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Like every other industry, artificial intelligence (AI) has also made its way into agriculture, where its market is expected to be worth $4.7 billion by 2028. Of the major agriculture fields – indoor farming, field farming, and livestock – field farming makes up the most of this market, with a share of 60%.

AI facilitates the implementation of precision farming, a novel technology-led approach toward crop management, where farmers optimize resources by varying how much and where to apply inputs (seed, fertilizer, water) based on tree-level farm insights.

It helps improve efficiencies and reduce costs by using advanced sensors, computer vision, and machine learning algorithms to analyse the data from various sources, like satellites, weather stations, drones, and equipment, for data-driven farming.

Here’s an overview of how AI and drones, particularly Aya Data’s precision agriculture solutions, can enhance agricultural output and lower costs for bigger plantations and small to mid-level plantations alike.

Challenges of Efficiencies in the Agricultural Space

In an article published in the African Journal of Food, Agriculture, Nutrition, and Development, the author established that climate change, post-harvest losses, and water scarcity are critical constraints to agricultural productivity in Africa. They also stated that creative innovation is imperative to sustainable agricultural growth in the region.

Agricultural inefficiencies, such as wasted resources and high labor costs, result in higher input capital. Additionally, 60% to 80% of African farms are manually operated, as most of the cultivation is done with hand-held tools and human muscle power.

Traditional agriculture in Sudan

Due to this, there’s often a lack of precision in farming practices, leading to inconsistent yields and reduced profitability.

Another major challenge in this space is the lack of data. Most farms are reluctant to adopt AI or automation solutions, such as drones for agricultural use, due to high costs and a lack of understanding of the technology.

The reluctance ultimately results in a significant gap in data collection and analysis, hindering efforts to improve efficiency and productivity. More so, the lack of digital assets on such farms further exacerbates these challenges.

study conducted by the University of Kent’s School of Economics shed light on this matter. Researchers found that the aversion to technology stems from the risks associated with modern technologies for small-scale farmers, such as high maintenance costs and the need for specialized knowledge.

To add to these challenges, the number of people working on farms is also declining. The younger generation is migrating to urban areas, leaving behind an aging population of farmers. 

While sub-Saharan Africa’s population has increased from 700 million people to more than a billion, the proportion of farmers has decreased from 65% to 57%.

How AI-Based Precision Agriculture Solutions Are Revolutionizing the Agri Space

According to the African Development Bank President (AfDB), Akinwumi Adesina, the agriculture business in Africa will be worth $1 trillion by 2030. In the same vein, McKinsey reports that agricultural productivity in southern and eastern Africa could double or triple with the adoption of modern technologies, like crop scouting drones

AI and modern technology equips African farmers with the means to bring these ambitious numbers to fruition.

Transport of banana plants

Precision agriculture services not only eliminate guesswork in planting and maintenance processes, but also provide data-driven insights into soil conditions, the number of trees on a plantation, and even blank spots that can be cultivated. 

A study presented at the 3rd International Electronic Conference on Agronomy found that precision agriculture with geospatial intelligence and AI reduces pesticide and fertilizer use by up to 30% and conserves up to 50% of water used in irrigation.

AI-powered crop scouting drones and satellites can also help farmers monitor their crops and detect early signs of diseases or pests. The United Nations Development Program (UNDP) reported that drone payloads, such as RGB and hyperspectral cameras, can monitor plant defects, calculate chemical attributes, quantify soil vegetation, and detect nutrient deficiency.

How Aya’s Precision Farming Solution Can Help

Drone usage on a farm 

Aya Data’s precision farming solution (AyaGrow), utilizes field survey and satellite and drone data,  combined with proprietary AI models, to provide a single source of farm data, tree-level analytics, and actionable insights for crop monitoring and precision agronomic decision-making.

These technologies work in sync to help farms reap the benefits of precision agriculture.

Improve Efficiencies: Since AyaGrow digitizes manual processes, farmers can save time and reduce labor costs, eliminating the need for lengthy and time-consuming paperwork. The tree-level reports on crop health allow farmers to make quick and accurate decisions rather than relying on guesswork. For example, instead of applying fertilizer at a blanket rate across the farm,farmers will be able to pinpoint the exact trees that need treatment and exclude those that don’t.  AyaGrow makes it possible to examine the exact tree health rather than work with estimates. The AI solution also allows you to visualize plant health through vegetation indexes to detect nutrient deficiency before it causes major plant damage.

Reduce Operational Costs: AyaGrow uses drones and satellites to handle the bulk of data collection and analysis, reducing fuel, labor, time and maintenance costs associated with traditional methods. For example, manual labor can take months to count the number of trees on a large farm. On top of that, farmers would have to pay them. With AyaGrow, the time can be reduced to hours, freeing the labor for other manpower-intensive tasks. Since Aya’s tree counting model has a precision rate of over 99%, it’s just as good if not better than manual counting.  

Our precision agriculture services facilitate tree counting, yield forecast, nutrient deficiency detection, pest and disease detection, and blank spot analysis. 

Aya’s case studies are a testament to how the company’s precision farming solution has helped small and large-scale farmers transform their operations. No matter where you are in your AI journey, Aya is ready to partner with you.

At Aya, our customer experience is rooted in our client feedback loop, post-purchase engagement, advanced solution architecture, and timely communication. We also ensure unwavering quality services by employing innovative solutions and prioritizing efficiency and speed in all projects. 

Our expertise in AI precision agriculture solutions comes from domain-specific knowledge, and external partnerships with industry specialists, such as agronomists  and drone experts. We strive to empower African farmers by assisting their AI innovation journey and solving their problems through our resourcefulness and industry authoritativeness. 

Conclusion 

Be it digitizing your data to make you AI-ready, building a customized AI solution from scratch or integrating AI into your existing operations, Aya Data is equipped and ready to help you. 

Aya’s services are backed by our key differentiators, including matchless experience, expertise, and quality in terms of niche knowledge, transparent practices, swift issue resolution, and external partnerships with specialists. Being African-led, we design our solutions with the local context in mind, so our clients can expect customized solutions tailored to their needs.

Book a free consultation to learn more about our precision agriculture solutions.

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