Dr ‘Bosun Tijani, the Honourable Minister of Communications, Information, and Digital Economy, has unveiled the list of selected recipients for the Fourth Industrial Revolution Technology Application (4IRTA) in Agriculture. The 4IRTA initiative serves as a platform for executing demonstration projects utilizing Fourth Industrial Revolution technologies, including Unmanned Aerial Vehicles (UAVs), Internet of Things (IoT), Artificial Intelligence (AI), and Blockchain, across various sectors of the economy. These projects are conceived as pilot initiatives, illustrating the successful implementation of these advanced technologies within Nigeria.

Each of the ten chosen beneficiaries is slated to receive funding amounting to N10,000,000. This financial support will facilitate the in-depth integration and application of Fourth Industrial Revolution technologies within their respective domains. The projects undertaken by the selected grantees will serve as exemplars, showcasing the successful incorporation of 4IR technologies into practical use in Nigeria.

Announcing the shortlisted grantees, the Communications Minister said in a post on his LinkedIn profile: 

In support of President @officialABAT’s mandate to cultivate 500,000 hectares of land across Nigeria to boost food security, I am pleased to announce the 10 shortlisted grantees for our Fourth Industrial Revolution Technology Application (4IRTA) in Agriculture.

In November last year, we invited applications from applicable market-ready innovations that leverage 4IR technologies (UAVs, IoT, AI and Blockchain) to enhance productivity in Nigeria’s Agricultural Sector.

In the 2 weeks of the application process, we received 2,329 applications, which then went through 2 rounds of reviews, supported by top 4IR Technology researchers and practitioners of Nigerian descent across the globe. The reviews applied criteria such as the alignment of the proposed solution with the objectives of 4IRTA, solution readiness and the quality of their video demonstration.

Congratulations to the 10 selected projects as we look forward to working with them in partnership with the Ministry of Agriculture @NGfmafs to support their path to scale and sustainability.

The selected projects are listed below:

1. Agri-Wing Project: Integrated Aerial Precision (IAPrecision) that proposes a solution for smallholder maize farming utilizing drone technology throughout the maize farming cycle to collect real-time data and provide tailored recommendations. It will also use UAVs for fertilizing and applying crop protection products, aiming to address challenges such as pest outbreaks, labor scarcity, and health risks, with a focus on stakeholder engagement for widespread adoption and scalability in Nigeria’s agricultural sector. 
2. Ranch.ID LivestockPro: This is a farm management tool that utilizes loT technology and the National Animal Identification and Traceability system, providing real-time data on livestock activities, location, health, and vaccinations to enhance productivity and decision-making processes, with sophisticated devices ensuring continuous monitoring and prompt medical intervention for optimal livestock management. 
3. Precision Farm Management: The solution employs precision farming technology, specifically drones and sensors, to implement organic farming techniques by monitoring soil and crop data, including soil health, elevation, water level, nutrient level, pH, and crop health. The implementation ensures improved crop performance through climate-smart, precise application of agricultural inputs like fertilizers using spray drones, minimizing waste and increasing yield. 
4. Automated loT-Based Irrigation System: The Automated loT-Based Irrigation System utilizes sensors to monitor soil moisture and weather conditions. This data is then transmitted wirelessly to a central hub where it is analyzed by a microcontroller or microprocessor. The system automatically adjusts irrigation based on real-time data, ensuring precise and efficient water usage. 
5. Geospatial Intelligence model for enhanced prediction of crop yield and crop stress assessment: The solution deploys are in loT isotopic table and UAV radiometer radar L-band to monitor water tables and assess soil health, guiding decisions on land fertility and planting times. It provides real-time status assessment, harvest predictions, and insights on pest and weed control. 
6. AgriTrust Solutions by Ledger Labs Ltd: This solution utilizes the blockchain to ensure transparency and make deliveries more efficient. It also intends to solve for fake products in the market. 
7. Alfor Livestock diseases and health reporting: The project aims to empower livestock farmers through a geospatial-enabled mobile app for reporting instant livestock anomalies, utilizing Artificial Intelligence to predict vulnerable Zones and disease spread, and storing data securely on a blockchain to provide farmers with comprehensive information on common diseases, enabling informed decisions regarding insurance, credit, and relief. 
8. loT Climate-Smart Device: Penkeep Climate-smart loT device that manages environmental factors such as temperature, humidity, air quality, water level, and water temperature in poultry and fish farms, making real-time adjustments based on advanced sensor data to ensure optimal conditions. It is complemented by FS Manager, an Al advisory platform that offers analytics on climate trends, disease diagnostics, market dynamics, weather forecasts and best farming practices. The product is commercial. 
9. Smart Pond (SP): The SP solution utilizes pressure sensors for accurate fish growth rate assessments, motion sensors for anti-theft alerts, and automated feeders to ensure precise feeding and cost reduction. The smart pond, currently in the prototyping phase, 
10. Future Fish Farms: The Smart Fish Farm employs sensors for real-time fish health and water monitoring, offering instant access to farmers via a mobile app and storing data in a database fueling a machine learning algorithm. It optimizes fish growth by determining ideal water conditions, feed amounts, feeding times, and brands, integrating computer vision, automating tasks, and providing proactive notifications. Currently in the prototyping phase. 

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