that proposes to develop a mobile app called Croppie to generate large volumes of ground-truthing photographic data from farmers in Peru and Uganda and train an AI/ML model that will generate predictive yield insights in actionable formats, for more effective planning, risk management and resilience.
An Inspire 2020 winning project that proposes to develop an app called N-ALLyzer to assist farmers in making optimal economic decisions on fertilizer application rates, with minimal user input. Unlike the traditional nutrient calculations, the app requires simple mobile phone-based pictures of maize or wheat leaves and answer few key questions on farming, to generate fertilizer recommendations customized using big data analytics and simulations.
An Inspire 2020 winning project that proposes to develop 360-degree locust monitoring tool that leverages ClimaCell.co’s weather intelligence engine. The tool will be developed with end users and farmers to monitor all key aspects and share early warnings, increasing countries’ capacity to prepare and respond early and effectively to locust swarms.
An Inspire 2020 winning project that proposes to develop a novel and user-friendly tool called Citizen-H2D3, which will shift diet data collection away from static researcher-led methods towards dynamic citizen-led systems. The system will provide [near] real-time intelligence on individual daily dietary diversity and other nutrition and purchasing metrics that will help decision-makers to develop viable and contextually-relevant policies.
A Inspire 2020 winning project that proposes to improve an existing low-cost portable device for rapid aflatoxin detection in peanuts and maize using image processing under UV light. Better value for aflatoxin-free material will promote efforts towards post harvest handling and quality upkeep. This would help lower the amount of aflatoxin that enters our food chain and have multitudes of impact on population health.
An Inspire 2020 winning project that proposes to create TALIA, the first agricultural advisory hotline operated entirely by state-of-the art AI. Through a pilot in Costa Rica, using unstructured and structured data from research and extension partners the project will train an established natural language processing technology, IBM Watson, to become an AI-driven agricultural extension agent.
A Inspire 2020 winning project that proposes to establish the first-ever global data platform, which will consolidate data on rangelands, including rangelands health, change, risks and opportunities for restoration from existing sources as well as from new sources such as satellite imagery and crowd-sourcing.
Aquaculture and small-scale fisheries are increasingly recognized for their contribution toward poverty alleviation and nutrition in poor developing countries. Yet, aquatic food-hazards risk management for safe human consumption remains a major issue along supply chains.As an alternative to lengthy and costly laboratory analyses, this project proposes a portable, user-friendly point-and-shoot near-infrared (NIR) device for rapid field screening of key aquatic food contaminants.
An Inspire 2020 finalist project that proposes to use NFC (Near-Field Communications) cards in Mozambique as means to improve access to markets and learning on consumer preferences to improve emergency response. Going beyond agricultural subsidy e-vouchers, these cards provide a wider set of choices, including agricultural inputs, food items, and health services.
An Inspire 2020 finalist project that proposes to develop a scalable and cost-effective smart hermetic bin for farm produce storage. Thanks to IoT technology and machine learning algorithm, the smart bins will provide farmers in Kenya with an affordable storage solution that allows them to monitor the quantity and quality of their stored produce remotely, enabling them to wait for good market conditions to sell.
An Inspire 2020 finalist project that proposes to use multi-source satellite, geo/agro tagged in-situ data, machine learning and citizen science to design a digital augmentation platform to characterize farming systems to scale site-specific crops/varieties in countries where fallow can be replaced by short season legumes or vegetables.
An Inspire 2020 finalist project that proposes to develop a system called FarmPhone as a smart IVRS-based, 24×7, vernacular, interactive platform which will bring together producers, agricultural laborers, primary processors for grains and pulses, traders and bulk procurers, resident associations (including housing boards and slum clusters) and transporters, and enable transparent and connected fair trade.
An Inspire 2020 finalist project that proposes to use hyperspectral imaging and AI for automated early plant disease detection. If the project manages to identify a small selection of wavelengths thanks to AI, cheaper multi-spectral sensors can be manufactured and broadly deployed.
A Inspire 2020 finalist project that proposes to reach more people with biofortified crops by improving their traceability in the supply chain. The project plans to implement blockchain technology on the farmX app to help value chain partners improve transparency and efficiency of business transactions, compliance processes and tracking and tracing of food products.
An Inspire 2020 finalist project that proposes to develop climate-agri risk scores from unique field-scale satellite-based soil moisture and greenness data, and historical climate records to reduce the risk for MFIs when offering financial services to smallholders.